Soil Organic Matter Dynamics and Crop Productivity as Affected. by Organic Resource Quality and Management Practices on.

Transcription

1 Soil Organic Matter Dynamics and Crop Productivity as Affected by Organic Resource Quality and Management Practices on Smallholder Farms by Florence Mtambanengwe A thesis submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Soil Science & Agricultural Engineering Faculty of Agriculture University of Zimbabwe June 2006

2 To my boys, I have done this for you. Thanks for the unwavering support and for believing in me. You are my inspiration. This is just the beginning of many more challenges to come.

3 i Abstract Crop productivity in low-input agricultural systems is largely a function of the soil s capacity to hold and release nutrients in soil organic matter (SOM). Although sandy soils on most Zimbabwean smallholder farms inherently contain a small amount of SOM, large variability in soil productivity (fertility gradients) exists between adjacent fields or field sections within the same farm. Farmer management of such variability remains a challenge and sustainable option for soil productivity are required. This study was based on the hypothesis that SOM, a renewable resource, is the driving force behind sustainable crop productivity on depleted sandy soils. Relationships between maize yields and SOM contents, nitrogen (N) release patterns, and their links with organic matter management practices by farmers differing in resource endowment were evaluated under different Natural Regions (NR) in the smallholder farming areas of Chikwaka (NR II: >750 mm yr -1 ), Chinyika (NR III: mm yr -1 ) and Zimuto (NR IV: mm yr -1 ). The cumulative effect of applying known quantities of different quality organic resources on SOM formation and maize productivity was also evaluated on-station at Domboshawa (NR II) and Makoholi (NR IV) Experimental Stations following incorporation of sunnhemp (Crotalaria juncea) green manure, calliandra (Calliandra calothyrsus) prunings, cattle manure, maize (Zea mays) stover and pine (Pinus patula) sawdust into soil. Farmers perception of soil productivity was consistent with laboratory indices across the different rainfall zones. Criteria for ranking the most productive rich and least productive poor fields ranged from colour through elements of soil structure to crop response following external nutrient inputs. Laboratory analysis showed that rich fields contained significantly more soil organic carbon (SOC) ranging between 5-8 g kg -1, compared with between 3-6 g kg -1 for designated poor fields. Differences in SOC contents between rich and poor fields were wider in the old communal areas of Chikwaka and Zimuto with >70 years of smallholder farming than in Chinyika (<25 years), suggesting that the observed fertility gradients are a cumulative effect of years of differential management practices by the different farmer classes. Overall, rich fields received between t C ha -1 compared to t C ha -1 for poor fields with resource endowment apparently dictating the intensity of use. Organic inputs with a C:N ratio >25 (the bulk of available resources on-farm) contributed significantly to overall particulate organic matter (POM) size in sandy soils. The intensity of C management was reflected more in meso- POM ( µm diameter) compared to the macro-pom ( µm diameter) fraction suggesting that the larger POM fraction has a high turnover and is not protected from degradation. However, early season (within five weeks of incorporation) N availability from these materials was low (<5% of added N) resulting in poor maize performance during the vegetative phase. This may justify the high organic matter loading strategy of up to 50 t ha -1 employed by those farmers who often achieve yields of >3 t ha -1 on coarse sands. Practical management options for smallholder farmers who usually access low quality resources may include pre-application treatments such as composting or organic/mineral N fertilizer combinations to enhance N availability. The overall size of the organo-mineral fraction (<53 µm diameter) in these soils was small (<250 g kg -1 soil) and stable, and was not influenced by quality and quantity of C inputs and time over which they had been applied. High quality organic materials (e.g. sunnhemp) apparently enhanced the N-supply capacity of the organo-mineral fraction without necessarily increasing its size. However, such materials (C:N <25) released between 15-25% of added N within five weeks of incorporation, suggesting that a significant proportion of N is lost before uptake. The challenge is to enhance the efficiency with which N release from high quality materials can be managed. Maize productivity, and most likely that of other cereals, on depleted sandy soils was related to within-season mineral N fluxes and labile POM fraction. Both factors were

4 primarily a function of differential capacity to manage organic matter by different farmer classes. Sustenance of optimal maize yields on sandy soils may only be possible through regular supply of both high and low quality materials in combination with mineral fertilizers, particularly N. High quality C inputs are likely to enhance short-term nutrient supply capacity of a small organo-mineral fraction present, while slow decomposing materials would contribute towards the long-term maintenance of critical SOM pools. ii

5 iii Acknowledgements The study is an output of the Nutrient Use Efficiency and Soil Organic Matter (NUESOM) project (Grant 2002 FS 189) funded by the Rockefeller Foundation (RF). I am particularly indebted to my supervisor, Dr Paul Mapfumo for awarding me the PhD Fellowship, a rare opportunity to express my potential. Funds to kick start on-farm work were received from the RF s African Careers Award Grant to Dr Mapfumo while initial establishment of the Domboshawa and Makoholi on-station experiment was through seed money from TSBF- CIAT s African Network (AfNet). Work reported in Chapter 7 of this thesis was largely through a grant to Dr Paul Mapfumo from International Foundation for Science, Stockholm. I thank Dr Mapfumo for his unwavering support, invaluable scientific and professional guidance and cooperation throughout the study. Thanks Paul, I can now face the world. I gratefully acknowledge the high level of cooperation received from farmers in Chikwaka, Chinyika and Zimuto smallholder areas, and officers from the Department of Research and Extension (AREX) of the Ministry of Agriculture, Zimbabwe, who were key facilitators in the communal study sites and provided technical services at Domboshawa and Makoholi Research Stations. Many thanks to Dr Bernard Vanlauwe of TSBF-CIAT, who was instrumental in the design of the on-station experiment and for keeping me focussed throughout the study. To Dr Alain Albrecht, thank you for the push. I am grateful to the World Agroforestry Centre (ICRAF) for allowing us to prune Calliandra from their site and to TSBF-CIAT for the lignin and polyphenol analyses. I also gratefully acknowledge financial support from the W.K. Kellogg Foundation under the WKKF Dissertation Awards Program and for identifying the potential of my study in contributing to the Foundation s mission in support of the development of healthy and sustainable rural communities in Southern Africa. A very special thank you to Academy for Educational Development (AED) and African Intellectual Resources (AIR) for intelligent ideas on how to write a winning thesis. Finally, I would want to thank Joyce Ushe, Timothy Mapfumo and Eliah Mbizah for their technical assistance with the thousands of samples destined for laboratory analysis, and my fellow student on the NUESOM Project, Josphat Chisora, for assistance with the socio-economic surveys and data handling.

6 iv TABLE OF CONTENTS ABSTRACT... I ACKNOWLEDGEMENTS... III TABLE OF CONTENTS... IV LIST OF TABLES... XII LIST OF FIGURES... XV LIST OF TEXT BOXES... XXII LIST OF APPENDICES.XXI LIST OF ACRONYMS AND ABBREVIATIONS... XXIIII CHAPTER INTRODUCTION AND PROBLEM DEFINITION Background Variability and soil fertility gradients on smallholder farms Study rationale Hypotheses Objectives of the study Thesis structure... 9 CHAPTER LITERATURE REVIEW The soil fertility management paradigm and soil organic matter Quantification of SOM Functional pools of SOM... 14

7 v Coarse light fraction Microbial biomass fraction Heavy fraction Causes of SOM decline Tillage Erosion Building SOM? SOM and Nutrient management strategies by smallholder farmers Livestock manure Green manures Intercrops and rotations Crop residues Woodland litter Household waste and compost Termitarium soil Mineral fertilizers Ash CHAPTER STUDY SITES AND RESEARCH METHODOLOGY Introduction On-station experimental sites Domboshawa Makoholi On-farm experimental sites Chikwaka... 29

8 vi Chinyika Zimuto Overview of the farming systems Overview of the methodological approach used CHAPTER ORGANIC MATTER MANAGEMENT AS AN UNDERLYING CAUSE FOR SOIL FERTILITY GRADIENTS ON SMALLHOLDER FARMS Abstract Introduction Materials and methods Selection of field sites and soil sampling Biomass quantification and analyses Carbon and nitrogen mineralization of field surface organic biomass Data analyses Results Characteristics of rich and poor fields A farmer criteria Zimuto In situ biomass available for incorporation Early dry season period Late dry season period Potential C and N contributions from in situ biomass C and N release patterns from in situ biomass Discussion Major determinants for productive and non-productive fields... 60

9 vii Quantities of in situ biomass available for incorporation Carbon contributions and nutrient release from in situ biomass Conclusions CHAPTER COMPARATIVE SHORT-TERM EFFECTS OF DIFFERENT QUALITY ORGANIC RESOURCES ON MAIZE PRODUCTIVITY UNDER TWO DIFFERENT ENVIRONMENTS Abstract Introduction Materials and methods Organic resource selection and characterization Generation of organic resources Field layout and experimental treatments Mineral N dynamics Data analysis Results Influence of organic resource quality and quantity on maize productivity Relative contributions of different nutrient sources on grain yield Nitrogen uptake patterns Discussion Conclusions CHAPTER

10 viii DIFFERENTIAL EFFECTS OF ORGANIC RESOURCE QUALITY ON SOIL PROFILE N DYNAMICS AND MAIZE YIELDS ON SANDY SOILS IN ZIMBABWE Abstract Introduction Materials and Methods Experimental treatments and management on-station On-farm experimental treatments and management Sampling for mineral N dynamics Ammonium-N and Nitrate-N analyses Data analyses Results Influence of organic quality and C application rate on soil NH + 4 -N Influence of organic quality and C application rate on soil NO - 3 -N Maize productivity in response to organic resource application onstation (Makoholi) Soil N changes and maize productivity under smallholder farmer management Discussion Conclusions CHAPTER ORGANIC MATTER QUALITY AND MANAGEMENT EFFECTS ON ENRICHMENT OF SOIL ORGANIC MATTER FRACTIONS ON CONTRASTING SOILS IN ZIMBABWE Abstract

11 ix 7.2 Introduction Materials and Methods Study sites Soil sampling and fractionation Mineral N analysis Quantifying the N mineralization potential and C contributions in fractions Data analyses Results Effect of organic resource quality on the size of POM fractions POM size fractions on sandy soils under smallholder farmer management Distribution of POM down contrasting soil profiles Potential mineral N contributions from different POM fractions Relationships between POM fraction size and maize productivity Discussion Build-up of POM fractions in soil Effect of organic resource quality on POM enrichment Effect of soil texture on POM enrichment Conclusions CHAPTER PARTICULATE AND LABILE C FRACTIONS AS INFLUENCED BY ORGANIC MATTER MANAGEMENT PRACTICES ON SMALLHOLDER FARMS Abstract Introduction

12 x 8.3 Materials and Methods Selection and monitoring of farm and field sites Soil sampling and fractionation Measurement of labile C fractions Data analyses Results C and N in inputs allocated to different field types Impact of short-term organic matter management on POM size fractions Effect of organic matter management history on POM enrichment in farmers fields Soil fertility management strategies by smallholder farmers: The Zimuto case study C lability and maize productivity Discussion Implications of organic matter management on fertility gradients on smallholder farms Enrichment of POM fractions in farmers fields Significance of annual organic inputs on labile C fractions Quality of applied organic resource and C lability Conclusions CHAPTER OVERALL DISCUSSION, CONCLUSIONS AND RECOMMENDATIONS Introduction

13 xi 9.2 Matching farmers perception of soil productivity with conventional science to enhance sustainability Resource endowment as an organic matter management factor Fate of different quality organic resources in cropping systems Optimizing organic nutrient sources for improved maize productivity Options for improving soil productivity for resource-poor farmers Areas of further research REFERENCES APPENDICES

14 xii LIST OF TABLES Table 3.1 Major characteristics of farming systems prevalent in the different agroecological regions of Zimbabwe Table 3.2 Descriptive criteria for classification of farmers in Chikwaka, Chinyika and Zimuto smallholder farming areas Table 4.1 Smallholder farmer indicators for highly productive (rich) and poorly productive (poor) fields or field sections in Zimbabwe (ranked in order of importance) Table 4.2 Soil characteristics of smallholder farmers rich and poor fields in three agroecological regions of Zimbabwe Table 4.3 Potential C and N contributions from maize- and non-stover biomass at different periods of incorporation under smallholder farmer management in high (Chikwaka) and medium (Chinyika) rainfall areas Table 4.4 Potential C and N contributions from maize- and non-stover biomass at different periods of incorporation under smallholder farmer management under semi-arid conditions in Zimuto ( mm year -1 ) Table 4.5.Quality parameters of in situ biomass* on rich and poor fields of smallholder farms in three agroecological regions of Zimbabwe Table 5.1 Quality of organic resources at time of field incorporation at Domboshawa and Makoholi experimental sites Table 5.2 Maize grain yield and harvest index as influenced by organic resource quality and application rate under contrasting environments Table 5.3 Relative contribution of mineral fertilizer and organic x mineral fertilizer interaction effects to maize grain yield as influenced by organic resource quality under different environments... 82

15 xiii Table 5.4 Statistical significance of organic and mineral nutrient sources on maize and stover N quality at Domboshawa Table 5.5 The effect of organic resource quality and quantity of application (carbon basis) on maize grain and stover N concentration at Domboshawa in Zimbabwe Table 6.1 Organic and mineral nutrient sources used as soil amendments by farmers in Chikwaka, Chinyika and Zimuto smallholder farming areas Table 6.2 Effect of organic resources quality on maize productivity for different application rates at Makoholi Experimental Station during cropping season Table 6.3 Maize biomass production and grain yields from different quality nutrient sources used in experiments designed and managed by farmers in three smallholder areas of Zimbabwe during the season Table 7.1 Quality of organic resources used under two contrasting soil types at Domboshawa and Makoholi field experiments Table 7.2 Organic and mineral nutrient sources used by smallholder farmers in Chikwaka and Zimuto communal areas Table 7.3 R 2 values of relationship between maize yields and total C, POM- and organo-mineral- size fractions (0-30 cm depth) under different organic matter management at four sites in Zimbabwe Table 7.4 R 2 values and level of significance for relationships between maize yields and particulate organic matter size fractions at different depths from two on-farm sites (Chikwaka and Zimuto) and two on-station sites (Domboshawa and Makoholi)

16 xiv Table 8.1 Mean quantities (ranges in parentheses) of organic and mineral nutrient sources used by smallholder farmers on rich and poor fields during the 2002/03 and 2003/04 seasons in Chikwaka, Chinyika and Zimuto Table 8.2 Quantity and quality of different organic and mineral nutrient sources used in farmer-managed field experiments in Chikwaka, Chinyika and Zimuto Table 8.3 Soil properties and total C applied on the most productive (rich) and least productive (poor) fields on selected farms in Zimuto Communal Area Table 8.4 Relationships between maize grain yield and different soil C and N fractions under different organic and nutrient resource management in subhumid Chikwaka and semi-arid Zimuto

17 xv LIST OF FIGURES Figure 3.1 Schematic diagram of the methodological approach adopted for the study. Solid arrows indicated direction of flow of events while dotted arrows represent key outputs necessary for each entry point Figure 4.1 Soil organic C content of rich and poor fields belonging to Resourceendowed, Intermediate and Resource-constrained farmers in Chikwaka, Chinyika and Zimuto. Bars represent SEDs Figure 4.2 In situ biomass in rich and poor fields of three farmer categories from Chikwaka (a), Chinyika (b) and Zimuto (c). Early denotes early dry season biomass and Late is late dry season biomass Figure 4.3 CO 2 -C release by different organic resources found on farmers fields following 150 days of incubation with soil. Bars indicate least significant differences at p < Figure 4.4 Total mineralizable N (NH + 4 -N + NO - 3 -N) from different quality organic resources found on farmers fields following 150 days of incubation with soil. Ratio of non-maize stover: maize stover biomass was ~2: Figure 5.1 Relationship between soil mineral N availability (before mineral N fertilizer application) and a 2 week-old maize crop biomass at Makoholi (a) and Domboshawa (b) under different quantities and quality organic resources Figure 5.2 Relationship between maize productivity at two weeks after emergence and final grain yield under low rainfall at Makoholi (a) with no mineral fertilizer N addition and (b) plus 120 kg N ha Figure 5.3 Relationship between maize total N uptake and grain yield under high rainfall conditions at Domboshawa. (Larger symbols of the same shape

18 xvi denote high biomass application rates of 7.5 t C ha -1 (versus 2.5 t C ha -1 ) for the same organic resource. Solid symbols denote mineral N fertilized treatments) Figure 6.1 Rainfall distribution during the season at Makoholi (total = 647 mm) and Zimuto (total = 659 mm). (Major events during the season are indicated by arrows) Figure 6.2 Soil NH + 4 -N dynamics under different quality organic resources applied at 1.2 t C ha -1 at Makoholi. T1 to T7 were independent sampling times following a rainfall event between 28 November, 2003 and 21 April, Figure 6.3 Soil NH + 4 -N dynamics under five different quality organic resources applied at 4.0 t C ha -1 at Makoholi. T1 to T7 were independent sampling times following a rainfall event between 28 November, 2003 and 21 April, Figure 6.4. Soil NO - 3 -N dynamics under different quality organic resources applied at 1.2 t C ha -1 at Makoholi. T1 to T7 were independent sampling times following a rainfall event between 28 November, 2003 and 21 April, Figure 6.5 Soil NO - 3 -N dynamics under five different quality organic resources applied at 4.0 t C ha -1 at Makoholi. T1 to T7 were independent sampling times following a rainfall event between 28 November, 2003 and 21 April, Figure 6.6 Relationship between maize grain yields and mid-season (Feb.) soil N availability in the top 30 cm of the profile following incorporation of different organic nutrient sources at two carbon rates on a sandy soil at Makoholi 114

19 xvii Figure 6.7 Soil available mineral N during mid (February) and end (April) of the season (2003-4) following incorporation of different nutrient sources in a sandy soil by smallholder farmers in Zimuto Figure 6.8 Relationship between total amount of N supplied in different nutrient sources and maize grain yield under smallholder farmer management in Chikwaka, Chinyika and Zimuto Figure 7.1 Schematic diagram showing procedure used to separate particulate organic matter and organo-mineral fractions in soil Figure 7.2 Relative C distribution in separated POM- and organo-mineral fractions following two seasons application of 4 t C ha -1 of different quality organic resources on (i) a sandy clay loam at Domboshawa and (ii) a coarse sand at Makoholi Figure 7.3 Relative C distribution in the different POM- and organo-mineral fraction following application of different quality organic resources on a coarse sands under (i) high rainfall area at Chikwaka and (ii) semi-arid conditions at Zimuto during the season Figure 7.4 Size and distribution of two POM fractions and an organo-mineral fraction following incorporation of different quality organic resources at 4 t C ha -1 on a sandy clay loam soil under high rainfall conditions at Domboshawa, and coarse sands under semi-arid conditions at Makoholi Figure 7.5 Potential mineralizable N from the macro-, meso-pom and organomineral fractions following incorporation of 4 t C ha -1 of different quality organic resources on (i) a sandy clay loam soil at Domboshawa and (ii) coarse sand at Makoholi

20 xviii Figure 7.6 Relationship between maize yield and potential mineralizable N from the macro-pom fraction in the top 30 cm of a sandy clay loam soil at Domboshawa Figure 7.7 Relationship between maize yield and potential mineralizable N from the organo-mineral fraction in the top 30 cm of a coarse sandy soil at Makoholi Figure 7.8 Relationship between maize yield and the sum of potential mineralizable N from the macro- meso-pom and organo-mineral fractions in the top 60 cm of a coarse sandy soil at Zimuto Figure 8.1 C and N inputs from different quality nutrient sources applied to most productive (rich) and least productive (poor) field types under different rainfall regimes of Chikwaka, Chinyika and Zimuto smallholder farming areas (n = 20) Figure 8.2 Enrichment of different POM-size fractions following field application of different quality nutrient sources in three smallholder farming areas of Zimbabwe Figure 8.3 Topsoil (0-20 cm) enrichment of different POM-size fractions for the most productive (rich) and least productive (poor) fields under smallholder management in semi-arid Zimuto Communal Area (n = 20) Figure 8.4 Mid-season (February) cumulative labile C fractions from the 0-20 cm and 0-60 cm soil depths following deliberate application of known quantities of different quality nutrient sources in Chikwaka (a) and Zimuto (b) Communal Areas Figure 8.5 Relative distribution of three different POM fractions under smallholder management on selected farms in semi-arid Zimuto

21 xix Figure 8.6 Relationship between maize grain yield, mineralizable N and readily available C in the top 20 cm of most productive (rich) and least productive (poor) fields under smallholder farmer management in Zimuto Figure 9.1 Possible enrichment of measurable organic matter fractions in fields differing in their productivity potential. Arrow size shows the magnitude of either C entering the pool (block arrows) or the amount of potential mineralizable N released from the fraction (simple solid arrows)

22 xx LIST OF TEXT BOXES Box 8.1 Soil fertility management strategies at Mr Mazarire s farm using cattle manure 170 Box 8.2 Soil fertility management strategies at Mrs Mbokochena farm using woodland litter..171 Box 8.3 Soil fertility management strategies at Mrs Chirakata s farm.171

23 xxi LIST OF APPENDICES Appendix 1. Monthly rainfall during 2002/03 and 2003/04 seasons at Makoholi and Domboshawa Experimental Stations Appendix 2. Rainfall distribution during the 2003/04 season in Chikwaka (total = 765 mm), Chinyika (total = 631 mm) and Zimuto (total = 659 mm) Appendix 3. Publications from this thesis

24 xxii LIST OF ACRONYMS AND ABBREVIATIONS AREX C CEC FPRA GHI GIS M masl N NH + 4 -N NIRS NO - 3 -N NR POM SOC SOM WAE UV Agricultural Research and Extension Carbon Cation exchange capacity Farmer participatory research approach Grain harvest index Geographical Information System Molarity Metres above sea level Nitrogen Ammonium nitrogen Near Infra-red reflectance spectroscopy Nitrate nitrogen Natural Region Particulate organic matter Soil organic carbon Soil organic matter Weeks after crop emergence Ultra-violet

25 1 CHAPTER 1 Introduction and Problem Definition 1.1 Background Increasing smallholder agricultural productivity in sub-saharan Africa has been identified in the UN Millennium Development Goals (MDG) as key to reducing extreme poverty and hunger (United Nations, 2000). Agricultural output has been declining in most parts of Africa not only threatening achievement of MDG1 (extreme poverty and hunger eradication), but also compromising environmental sustainability as farmers often move into marginal areas. Soil fertility degradation still remains the single most important constraint to food production in sub- Saharan Africa including Zimbabwe (Sanchez et al., 1997; Mapfumo and Giller, 2001), and it has become vital to adopt a holistic approach in the promotion of improved soil productivity, particularly in the smallholder sector. In Zimbabwe alone, failure of the 2003/04 and 2004/05 seasons due to persistent droughts and government land reform programmes has led to an officially acknowledged maize (Zea mays L.) deficit of 1.2 million metric tonnes, requiring over US$200 million for grain importation alone (United Nations, 2005). This emphasizes the importance of understanding the processes underpinning soil productivity and how these could be manipulated to enhance agricultural productivity. At national level, one of the many ways in tackling food security demands includes formulation of strategies that help bring back depleted soils to their original agricultural production potential. Maintaining productivity of those soils that are currently productive without encroaching into marginal areas remains a major

26 2 challenge to agricultural productivity. This may require that the soil resource base is able to adequately provide the nutrients required to sustain the increased crop yields. Continued decline in soil productivity has necessitated the formulation of improved management strategies that maintain and protect the soil resource base. Traditional methods for sustaining soil productivity have been outpaced by a growing population, a diminishing natural resource base, and a downward spiral of many national economies. Moreover, insufficient nutrient inputs in the form of organic and mineral fertilizers to replace harvested or exported nutrients typify the majority of such cropping systems (Smaling et al., 1997). In most instances, maintenance of soil fertility on smallholder farms in sub-saharan Africa is almost entirely dependent on locally available organic resources, which are often in insufficient quantities to make the desired impact (Mapfumo and Giller, 2001). Use of mineral fertilizers, despite their acknowledged benefits by smallholder farmers (Piha, 1994), have remained prohibitively expensive. For instance, the retail price of about US$30 per 50 kg bag of nitrogen (N) fertilizer, (retail price of 2005) is far beyond the reach of most smallholder farmers, who survive on <US$1 a day. About 70% of Zimbabwe is covered by inherently poor coarse sandy soils derived from granite (Thompson and Purves, 1981). However, the predominantly resource-constrained farmers in the smallholder sector still rely heavily on these soils for dry-land farming with very little or no external nutrient additions. Soil organic matter (SOM) has been identified as the single major source of nutrients sustaining crop productivity in such low-input systems (Woomer et al., 1994; Hassink, 1997). Sandy soils characterizing many Zimbabwean smallholder farms invariably contain small amounts of SOM because of their lack of capacity to

27 3 protect organic matter from microbial degradation (Giller et al., 1997). How smallholder farmers continue to maintain the productivity of their arable fields therefore remains a puzzle and requires further research on crop-soil management interactions. The importance of SOM in nutrient cycling has long been recognized although a mechanistic understanding of the relationship between SOM and nutrient availability has only begun to emerge in recent years (Vanlauwe et al., 2002a; Mtambanengwe and Mapfumo, 2005). Nutrient release from SOM is dependent upon mineralization of biologically active fractions, which may vary qualitatively and quantitatively in relation to the quality and quantity of organic inputs (Vanlauwe et al., 1994; Barrios et al., 1996). The fractions may or may not be homogeneously distributed in space and time. However, information on the actual fate of the applied organic resources to soil is still scanty (Palm et al., 2001a). Significant advances have been made in understanding the influence of resource quality on plant nutrient availability (particularly N and P), but to date the effect of resource quality and management factors on SOM dynamics over different time frames have not been clearly understood (Mapfumo et al., 2001a). The major challenge on arable lands is to arrest SOM decline, and wherever possible, promote its build-up through appropriate management of organic resources available to farmers. Farmers often face complex management decisions involving resource allocation to different field typologies, as well as labour constraints (Tittonell et al., 2005a). 1.2 Variability and soil fertility gradients on smallholder farms Physical, chemical and biological soil properties may vary over short distances resulting in uneven crop stands. While much of the variation in soil productivity

28 4 observed across faming landscapes has often been attributed to inherent differences in soil forming factors such as climate, parent material (Foth, 1984) and catenary positioning (Tittonell et al., 2005b), soil processes leading to the manifestation of within-field and within-farm variation are still not well understood. For instance, differences in productivity between two sections of the same field, or between fields sharing the same soil parent material and textural properties are often evident within and across fields and farms (Mapfumo et al., 2001a). While farmers generally recognize the existence of such spatial soil variation within their fields and farms (Scoones et al., 1996; Chikuvire, 1998), the nature and causes of these high and low zones of fertility, or soil fertility gradients, are largely unknown. The little explained variation has been attributed to the physically well-defined field environments such as termite mounds, homestead surroundings and areas under tree canopies. Evidence exists that farmers deliberately exploit these islands of fertility in order to maximize use of available nutrients in these niches (Carter and Murwira, 1995; Chikuvire, 2000). Variation in crop yield largely occurs as a result of either environmental limitations or differences in management by farmers within specific cultural and socioeconomic contexts (Tittonell et al., 2005a). Such gradients are more pronounced under unfavourable crop growth conditions, such as low or poor rainfall distribution or low nutrient application. Resource allocation to various fields/ field sections belonging to the same farmer may vary substantially creating zones of nutrient accumulation and depletion (Vanlauwe et al., 2001; Smaling et al., 2002). The practice of preferential distribution of resources within and between farms is common under most smallholder farms in sub-saharan Africa, and the challenge is to come up with tools that could help manage these differences rather than

29 5 concentrating on bringing areas of low fertility in line with the rest of the fields. Such localized nutrient concentrations are likely to have a differential impact on the SOM status of the different fields. Whether soil fertility gradients evolving from farmer management are more important in determining overall farm productivity compared to those from inherent soil properties still needs verification and more empirical data is required. 1.3 Study rationale Use of organic nutrient sources by the majority of smallholder farmers is often seen as an alternative to expensive mineral fertilizers. However, organic resources are rarely available in sufficient quantities to cover land area required for optimal crop production, particularly the maize staple food. Although information on the amount of nutrients potentially released by different quality organic materials is available (Palm et al., 2001a; Chikowo, 2005), the net flow of resources at field scale is only beginning to emerge. Little is known about the behaviour of the applied organic resources under different land management systems or how they affect soil-nutrient-crop interactions spatially and temporally. Several studies have demonstrated additive effects between organic and mineral fertilizers combinations (Palm et al., 1997; Giller 2001). With the exception of cattle manure, information on which of the readily available organic resources on smallholder farms can be applied together with mineral fertilizers to maximize crop yields is still scanty. More work on nutrient combinations under smallholder management is necessary to be able to come up with a step-by step decision guide enumerating the exact quantities for either of the nutrient source required. It remains a fact that there is no achievable yield without mineral fertilizer application for most cultivated

30 soils in Zimbabwe (Grant, 1967; Mapfumo et al., 2001b), and it is therefore imperative that farmers increase the efficiency of mineral fertilizer use. 6 Most of the studies on organic matter decomposition and nutrient release have been mainly concentrated on homogenous materials such specific leguminous species and crop residues (Cadisch and Giller, 1997). This poses a challenge for a predictive understanding of the behaviour of SOM on real farm situations since organic resources accessible to most smallholder farmers are highly heterogeneous in quality and vary in quantity. Apart from the knowledge that high quality organic inputs release nutrients in short-term through their interaction with the active SOM fraction (Drinkwater et al., 1996; Palm et al., 2001), the pathways of SOM formation from different quality organic residues are not clearly understood. There is critical need to improve our understanding of resource quality and SOM management interactions in order to translate the available knowledge on soil biological processes into practical management solutions that are adaptable on-farm (Mapfumo et al., 2001a). The quality of resources available for soil amelioration on smallholder farms still needs characterization using set parameters of the decision tree for organic matter management (Giller, 2000; Palm et al., 1997, 2001). It is only after quality assessments that the impact of such resources on SOM build-up across different agroecological zones can be predicted. Studies by Bonde et al. (1992) suggest that annual inputs to soils contribute to a C build-up in the clay fraction. Given that soils on many smallholder farms of Zimbabwe are sandy and inherently low in clay content, chances of building SOM in such soils are slim (Giller et al., 1997; Mapfumo and Giller, 2001), and yet some farmers still achieve high crop yields.

31 7 There is need to understand and document possible SOM pathways and shortterm N availability driving crop productivity in these coarse textured soils following use of different quality/quantity organic resources. Of critical importance is how some of these coarse-textured soils continue to maintain reasonable productivity over time. In some instances, the observed yield response patterns and nature of interactions have largely been difficult to explain at field level. While there is considerable development in our understanding of the role of SOM in nutrient cycling, indices quantitatively defining possible linkages between farmer management practices and soil biological processes need to be developed. Thresholds for defining optimum crop productivity need to be identified in order to come up with management tools similar to those developed for mineral fertilizers (Piha et al., 1998). This study focused on mechanisms of SOM formation and N availability under management systems involving C substrates of different quality. The main objective of the study was based on the understanding that SOM is the driving force behind sustainable crop productivity on depleted sandy soils characterizing the majority of smallholder farms in Zimbabwe. Emphasis was put on establishment of relationships between SOM fractions, N release, fertilizer use efficiency and maize yields, and their links with organic matter management practices by farmers belonging to different social status (Mabeza-Cimedza, 2000; Ramisch, 2004). This was then used to account for the observed fertility gradients within and across farms, and the implications of farmers medium- and long-term organic management practices.

32 8 1.4 Hypotheses With this background, the following hypotheses were formulated: 1. Soil fertility gradients are a result of systematic organic matter management by different farmer resource groups. 2. Repeated application of low quality organic matter (high lignin, low N) results in significant build-up of SOM and increased fertilizer use efficiency. 3. The quantity, quality and management of organic nutrient sources applied to soil by smallholder farmers are mainly dependant on the wealth status of individual farmers. 4. Systematic application of organic resources to soil enriches functional SOM fractions resulting in an enhanced supply of nutrients, particularly N, to growing crops. 5. Crop yield responses observed on selected smallholder farms are a consequence of systematic management of organic matter that enriches the size and quality of functional SOM pools and ensures a steady supply of nutrients to crops over time. 1.5 Objectives of the study The overall objective of the study was to determine the quality and quantity of organic materials applied to soil under different management systems in Zimbabwe by smallholder farmers belonging to different social categories, and how these resources influence SOM formation, soil nutrient supply patterns and efficient use of added mineral fertilizers. The specific objectives of the study were to:

33 9 1. Identify management factors influencing the formation of within-field/ farm soil fertility gradients paying particular attention to the organic carbon (C) and nitrogen (N) inputs by farmers across different social gradients. 2. Evaluate the effects of organic resource quality and quantity on maize productivity and determine fertilizer use efficiency of different organic C sources. 3. Characterize the different organic nutrient resources under smallholder farming systems and determine their N supply characteristics in relation to soil profile N changes and maize productivity on sandy soils. 4. Quantify the interactive effects of organic resource quality and quantity on SOM functional pools essential for maintenance of maize productivity under different management systems and soil types 5. Establish the relative influence of annual organic inputs by different farmer resource groups on the size of soil available C pools and how this C accounts for observed maize yield. 1.6 Thesis structure Chapter 1 gives the problem definition and justification while an overview of relevant literature relating soil organic matter to soil fertility is reported in Chapter 2. In Chapter 3, a detailed description of the study sites where most of the experimental work was carried out is outlined. The selection process of host farmers for on-farm study sites is also described in Chapter 3. Chapter 4 deals with identification of management factors influencing the formation of withinfield/farm soil fertility gradients. This was explored through quantification of in situ field biomass in fields differing in productivity. Farmer indices of productivity were

34 10 also enumerated and compared with laboratory indices. Chapter 5 compares the short-term effects of organic resource quality on maize productivity under different environments. The benefits of combining organic with mineral nutrient resources were also quantified. The N-supply capacity of organic resources varying in quality and quantity to a growing maize crop and the fate of NO - 3 -N and NH + 4 -N released was explored under sandy soil profiles both on-station and on farmers fields (Chapter 6). The relative contribution of different quality organic materials to POM fraction of SOM and subsequent nutrient release was quantified on soils differing in texture (Chapter 7). Chapter 8 investigates possible enrichment of the biologically active labile C fractions under smallholder farmer management in different agro-ecosystems. The impact of differential farmer management practices on manifestation of soil fertility gradients was also explored using Zimuto Communal area as a case study. In Chapter 9, findings of the whole study are distilled and the impact of differential organic matter management to fields differing in productivity conceptualized. The study s overall conclusions and recommendations are also made.

35 11 CHAPTER 2 Literature Review 2.1 The soil fertility management paradigm and soil organic matter Over the last two decades, research has focused on understanding the potential role of SOM as a source of plant nutrients in tropical ecosystems (Swift, 1985; Duxbury et al., 1989; Seward and Woomer, 1993; Barrios et al., 1997; Bergström and Kirchmann, 1998). Some of this research has paid particular attention to factors governing SOM decay and build-up as well as partitioning it into fractions under natural and derived agro-ecosystems in Zimbabwe (King and Campbell, 1994; Mtambanengwe, 2000; Chivenge, 2003). There however, has been limited information on possible avenues to fully exploit SOM for integrated soil fertility management in tropical cropping systems. Studies in temperate environments have shown that the functions of SOM include nutrient supply, water retention, buffering and CEC (Oades et al., 1989; Feller, 1993). However, given the inherent differences in climate, vegetation, soils, topography and land management, chances are that the critical SOM values needed to achieve these services are different under tropical conditions might be different. Observed trends in nutrient depletion on smallholder farms in the tropics have been largely linked to the continued decline in SOM (Sanchez et al., 1997). While SOM itself is not a direct requirement for plant growth, it acts as a store for nutrients, particularly N, P and S, which become available for plant uptake as the SOM is mineralized (Wander et al., 1994; Woomer et al., 1994). Of great importance in SOM studies is, perhaps, the relationship between organic inputs

36 12 and their effect on SOM build-up in the different fractions in relation to plant productivity. The quality of organic inputs, soil textural composition and land-use type may affect the composition and stability of SOM. The substrate quality and its rate of decomposition largely regulate the time over which mineral nutrients are released from an organic resource for plant uptake. The C sources in the organic substrates range from simple sugars to complex organic compounds including lignin, cellulose and polyphenols. High concentrations of some of these secondary compounds in organic inputs have been correlated to SOM stabilization as defined by their mean turnover times (Parton et al., 1987; Oades, 1988). Research in soil fertility and productivity has been concerned with attempts to fractionate SOM into components and to try to define the role of each component (Elliot and Cambardella, 1991; Swift et al., 1994). According to Feller et al. (1983), SOM can be separated into functional pools each of which is believed to play a particular role in nutrient release, cation exchange, water holding capacity and soil aggregation. Three basic fractions have commonly been associated with SOM and these include the light (active) fraction including the particulate organic matter (POM) and microbial biomass pool, the slow fraction and the humic (passive) fraction (Parton et al., 1988; Duxbury et al., 1989). The different functional pools, based on their decomposition rates and mean residence time in soils, may be important in providing insights on the possible link between SOM dynamics and nutrient availability (Swift and Woomer, 1993). 2.2 Quantification of SOM While there is no general consensus as to the actual definition of SOM, it usually refers the organic fraction of the soil, which includes plant and animal residues at

37 13 various stages of decomposition, cellular fractions and tissues of microbes and substances synthesized by the soil population (Campbell, 1989). Dead organic matter (fine litter and SOM) constitute ~50% C in tropical soils, 60-70% in savanna and about 95% in tropical grasslands (Theng et al., 1989). The humus fraction which is basically associated with clay minerals may constitute up to 80-90% of C in soil (Duxbury et al., 1989). In areas where the soils have a significant clay content, SOM levels are much higher (2% versus 0.5% for most sandy soils) even under similar climates and management practices. Measurements of the biological active pools of SOM (Motavalli et al., 1994; Blair et al., 1997) may help provide insights on the build up of SOM under organic residue management applied to soils of varying textural properties. Over the past two decades, research has been focused on the fractionation of SOM under natural and agricultural ecosystems through both physical and chemical methods (Stevenson and Elliott, 1989; Chotte et al., 1993; Barrios et al., 1997; Blair et al., 1995, 1997; Chivenge et al., 2000). Physical fractionation involves the disruption of the soil structure by shaking, floatation, and separation of organic fractions according to density, wet sieving and sedimentation. Chemical procedures separate humic and non-humic substances in acid or alkali. Much of the soil humus consists of humin, humic acid and fulvic acids, all of which are collectively referred to as humic substances, but these have not been found to be closely related to SOM functions (Stevenson and Elliott, 1989). It is the non-humic substances including various classes of biochemical compounds such as carbohydrates, proteins and lipids that may be responsible for long term nutrient release. However, no ideal method has been identified to separate most of these compounds from soil due the complex nature of SOM. Both physical and chemical

38 fractionation methods seem to have had success in SOM studies in approximating SOM pool sizes (Feigl et al., 1995; Magid et al., 1996) Functional pools of SOM Coarse light fraction The coarse light fraction is also referred to as the labile or POM fraction. It largely consists of a range of different products ranging from unprotected rapidly mineralizable components of plant debris and soil fauna to the more recalcitrant compounds such as lignin and polyphenols. By definition, it is assumed to be that organic fraction lying between µm with a wide C:N ratio of between and constitutes 45-65% of total SOM (Sollins et al., 1984; Anderson and Ingram, 1993; Okalebo et al., 1993). Although it is regarded as highly labile, it does not constitute the majority of the active SOM pool and has been known to vary within and between seasons (Boone, 1994; Woomer et al., 1994). Residue inputs and climate are the main factors controlling the POM pool. The greater part of this fraction has a short turnover period ranging from a few days to a few years. The light fraction of SOM plays an intermediary role between plants and humus. It has been reported to be a major source of N and other readily decomposable plant compounds. Changes in the POM fraction often reflect changes in organic inputs Microbial biomass fraction The microbial biomass pool (the active fraction) is highly labile and is the SOM fraction with the most rapid turnover rate (Paul and Clark, 1989). This pool is unprotected and constitutes a transformation matrix for organic matter in soil and acts as a reservoir for plant labile nutrients. Because it is living, this pool responds quickly to stresses in the environment or changes in organic matter inputs than

39 15 does SOM as a whole (Theng et al., 1989; Woomer et al., 1994). Measurable changes in microbial biomass may reflect changes in land management long before such changes are reflected in total SOM. It constitutes between 1 to 5% of total SOM (Henis, 1986) although some studies in natural tropical woodlands has shown higher concentrations (Anderson and Domsch, 1989; Srivastava and Singh, 1991; Kirchmann and Eklund, 1994) Heavy fraction This fraction is humified soil comprising physically protected and/ or chemical forms of organic matter which are resistant to decomposition. The fraction s turnover time ranges between 20 to 40 years for slow soil and up to 200 to 1000 years for passive soil depending on degree of physical disturbance (Anderson and Ingram, 1989). The heavy fraction (>1.6 g cm -3 ) contributes 30-50% of total SOM and may contain materials with a narrow C:N (Meijboom et al., 1995). Tillage, aggregate disruption and soil particle-size distribution control the pool size. It is a biologically passive pool, and is sometimes loosely referred to as the humus representing organic matter adsorbed on mineral surfaces or contained in microaggregates. Organic matter in this fraction is found in close association with clay and silt and hence is physically protected from microbial attack. High clay content in soil is considered a factor that promotes C stabilization through bonding of organic colloids with mineral surfaces (Tiessen and Stewart, 1983; Motavalli et al., 1994). Although humus decomposition is slow, there is a low but continual release of nutrients as the components of this fraction decompose. This fraction releases more mineral N than other SOM fractions in the long term and contains the highest population of soil microorganisms (Jenkinson and

40 16 Rayner, 1977). The passive pool has a very high CEC ( cmol (c) kg -1 ), and therefore contributes significantly to the CEC of low-clay or highly weathered soils. Organic matter in this fraction has been reported to undergo slow changes during cultivation, thus is likely to contribute little to the short- or medium-term fertility of soils (Meijboom et al., 1995). 2.4 Causes of SOM decline Tillage Different SOM fractions mineralize nutrients at different rates under different management practices. It is not the loss of soil C that poses a threat to smallholder farmers, but rather the decline in crop yields resulting from SOM-associated properties. The efficiency with which nutrients are recycled within existing cropping systems are dependant on SOM (Swift and Woomer, 1994). The quality and quantity of SOM can vary monthly, depending on site conditions. In addition to land degradation and erosion processes, continuous cropping can negatively affect SOM levels of most agricultural soils. Upon cultivation, organic material in soil disintegrates rapidly to enter finer, mineral-associated organic pools which during their subsequent mineralization, contributing significantly to the soils available nutrient pool. Generally, tillage results in the disruption of soil aggregates (Six et al., 2002) and improved aeration. This increases microbial activity, and hence the rate of SOM decomposition, as microorganisms gain access to intraaggregate organic matter (Tiessen and Stewart, 1983). Tillage alters lateral distribution of organic matter by physically importing topsoil into lower depths. The decline in SOM is also accelerated when the rate at which C is added to the soil system is exceeded by C losses due to decomposition under different land

41 17 management such as tillage. Under mulching or minimum tillage, SOM accumulates but is restricted to the surface while conventional tillage that incorporates crop residues may affect SOM contents at lower depths (Elwell and Norton, 1988; Vogel, 1994; Grant, 1995). Known consequences of SOM loss include the reduction in soil nutrient supply and storage capacity, reduced soil aggregate stability, reduction in soil biological activity and increased susceptibility to erosion (Srivastava and Singh, 1989) Erosion Both wind and rain play a predominant role in distribution of organic matter in natural and arable systems through their erosive processes. Erosion not only affects the direct distribution of organic matter in productive environments, but may have long term consequences on plant productivity through depletion of labile SOM pools (Swift and Woomer, 1994). Immediate effects of soil erosion are not only the declines in soil fertility (Elwell and Stocking, 1988), but also the potential increase in floods and salinization of surface water (Murphy, 2002), absolute decline of arable and grazing land (Janzen et al., 2002) leading to a reduction in agricultural and livestock outputs. Organic matter decline in agricultural systems is exacerbated by overexploitation of arable land by man (Bunders, 1990). Janzen et al., (2002) identified three ways in which erosion can affect organic matter. These include either physical removal of organic matter from the site, mixing of subsoil into the surface layer by stripping the surface away or deposition of soil eroded from elsewhere in the landscape. The effects of erosion vary from place to place across the landscape.

42 Building SOM? Use of organic matter inputs by the majority of smallholder farmers is often aimed at improving the physical structure of the soil and providing nutrients to growing crops with little emphasis on the biological aspect (Woomer et al., 1994). The substrate quality and its rate of decomposition largely regulate the time over which mineral nutrients are released from an organic resource for plant uptake. The C sources in the organic substrates range from simple sugars to complex organic compounds including lignin, cellulose and polyphenols. High concentrations of some of these secondary compounds in organic inputs have been correlated to SOM stabilization (Parton et al., 1987; Oades, 1988). High quality organic materials, defined on the basis of their high nitrogen (N) concentration relative to lignin and polyphenols, have been known to have fast turnover rates, and poor precursors for SOM build-up (Palm et al., 1997; Giller et al., 1998). Given the relative scarcity of high quality resources on-farm, there is need to consider a possible complementary role of low quality organic materials in the development of soil fertility technologies. Low quality organic resources may be good precursors to SOM build-up because of their low turnover rates, and are therefore likely to significantly influence the spatial and temporal distribution of SOM in arable lands. Application of large amounts of lignified materials or those rich in polyphenols have the potential to allow SOM accumulation since they have mean resident time of >5 years (Melillo et al., 1989). Studies by Bonde et al. (1992) suggest that annual inputs seem to simultaneously contribute to a C build-up in the clay fraction. The relative proportion of clay in soil may be important in promoting SOM

43 19 stabilization through bonding of organic colloids with mineral surfaces (Tiessen and Stewart, 1983; Motavalli et al., 1994). Soils on many smallholder farms of Zimbabwe are sandy with mean clay contents rarely exceeding 60 g clay kg -1 soil. Given the critical role that SOM plays in low input cropping systems, what are the chances for building SOM under such conditions? Giller et al. (1997) and Palm et al. (2001a) both concluded that chances of building SOM in sandy soils are slim as these soils have no capacity to store and protect critical SOM levels required to sustain crop productivity. 2.6 SOM and Nutrient management strategies by smallholder farmers As low-input agricultural systems remain dominant in sub-saharan Africa including Zimbabwe, it is essential to improve understanding of the functioning of SOM under smallholder management. There is little available information on the degree to which overall farm management affects the various functions of the component parts of SOM. Smallholder farmers in Zimbabwe clearly recognize the importance of soil fertility and conservation (Mugwira and Shumba, 1986; Murwira and Mukamuri, 1998; Mapfumo and Giller; 2001), which is almost entirely dependant on locally available resources. There is general knowledge that application of organic residues improves the physical conditions of soil although information as to why this happens is still scanty (Sanchez et al., 1989). Farmer manipulation of the soil resource base differs in intensity partly because of the limited availability of either nutrient source or a result of differences in farmers conceptualization of soil fertility management. The issue of resource allocation influences production goals and is of direct relevance to soil fertility management. It therefore calls for a more direct intervention to improve soil status while at the same time strengthening farmer knowledge and skills.

44 20 Smallholder farmers have, over time, found widespread use of locally available forms of organic nutrient sources such as livestock manures, woodland litter, green manures, composted materials, household waste and crop residues (Campbell et al., 1998; Mapfumo and Giller, 2001). However, the negative nutrient balances, estimated at -22 kg N ha -1, -2.5 kg P ha -1 and -15 kg K ha -1 from arable lands (Smaling et al., 1997), are suggestive of management practices that are purely extractive with inadequate nutrient inputs to balance the system (Grant, 1995). The socio-economic boundaries within which farmers operate are inundated with numerous constraints. For example, crop residues have alternative uses as dry season livestock feed and/ or livestock bedding during the rainy months in Zimbabwe (Murwira, 1993; Nzuma et al., 1998). Manure application is a preserve of cattle owners, while composting is often too labour intensive. Overall, the quantities of organic nutrient inputs available to farmers are limited (Mapfumo and Giller, 2001). Farmers options for soil fertility replenishment may be grouped into three broad categories. These include (i) use of mineral fertilizers, (ii) crop sequences and intercrops with N 2 -fixing grain legumes, green manures and trees, and (iii) livestock manure, crop residues and other forms of organic nutrient sources from within and around the farm (Mugwira and Murwira, 1997; Buresh and Giller, 1998). In addition to supplying nutrients and improving soil physical properties, organic inputs can also lead to the formation of SOM (Woomer and Swift, 1994). However, SOM formation can be controlled to some extent by the quality, quantity and management of these organic residues.

45 Livestock manure Livestock manure, cattle manure in particular, is a traditional source of plant nutrients and can be rated as one of cheapest sources of organic fertilizer in many smallholder farming systems (Mugwira, 1984; Mugwira and Murwira, 1997). Manure application to soil results in increases in soil ph, infiltration rate, water holding capacity and decreased bulk densities (Grant, 1967; Murwira, 1993). Apart from supplying N, several studies have demonstrated the importance of manure as a major source micro-nutrients (Grant, 1967; Nhamo, 2001). The quality of livestock manure is very variable due to variation in animal diets and manure management before field application. Feeds rich in secondary compounds like lignin and polyphenols are more likely to contribute to increasing SOM levels following application of manure from such feeds. Decomposition studies of some communal area cattle manures by Murwira (1993) and Nyamangara et al. (1999) showed that N release is slow and spread over time. This therefore means that its application may not necessarily benefit the growing crop, but may have advantageous residual effects in the medium- to long-term. However, use of manure is a benefit of livestock owners. Soil C content under manure management is likely to be variable due to differences in the chemical composition of the manures, rate and mode of application and the frequency with which the manure is applied to a particular field Green manures The multiple role of leguminous crops in the smallholder farming systems ranks them highly on the soil fertility agenda (Sanchez, 1995; Giller et al., 1998; Mapfumo, 2000). Apart from supplying plant nutrients, legume green manure can be produced and utilized in situ. Application of legume green manure in arable

46 22 farming systems provides a large amount of readily decomposable C and a ready supply of N for soil microorganisms. In Zimbabwe, leguminous species such as Tephrosia, Crotalaria and Mucuna were recommended as N supply sources to maize as early as the 1950s (Rattray and Ellis, 1952; Gilbert, 1998). Studies have shown that between 40-80% of applied organic N from high quality residues is added to soil and mineralized to available forms (Haggar et al., 1993; Palm, 1995). In cereal cultivation, N contributions from high quality organic resources such as green manures were estimated to reach high levels of up to 250 kg N ha -1 yr -1 (Giller, 2001). However, information on potential contributions of green manures to the different SOM fractions is still scanty. Although green manures are most beneficial in providing nutrients in the short-term, an option more likely to be appealing to most smallholder farmers, they are likely to have a minimal role in SOM build-up (Palm et al., 2001) Intercrops and rotations The practice of legume-cereal intercrops by smallholder farmers is common in Zimbabwe although there is a general lack of awareness on the beneficial role in soil fertility amelioration of this farming method. Groundnut (Arachis hypogaea) has often been the common legume intercropped or grown in rotation with maize (Shumba, 1983; Waddington et al., 1998), although other legumes like cowpea (Vigna unguiculata) (Nhamo et al., 2003) are widely intercropped with maize. Inclusion of legumes in cropping systems may result in erosion control (Chikowo, 2004), smothering of weeds (Mapfumo et al., 2005), soil moisture conservation (Mapfumo and Giller, 2001) and biological nitrogen fixation (Giller, 2001), although the net benefits may vary significantly between seasons.

47 23 Maximum land utilization is probably the main reason why farmers intercrop. However, because of phenological differences, there is bound to be competition for nutrients, moisture and light in such cropping systems and SOM build-up may only be dependent on prevailing organic matter management strategies. Of significance to the soil C pool may be the inputs from incorporation of the crop residues because the supply of herbaceous material from intercrops in the form of senesced material is unlikely to be sufficient to impact on SOM. Maize yield increases have been realized under management systems that included incorporation of groundnut stover into soil (Mukurumbira, 1985). However, it is a common practice to remove the uprooted crop residues from the field, so there may be little or no C contribution by the legume to soil Crop residues Crop residues, by-products that result from the cultivation of cereals, legumes, root crops and tubers among other things, perform various functions in smallholder farming systems (Palm et al., 2001). When left in the field after harvest, they play an important role in nutrient cycling, erosion control, livestock feed, water conservation and maintenance of favourable soil physical properties (Powell and Unger, 1998). Livestock also play a role in converting low quality crop residues into somewhat richer nutrient sources. The magnitude of the beneficial effects of crop residues to SOM pools depends on the quantity and quality of the residues, the subsequent crop to be grown and soil management. Organic residues with different chemical compositions vary in their C and N mineralization potentials and decomposition patterns (Mafongoya and Nair, 1997). Maize, by virtue of its being the staple food crop in Zimbabwe, is grown widely and thus, the maize stover is a readily available residue in most smallholder farming communities. Maize stover

48 24 has a high C:N ratio implying that its nutrient release pattern is be slow, and with proper management, the residues could play an important role in SOM formation (Campbell et al., 1998; Mapfumo, 2000; Palm et al., 2000) Woodland litter The use of woodland litter as a soil fertility amendment is a traditional practice in most communal farming areas of Zimbabwe and has of late gained momentum in the wake of increasing fertilizer costs and dwindling livestock populations. While there is considerable information on the chemical composition and decomposition patterns of litter from temperate areas (Jensen, 1974; Aber et al., 1990), knowledge of litter as a source of plant nutrients, amounts collected and application rates is scanty. Annual woodland litterfall may be as much as 5 t ha -1 and according to Nyathi and Campbell (1993), measured annual litter collection in Masvingo, southern Zimbabwe, ranged from 0.2 to 1.2 t household -1. The same survey showed that those smallholder farmers who owned cattle realized the importance of woodland litter by putting the collected litter in cattle pens during the dry season to enhance manure quality. Possibilities of building SOM in this type of management are likely given the heterogeneous nature of the litter quality which usually comprise of both herbaceous and tree litter (Mtambanengwe and Kirchmann, 1995; Mtambanengwe, 2000). However, the exact proportion of decomposing woodland litter incorporated into SOM pool is not known unlike high quality organic fertilizers Household waste and compost Of all the organic amendments used by smallholder farmers, household waste is perhaps the most heterogeneous in terms of quality and composition. Proportions of paper, cooked food, plastics, metals and ash are normally very high in pits used

49 25 for discarding household wastes. Eventually, only decomposable material can be applied to arable land, thus sorting or separation of biological waste from the other materials is inevitable (Kirchmann, 1994). Household waste is perhaps one of the commonly used organic amendments, particularly in homefields and vegetable gardens, as virtually all households, resource poor and rich farmers have something to throw away (Campbell et al., 1998). On the other hand, compost material, because it is labour intensive, is applied to smaller field portions. Both high and low quality materials find their way in compost heaps. There is no information available as to what contributions compost manure and household waste have on SOM build-up Termitarium soil Termitaria soil is also an important nutrient source in Zimbabwean smallholder agriculture because of their high fertility status (Nyamapfene, 1986). Large portions of the Zimbabwean landscape are dotted with mounds of different species of termites. As such, access to termitaria soil for application to arable lands encompasses a large group of farmers. It is perhaps the feeding habits of the termites that determine the quality of the termitaria soil. Wood, grass or litterfeeding termites may consume large proportions of organic matter in their surroundings and the non-digested part of this material is accumulated in mounds and gallery walls (Dangerfield, 1990). Addition of termitarium soil to arable lands has been reported to increase the calcium, magnesium and top-soil clay contents. Farmers have reported residual effects lasting up to five years (Carter and Murwira, 1995), although the sustainability of their use is questionable given the amount of labour required to get the termitarium soil to the fields.

50 Mineral fertilizers Mineral fertilizer use in Zimbabwe is widespread in the sub-humid and high potential areas. The most common mineral fertilizer forms used are compound D (7%N:14%P 2 O 4 :7%H 2 O) and ammonium nitrate (34.5% N). Often, the nutrient source is purchased in amounts inadequate to replace those nutrients lost annually in harvested produce (Smaling et al., 1997). The recommended rates of top-dressing N fertilizer in Zimbabwe varies between 51 to 69 kg N ha -1 for Natural regions II to IV, but studies have shown that farmers apply less than a quarter of that (Grant, 1981; Campbell et al., 1998). In Integrated soil fertility management, several studies have shown the complementarities by combining mineral N fertilizers with different quality organic resources (Palm et al., 2001; Nyamangara et al., 2005). However, still scanty is information on the actual effect of this management practice on SOM dynamics in different soils Ash Virtually every household in communal Zimbabwe has access to ash. Ash is generated from firewood, a source of energy in cooking food and heating. Use of ash for soil fertility management is widespread (Kanyoka, 2004) but the method of use varies within and between households. Its composition also varies with source although calcium is the most abundant element in wood ash (Stromgaard, 1984; Araki, 1993). Under smallholder management, the quality of ash is compromised by a high sand and charcoal content making up ~80% of total weight (F. Mtambanengwe, unpublished data). Use of ash is usually in combination with household wastes and is commonly applied around the homestead. Because of the negligible quantities generated, information on its likely contribution to SOM has previously not been quantified.

51 27 CHAPTER 3 Study Sites and Research Methodology 3.1 Introduction The study was conducted at both on-station and on-farm sites across three agroecological regions/ Natural regions (NR) II to IV of Zimbabwe. Agro-zonation in Zimbabwe is mainly defined in terms of the amount of mean rainfall received annually and its distribution, and altitude (Vincent and Thomas, 1961; Department of the Surveyor-General, 1984). Natural Region II is a sub-humid zone that receives >750 mm yr -1, NR III receives between 650 and 750 mm yr -1, while NR IV is a semi-arid area receiving <650 mm yr -1 (Table 3.1). Two on-station experiments were set-up at Domboshawa (NR II) and Makoholi (NR IV) while onfarm experimentation was conducted at three namely Chikwaka (NR II), Chinyika (NR III) and Zimuto (NR IV). The study sites represent the dominant soil type in addition to rainfall regimes characterizing most of the smallholder farming systems in Zimbabwe. 3.2 On-station experimental sites Domboshawa Domboshawa Training Centre is located about 30 km north of Harare (31 19'E and 17 36'S) at an altitude of ~1500 metres above sea level (masl). The soils at the Domboshawa site are well-drained, moderately shallow to deep (up to 1.4 m) being a fusion of soils from granitic parent material (6G family) and dolerite intrusions (6E) (Thompson and Purves, 1981).

52 Table 3.1 Major characteristics of farming systems prevalent in the different agroecological regions of Zimbabwe 28 Agro-ecological region Rainfall Agricultural production systems Natural Region II (18.8% of total area) Natural Region III (17.4% of total area) Natural Region IV (33.0% of total area) >750 mm annual rainfall confined to the summer months of November to March mm annual rainfall with relatively high temperatures and infrequent, heavy falls of rain. Subject to seasonal droughts mm annual rainfall and subject to frequent seasonal droughts Intensive mixed farming of livestock (beef, dairy, pigs, poultry), fodder crops, cereal grains, cash and food crops (e.g. tobacco, cotton, maize, groundnuts, soyabeans), horticulture. Semi-intensive farming of livestock. Fodder crops, cash crops (e.g. cotton), food crops (e.g. maize, millets, sorghum, groundnuts) Semi-extensive farming, mainly livestock (cattle, goats, wildlife). Drought tolerant, short-duration cash and food crops (maize, millets, sorghum, cotton, sunflower, groundnut) The resultant sandy clay loam soils are Lixisols (World Reference Base, 1998) and can loosely be classified as a contact soil of poor to moderate fertility. The top 20 cm of soils from Domboshawa had an average of 7.3 g C kg -1, 0.7 g N kg -1, approximately 730 g sand kg -1, 220 g clay kg -1 and a ph of 5.2 (H 2 O). Potential mineralizable N from the sandy clay loams after two weeks of anaerobic incubation averaged 40 mg N kg -1.

53 Makoholi Makoholi Research Station is located about 280 km south of Harare (30 45'E and 19 47'S) in NR IV (Table 3.1) at an altitude of about 1200 masl. The soils belong to the 5G family and are well-drained, moderately shallow to deep derived from granitic parent material (Anderson et al., 1993). Makoholi is dominated by relatively infertile coarse sands, Arenosols (World Reference Base, 1998), very low in organic C and N. The soils had an average of 4 g C kg -1, 0.4 g N kg -1, approximately 820 g sand kg -1, 90 g clay kg -1 and a ph of 4.7 (H 2 O) in the top 20 cm of the profile. The N release capacity from the coarse sands at Makoholi only averaged 18 mg N kg -1 after two weeks of anaerobic incubation. 3.3 On-farm experimental sites Chikwaka The study site within Chikwaka communal area in NR II (Table 3.1) lies between S and E at an altitude which varies between 1230 and 1265 masl. Chikwaka is situated about 80 km northeast of Harare and has a history of over 70 years of smallholder farming. The soils are generally coarse sands derived from granite, Arenosols (World Reference Base, 1998). Twenty farmers were selected to take part in this three-year study. Average landholding is < 3 ha household -1 with the majority of the smallholder farmers owning only one field, usually around the homestead. Of the 20 farmers, only 5 owned out-fields. Host farmers fields had organic C contents varying between 3-8 g C kg -1, total N contents of between g N kg -1, g clay kg -1 and a ph (H 2 O) of between 4 and 5. Maize is the major crop grown through rain-fed

54 agriculture although a wide range of food and other commodities mainly for subsistence are also produced (Table 3.1) Chinyika Chinyika resettlement area (between S and E) in NR III (Table 3.1) and approximately 250 km east of Harare. The topography of Chinyika is dominated by massively jointed bedrock at an altitude of between 1320 and 1480 masl (Anderson et al., 1993). The soils range from coarse sands (Arenosols) to sandy clay loams (Lixisols). Chinyika was only opened by the Government of Zimbabwe for resettlement between 1982 and The Government policy since independence in 1980 has been to acquire land for resettlement to relieve pressures to overpopulated areas of the country while maintaining production. Under utilized large scale commercial farms were acquired for this purpose for which Chinyika was part to. A total of 20 farmers were identified for the soil fertility gradient work. Soils from fields under observation had between 4 and 6 g C kg -1, 0.5 and 0.8 g N kg -1, between 70 and 200 g clay kg -1 and a ph of between 4.5 and 5.6 (H 2 O) and can be classified as both Arenosols and Lixisols (World Reference Base, 1998) depending on the underlying bedrock. Chinyika Resettlement operates on a smallscale commercial basis, with each household owning an average landholding of 6 ha. Maize and tobacco form the main cash crops of many households. The intensive resettlement scheme has a livestock option to it with the majority of farmers owning at least 5 cattle.

55 Zimuto The site location in Zimuto communal area lies between S and E at an altitude of between 1175 and 1225 masl. Zimuto is in NR IV, 320 km southeast of Harare and receives a mean annual rainfall of between mm. History of settlement and smallholder farming dates over 70 years. Average landholding is 3 ha household -1. The soils range from coarse sands on topland position to sandy clay and clay loams which occur in low lying vlei depressions dotted across much of the landscape. The majority of these depressions are moist throughout much of the year, due to a high water table formed by underlying granite. Farmers take advantage of these moist depressions and grow winter wheat, dry season maize and rice among other crops. Most of these food crops are grown for subsistence (Table 3.1). The study involved 20 farmers from Zimuto communal area. Soils from host farmers fields (Arenosols) had variable properties varying between 4 and 7 g C kg -1, 0.4 and 0.8 g N kg -1, 50 and 90 g clay and a ph of between 4 and 5 (H 2 O). 3.4 Overview of the farming systems Zimbabwe has a dual agricultural system comprising of large-scale commercial and smallholder farmers. Before the second phase of the government land reform programs of 2001, most of the productive parts of NR I and II were occupied by large-scale commercial sector occupying about 11 million hectares (Rukuni, 1994). The hectarage of large commercial farming has since been reduced by more that half in the last five years (United Nations, 2005). The other part mainly comprised over 1 million smallholder households occupying about 16 million hectares and a further smallholder units covering about 3.3 million hectares in the

56 32 resettlement areas. Prior to the arrival of the white settlers, millets were the staple food of Zimbabwe. Emphasis on maize production only took precedence in the 1960s following a launch of an agricultural policy that promoted commercial farming through a wide reliance of imported seed of maize and other crops. Domboshawa and Makoholi are agricultural institutions wholly owned by the Government through the Ministry of Agriculture. Both centres have crop and livestock units. Low-input maize-based systems with strong crop-livestock interactions dominate the farming systems in the three communal area study sites of Chikwaka, Chinyika and Zimuto (Table 3.1). The extended family plays a central role in agricultural production. Women do most of the work in arable cropping lands, particularly in situations where men are employed away from home. Livestock provide draught power and manure to arable fields while crop residues, particularly maize stover, are exported from the fields and strategically used as feed for livestock during the dry season. The residues are either stored for feed in specially constructed stover racks adjacent to cattle pens or thrown directly into the cattle pens to provide both feed and bedding and to boost manure stocks. During the cropping months of November to May, livestock is kept away from arable fields but uncontrolled communal grazing dominates the dry season months from July to October. It is a normal practice for farmers to plough their fields in the dry season (winterploughing) in June and July. However, farmers with limited draught power only plough once a year at the beginning of a new rainy season (October/ November).

57 Overview of the methodological approach used The study was based on an interactive bottom-up approach (Heron and Reason, 2001), involving farmers from the onset. The issue of loss of soil productivity was identified as the single most pressing problem the farmers in the three communal areas faced. Literature reviews, expert interviews, exchange of information and establishment of commitment with extension workers, farmers, farmer organizations and local political structures within the proposed study sites formed the inventory phase of the study. Field selection criteria included on-farm sites that have, over time, been systematically and consistently managed by known groups of farmers. Gathered information based on reconnaisance trips, farmer participation, key informant interviews and literature on biophysical and socio-economic characteristics of the respective farming systems, was used to classify farmers according to wealth, age of household and competence in farming. These attributes were assumed to give insights relating to the farmers history of organic matter management, paying particular attention of C inputs. Three different social categories were identified following characterization of resource endowment. The three identified farmer groups were (i) Resource-endowed farmers, (ii)resourceconstrained farmers, and (iii) Intermediate farmers - a diverse group lying in between the above two. They are generally a transitional group (Table 3.2). Main activities included meeting with farmers, field experiments and intensive laboratory work (Figure 3.1). The selected farmers helped to identify appropriate field sites with attributes that included:

58 Table 3.2 Descriptive criteria for classification of farmers in Chikwaka, Chinyika and Zimuto smallholder farming areas 34 Farmer category Description Resource-endowed Intermediate Resource-constrained Adequate accommodation with brick under galvanized iron sheets, asbestos or grass thatch. Own farming implements e.g. a plough; an ox-drawn cart High livestock ownership with >10 cattle and at least 2 oxen Have >3 ha of arable land Relatively high capacity to secure inputs Regular contact with extension and generally employ extension recommendations, either through direct training (e.g. the Master Farmer programme by AREX*) or indirectly (e.g. copying other farmers) Generally have more than 20 years of farming experience Often have access to credit facilities Varying resource ownership (e.g. may have a plough but not enough draught animals) Cattle ownership 4 Includes the eager-to-learn type farmers but are limited by resource base (most of the relatively young farming households fall into this category) Seek to enhance their production through communal social arrangements (e.g. combining draught animals) and active involvement with extension agencies. Landholding averages 2 ha household -1 Limited access to credit Major constraints include lack of farming implements; lack of draught power (0-3 cattle) and lack of cash to buy inputs Variable farm size (0.5 to > 3 ha) but those with large landholdings typically utilize a small proportions of their total arable land Unlike other farmer groups, they generally have limited or no source of remittances Constituted by a significant number of female-headed and old (> 60 years) households Usually not members of local social groups and often shy away from community meetings Generally do not avail themselves for training by AREX Often sell their labour to other two groups * The Master Farmer programme is run by the Department of Agricultural Research and Extension (AREX) of the Zimbabwe Ministry of Agriculture to train individual smallholder farmers on its recommended farming methods

59 35 i. A known history of organic matter applications ii. Different organic matter management (cereal or other stover, livestock manure, woodland litter, compost or household waste, termitaria) iii. iv. Fields with no external C application in the past 5 years Distinct soil textures. Farmer participatory research approaches (FPRA) were used in order to identify the main problems smallholder farmers of the respective study sites faced in crop productivity. Focussed group discussions, priority-ranking techniques, transect walks and informal interviews constituted the major FPRA tools. During the same meetings, including re-visits to key informants, existing and preferred priorities in solving the soil fertility problem were identified. The objectives of the study were outlined during farmer workshops following which the range and quantities of organic resources available to farmers was established. Using historical information on nutrient and organic matter management, at least 20 farms were selected in each of the three study areas, with at least six replicates per each of the three identified farmer class in the respective areas. The on-station sites were researcher managed and were set-up to investigate the effect of different quality organic resources of known quantities on enrichment of different SOM fractions, soil N dynamics and subsequent crop productivity.

60 Entry point Activity Output 36 Background information & problem identification Problem: overall decline in crop yields due to soil fertility degradation Reconnaissance trips Site selection Key informant interviews Farmer participatory research approaches (FPRAs) FPRAs particular attention to C inputs within arable systems Selection of representative field sites; On-farm & on station experimentation with Resource allocation to different fields Determination of nature & magnitude of soil fertility gradients: Biophysical & socio-economic properties Farmers perception of: Field productivity Socio-economic characterization Organic matter management history for rich & poor fields Soil sampling for Organic C + nutrient status Farmer/ Researcher managed trials with different quality & quantity organic resources Assess management effects on soil & maize productivity SOM fractionation Determination of soil labile C fractions Farmer classes identified: Resourceendowed; Intermediate; Resource- constrained Field states: Rich & Poor fields established Tally farmer indicators against laboratory indices; Existence of within farm & between farm soil fertility gradients Organic resource quality and quantity effects on maize & SOM characteristics quantified Causes of soil fertility gradients identified Understanding of profile N & SOM dynamics enhanced Relationships between SOM fractions, soil N & maize yields quantified Figure 3.1 Schematic diagram of the methodological approach adopted for the study. Solid arrows indicated direction of flow of events while dotted arrows represent key outputs necessary for each entry point.

61 37 CHAPTER 4 Organic Matter Management as an Underlying Cause for Soil Fertility Gradients on Smallholder Farms 4.1 Abstract This chapter focuses on establishment of management factors influencing the formation of within-field/farm soil fertility gradients. Management of spatial and temporal variability of soil fertility within fields and farms is one major challenge for increasing farm-level crop productivity in smallholder agriculture. Using farmer participatory research approaches, host farmers belonging to each of the Resource-endowed, Intermediate and Resourceconstrained farmer groups identified the most (rich) and least (poor) productive field or field section, which were then studied over two years. Farmer criteria for defining soil fertility ranged from colour through elements of soil structure to crop response following external nutrient inputs. The fertility ranking of fields consistently matched with laboratory indices, with rich fields containing significantly more soil organic carbon (SOC) and nutrients than the corresponding poor fields. Fertility gradients were evident within and across farms belonging to different farmer classes. The mean SOC content for rich fields were >6.0 g kg -1 compared with <4.6 g kg -1 for the designated poor fields. Rich fields belonging to Resource-endowed farmers had 16-28% more SOC than those belonging to their resource-constrained counterparts, suggesting differences in organic matter management. Differences in SOC and fertility status between rich and poor fields were wider in Chikwaka and Zimuto which had more than 70 years of cultivation in contrast to Chinyika which had been under smallholder farming for only 20 years, suggesting that the observed fertility gradients are a cumulative effect of years of differential management practices by the different farmer classes. Analysis of potential benefits from in situ organic biomass inputs suggested that the processes of organic matter capture and utilization discriminated against Resourceconstrained farmers. About 50% of in situ biomass, preferentially maize stover, was lost in three dry season months, and up to 72 % of potentially recyclable N is lost from poor This Chapter has been published as: Mtambanengwe, F. and Mapfumo, P Organic matter management as an underlying cause for soil fertility gradients on smallholder farms in Zimbabwe. Nutrient Cycling in Agroecosystems 73:

62 fields managed by Resource-constrained farmers. In contrast, Resource-endowed farmers incorporated more than 1.5 t C, 25 kg N and 5 kg P ha -1 season -1 because of their access to draught power during the early dry season. Such inputs could make a difference on these nutrient-depleted soils. Intermediate farmers represented a diverse transitional group whose size and variability could be indicative of the dynamism of technology usage. It was concluded that management of soil fertility gradients to increase crop productivity on smallholder farms hinges on increasing the capacity and efficiency with which organic matter is generated and utilized by different farmer wealth groups across temporal scales Introduction Concerns about continued decline in soil productivity under smallholder farming systems in Sub-Saharan Africa have increased calls for soil fertility management strategies that enhance soil biological functions and protect available resources (Swift, 1998; Gichuru et al., 2003). Smallholder farming systems in most parts of this region including Southern Africa are characterised by negative soil nutrient balances due to low external nutrient inputs (Smaling et al., 1997), and soil organic matter (SOM) is often the single largest source of nutrients for growing crops (Woomer et al., 1994). Nutrient release from SOM is dependent upon mineralization of biologically active fractions (Vanlauwe et al., 1994; Barrios et al., 1996), which may vary qualitatively and quantitatively in relation to the quality and quantity of organic resources used. Differences in land and organic matter management practices by farmers may therefore lead to changes in SOM quality and quantity depending on inherent soil properties and prevailing environmental conditions. While much of the variation in soil productivity observed across farming landscapes has often been attributed to inherent differences in soil forming factors such as climate, parent material and catenary positioning (Foth, 1984), within-field and within-farm variation has largely remained unexplained. For instance, it is common to find differences in

63 productivity between two sections of the same field, or between fields sharing the same soil parent material and textural properties. 39 While farmers generally recognize the existence of such spatial soil variation within their fields and farms (Scoones et al., 1996; Chikuvire, 1998), the nature and causes of these high and low zones of fertility, or soil fertility gradients, are still not well known. The little explained variation has been attributed to the physically well-defined field environments such as termite mounds (Nyamapfene, 1986), homestead surroundings (Zingore, 2006)and areas under tree canopies (Chivaura-Mususa and Campbell, 1998). In this study, differential effect of organic matter management on SOM status is considered as a potential cause for these within field/farm soil fertility gradients. Smallholder farmers have, over time, found widespread use of locally available forms of organic nutrient sources such as livestock manures, woodland litter, green manures, composted materials, household waste and crop residues (Campbell et al., 1998; Mapfumo and Giller, 2001). However, the negative nutrient balances, estimated at -22 kg N ha -1, -2.5 kg P ha -1 and -15 kg K ha -1 from arable lands each season (Smaling et al. (1997), are suggestive of numerous constraints facing smallholder farmers in their management of nutrient resources. In Zimbabwe, crop residues have alternative uses as dry season livestock feed and/ or livestock bedding during the rainy months. Manure application is a preserve of livestock owners, while composting is often too labour intensive. Overall, the quantities of organic nutrient inputs available to farmers are limited (Mapfumo and Giller, 2001).

64 40 With the growing need for agricultural intensification, soil management options that focus on efficient and sustainable utilization of locally available organic resources are required. Previous studies on organic matter management have tended to concentrate on high quality organic materials from agroforestry tree-species (Mafongoya et al., 1998; Chikowo et al., 2004), legume green manures (Waddington, 2003) and composted cattle manure (Nzuma, 2004). These high quality organic materials, defined on the basis of their high nitrogen (N) concentration relative to lignin and polyphenols, are able to decompose and supply nutrients to growing crops within short time periods (Heal et al., 1997; Palm et al., 1997). Given the relative scarcity of most these resources on-farm, there may be need to consider the complementary role of low quality organic materials in the development of soil fertility technologies. Low quality organic resources are good precursors to SOM build-up because of their low turnover rates (Palm et al., 1997), and are therefore likely to contribute significantly to the spatial and temporal distribution of SOM in arable lands. This study focused on identification of management factors influencing the formation of within-field/ farm soil fertility gradients paying particular attention to the organic C and N inputs. The ultimate goal is to manage these soil fertility gradients in a way that improves on overall farm productivity. The overall objective of this study was to identify management factors influencing the formation of within-field/ farm soil fertility gradients paying particular attention to the organic carbon (C) and nitrogen (N) inputs by farmers across different social gradients. The following specific objectives were pursued:

65 41 i. To identify the main indicators for soil productivity as perceived by farmers and determine whether these are consistent with soil fertility indices from the laboratory ii. To quantify the amount of weed and crop residue biomass available for incorporation into soil of contrasting fertility status by different farmer wealth class iii. To determine potential benefits of in situ field biomass capture in enhancing soil organic matter levels and soil nutrient cycling at field scale 4.3 Materials and methods Selection of field sites and soil sampling The study was carried out in three smallholder farming areas of Chikwaka, Chinyika and Zimuto described in Chapter 3. Two field sites contrasting in productivity potential (rich and poor fields) were chosen for monitoring and experimentation from each study site. An overview of farm management practices by each of the three identified farmer groups namely Resource-endowed, Intermediate and Resource-constrained farmers (Chapter 3) were represented by at least 6 farms per study site. Soils were then collected from these rich and poor fields before the onset of the rainy season for laboratory characterization. For each site, at least 10 auger samples were collected from the top 20 cm (plough layer), bulked in a clean bucket and the soil thoroughly mixed before a composite sub-sample was withdrawn for laboratory analysis. These soils were analysed for texture, ph, total organic C (SOC), N, P, Olsen P, mineral N after two weeks of anaerobic incubation (Anderson and Ingram, 1993). Ca, Mg and K were analysed according to Page et al. (1982).

66 Biomass quantification and analyses The quantities of in situ organic biomass potentially incorporated into soil by farmers were measured over a two-year period in the rich and poor fields. Farmers with access to draught power and labour often use residual moisture from the rainy season to winter-plough their fields after crop harvest between April and August. These fields are then ploughed again in October-November at the start of the new cropping season. The other farmers do not winter plough and usually prepare their fields only once at the start of new season. Accordingly, field biomass was measured in situ during the dry season periods of June/July (early dry season) and October (late dry season) before the beginning of a new cropping season. All organic material which included standing and dead matter on field surfaces falling within four replicate grids measuring 1 x 1 m 2 randomly selected from a 20 x 5 m 2 grid was collected in labelled khaki bags. The collected biomass was separated into two distinct fractions namely (1) maize stover- related material only and (2) non-stover biomass, which included live broad-leaved weeds and grasses, grass litter, animal droppings and other crop residues. The samples were oven-dried at 60 C to a constant weight and dry matter measured. Subsamples of the organic materials were milled to pass through a 1 mm sieve and analysed for total C, N, P and lignin (Anderson and Ingram, 1993). The sub-samples were also analysed for total soluble polyphenols using the Folin-Denis method (Quarmby and Allen, 1989). Potential soil C, N and P contributions from the organic materials were estimated by multiplying the nutrient concentration by the corresponding biomass quantity.

67 Carbon and nitrogen mineralization of field surface organic biomass Carbon and N mineralization of different organic materials found on field surfaces following crop harvest were determined in leaching tube incubations (Giller, 1999; Stanford and Smith, 1972). The leaching tube incubation method gives an estimate of potential N mineralization from different materials under conditions of optimal moisture and temperature. The method is non-destructive and allows periodic leaching of the released N from the same tube over time using a dilute nutrient solution. This simulated N removal by the root system under field conditions. The leaching solution contained 1mM CaCl 2 ; 1mM MgSO 4 ; 0.1mM KH 2 PO 4 and 0.9 mm KCl and is aimed at replacing salts removed from the soil during leaching (Giller, 1999). The treatments were: (i) groundnut stover, (ii) maize stover, (iii) cowdung, (iv) mixed biomass from rich fields, (v) mixed biomass from poor fields, (vi) a mixture of maize stover and non stover biomass from both rich and poor fields in a representative ratio in which they occurred in the field (1:2), (vii) unamended control. Groundnut stover represented the relatively high quality organic resource while cowdung, a common organic material on field surfaces during the dry season, was used as one of the non-residue organic materials that could substantially influence N release. Prior to mineral N determination, all organic materials were ground and applied at a rate equivalent to 100 mg N kg -1 soil following initial total N and C analyses. The materials were mixed with 150 g soil (2:1 soil:sand mixture). Leaching was done with 120 ml of leaching solution in 3 x 40 ml aliquots. The initial NH + 4 N and NO - 3 -N for all treatments was analysed from leachates collected on day 0. The tubes were subsequently leached on days 1, 2, 4, 8, 16, 24, 32, 48, 64, 88, 120 and 152. The tubes were incubated in the dark at 25 C, and excess

68 44 water following each leaching event was removed by a mild suction pump. The leachates were analysed for NH + 4 -N and NO - 3 -N. Net N mineralization was calculated as the difference between the N released from the amended test samples and that of the unamended control. Net cumulative N mineralization from the different organic materials was determined over 152 days of incubation. Carbon mineralization rates in the organic materials were estimated by 10 ml of 0.1 M NaOH trap contained in small vials hung from the top of each sealed leaching tube (Stotzky, 1965). The amount of trapped CO 2 was determined by back titration using 0.1 M HCl and phenolphthalein indicator (0.5%) at intervals of 1, 2, 4, 8, 12, 16, 24, 32, 48, 64, 88, 120 and 152 days. Two to three drops of 1.0 M BaCl 2 were added to each vial to stabilise the trapped CO 2 as CO 3 - before titration. The amount of trapped CO 2 -C was calculated as follows: mg CO 2 -C = (ml HCl blank ml HCl sample) x M x 22 Sample weight (mg) Where: M = molarity of HCl 22 = the equivalent weight of CO Data analyses Means for in situ biomass and potential C, N and P contribution, for a given sampling period, were analysed by ANOVA using MINITAB Statistical package (Minitab Inc., 2000) with farm sites used as replicate blocks for each study area. All mean comparisons were made at p < Biomass means between the two sampling times were compared using t-tests.

69 Results Characteristics of rich and poor fields A farmer criteria A field s relative contribution to household food reserves constituted the most important criteria in ranking its productivity among others within a farm. Fields that consistently gave high yields were considered rich, contrary to designated poor fields which invariably gave poor yields and exhibited low crop responses despite addition of external nutrients such as manure and mineral fertilizers (Table 4.1). Formation of clods (stable aggregates) during tillage was considered a sign of a productive soil and this was often reflected in soil clay content and colour. Most light coloured and sandy soils were perceived unproductive even under relatively high levels of agronomic management. It was also revealed that the rich fields were often given the first priority with respect to major crop management activities such as inputs and early cropping. Farmer designation of rich and poor fields in all the three agro-ecological regions under study was generally consistent with findings from laboratory analyses. While about 80% rich and poor fields invariably consisted of sandy to loamy sand soils with <90 g clay kg -1 soil, few rich fields recognized by farmers as having high clay contents had between 100 to 200 g clay kg -1 soil. Overall, SOC levels were significantly higher in rich than poor fields. Average SOC contents for rich fields were 6 g C kg -1 soil in Chinyika and 7 g C kg -1 soil in Chikwaka and Zimuto. These values were 31 to 49% higher than the designated poor fields (Table 4.2). However, the relative SOC contents for both field types differed significantly with farmer classes.

70 Table 4.1 Smallholder farmer indicators for highly productive (rich) and poorly productive (poor) fields or field sections in Zimbabwe (ranked in order of importance) 46 Rich field/ field sections Poor field/ field sections 1. Consistently contributing the highest amount of yield (typically maize grain) to household food reserves 1. Crop yields are poor year after year regardless of management effort 2. Gives high crop growth and yield responses to external inputs (both organic and inorganic). Even small additions of mineral N fertilizer such as 1 bag ha -1 (~17 kg N ha -1 ), at least 15 bags (1 bag = 50 kg) of maize grain are harvested. 3. Red or grey coloured soils 4. Exhibit clods on tilling 2. General crop failure without external nutrient inputs (e.g. no maize or groundnut grain is obtained without addition of manure or mineral fertilizer) 3. Low response to external nutrient inputs. Generally less than 7 bags ha -1 (1 bag = 50 kg) with addition of about 1 x 50 kg mineral fertilizer (~17 kg N ha -1 ) 5. Soils do not dry easily and do not readily wilt crops 6. Relatively high clay content 7. Presence of islands of termite mounds 4. Often poor seed emergence due to surface crusting 5. Light coloured soils with poor capacity to hold moisture 6. Soils too sandy to show any aggregation upon ploughing

71 47 In Chikwaka, the rich fields belonging to Resource-endowed farmers averaged 6.9 g C kg -1 soil compared with 5.4 g C kg -1 soil in rich fields belonging to Resourceconstrained farmers, while comparative figures were 6.5 versus 5.6 g C kg -1 for Chinyika and 7.1 versus 5.9 g C kg -1 soil for Zimuto (Figure 4.1). Corresponding differences with respect to poor fields were small. For instance, poor fields belonging to Resource-endowed, Intermediate and Resource-constrained farmers in Chikwaka averaged 5.0, 5.0 and 4.4 g C kg -1 soil (Figure 4.1). Soil analytical results showed that nutrient concentrations were significantly higher in rich than poor fields, particularly with respect to total N, mineralizable N, exchangeable Ca and Mg (Table 4.2). Consistent with the SOC results, the magnitude of differences in concentrations of the various nutrients between rich and poor fields was considerably narrow in Chinyika compared with Chikwaka and Zimuto. For example, rich fields in Chinyika contained 56% more mineralizable N than poor fields compared to 66 in Chikwaka and 80% in Zimuto. The same trend was observed for Mg, with corresponding differences of 14, 50 and 120% for Chinyika, Chikwaka and Zimuto respectively. There were, however, contrasting patterns in soil P and K concentrations in all the study areas. Both field types exhibited invariably low P contents, with Olsen P values of no more than 8 mg kg -1 soil across the study sites. Soils in Chinyika and Zimuto averaged between 0.1 and 0.2 cmol (c) kg -1 soil exchangeable K, about 6 times more than soils in Chikwaka (Table 4.2).

72 48 8 (a) Chikwaka (>750 mm yr -1 ) (b) Chinyika ( mm yr -1 ) Soil organic C (g kg -1 ) (c) Zimuto ( mm yr -1 ) Rich field Poor field Resource-endowed farmer Intermediate farmer Resource-constrained farmer Figure 4.1 Soil organic C content of rich and poor fields belonging to Resource-endowed, Intermediate and Resource-constrained farmers in Chikwaka, Chinyika and Zimuto. Bars represent SEDs

73 49 Table 4.2. Soil characteristics of smallholder farmers rich and poor fields in three agroecological regions of Zimbabwe Soil attribute Chikwaka Chinyika Zimuto Rich field Poor field Rich field Poor field Rich field Poor field Organic C (g kg -1 ) 7.1 (0.64) 4.6 (0.17) 5.8 (0.31) 4.9 (0.28) 6.7 (0.55) 4.5 (0.22) Total N (g kg -1 ) 0.7 (0.10) 0.5 (0.05) 0.8 (0.07) 0.6 (0.04) 0.8 (0.08) 0.5 (0.05) Total P (g kg -1 ) 0.1 (0.02) 0.1 (0.01) 0.1 (0.00) 0.1 (0.00) 0.1 (0.01) 0.1 (0.01) Olsen P (mg kg -1 ) 7.8 (1.43) 4.3 (0.78) 3.4 (0.32) 3.4 (0.52) 3.8 (0.64) 2.1 (0.37) Mineralizable N (mg kg -1 )* 26.0 (2.45) 15.7 (1.87) 16.4 (1.87) 10.5 (1.29) 24.7 (3.87) 13.8 (3.87) Exch. Ca (c mol (c) kg -1 ) 1.2 (0.32) 0.4 (0.06) 1.0 (0.17) 0.8 (0.09) 1.3 (0.17) 0.5 (0.16) Exch. Mg (c mol (c) kg -1 ) 0.6 (0.14) 0.3 (0.03) 0.8 (0.08) 0.7 (0.08) 1.1 (0.30) 0.5 (0.11) Exch. K (c mol (c) kg -1 ) 0.03 (0.001) 0.02 (0.001) 0.2 (0.01) 0.1 (0.01) 0.1 (0.02) 0.1 (0.02) Sand (g kg -1 ) 850 (12.5) 870 (4.4) 820 (10.3) 820 (6.3) 840 (19.6) 860 (10.2) Silt (g kg -1 ) 67 (4.0) 58 (4.2) 99 (6.9) 100 (3.3) 70 (6.2) 63 (4.3) Clay (g kg -1 ) 83 (10.0) 72 (2.3) 81 (5.1) 80 (4.1) 90 (20.2) 77 (11.1) ph (0.01M CaCl 2 ) 4.4 (0.24) 3.7 (0.09) 4.61 (0.09) 4.46 (0.03) 5.06 (0.20) 4.13 (0.11) * mineralizable N after two weeks of anaerobic incubation. Figures in parentheses denote standard error of the mean

74 In situ biomass available for incorporation Early dry season period The total in situ biomass available on field surfaces during early dry season, about one month after harvesting, comprised mainly of maize stover and non-stover biomass. The non-stover biomass included living and non-living weed plant materials, unidentified organic material from the previous season and animal droppings. Overall, maize stover constituted only 27% of total biomass in Zimuto, compared with 45% for Chinyika and 51% for Chikwaka. This was attributed to comparatively low quantities of maize biomass generated under low annual rainfall received in Zimuto, and also to the fact that farmers in this area tended to be efficient in their collection of the stover as a dry-season livestock feed supplement. The quantity of maize stover ranged from about 0.4 t ha -1 in semi-arid (~640 mm yr -1 ) Zimuto to 1.2 t ha -1 under high rainfall (>750 mm yr -1 ) in Chikwaka. Neither field type nor farmer class significantly influenced the quantities of maize stover available during the early dry season period for all study sites. For instance, maize stover biomass quantities across the three farmer classes in Chinyika and Chikwaka were within 5% (Figure 4.2). In contrast, both field type and farmer class significantly influenced total biomass quantities because of their effect on nonstover biomass. Rich fields belonging to Resource-endowed farmers had consistently higher biomass than the respective poor fields across all three study areas (Figure 4.2). There were, however, no significant differences between the two field types for Intermediate and Resource-constrained farmers except in Chikwaka where the rich fields for Intermediate farmers were consistent with those belonging to Resource-endowed farmers.

75 51 Early - non stover biomass Early - maize stover biomass Late - non stover biomass Late - maize stover biomass (a) Chikwaka (> 750 mm yr -1 ) SED Maize stover (Early = 0.07; Late = 0.03) SED Non-stover (Early = 0.06; Late = 0.05) SED Overall (Early vs Late) = Biomass contribution (t ha -1 ) (b) Chinyika ( mm yr -1 ) (c) Zimuto ( mm yr -1 ) SED Maize stover (Early = 0.03; Late = 0.02) SED Non-stover (Ealy = 0.08; Late = 0.02) SED Overall (Early vs Late) = 0.05 SED Maize stover (Early = 0.04; Late = 0.02) SED Non-stover (Early = 0.08; Late = 0.05) SED Overall (Early vs Late) = Early Late Early Late Resource-endowed farmer Early Late Early --Rich field-- --Poor field-- --Rich field-- --Poor field-- --Rich field-- --Poor field-- Intermediate farmer Late Early Late Early Late Resource-constrained farmer Figure 4.2 In situ biomass in rich and poor fields of three farmer categories from Chikwaka (a), Chinyika (b) and Zimuto (c). Early denotes early dry season biomass and Late is late dry season biomass

76 52 The total biomass on Resource-endowed farmers rich fields ranged between 1.7 and 2.7 t ha -1, about % higher than rich fields from Resource-constrained farmers Late dry season period The total biomass quantities measured in October were between 30-46% lower than recorded during the early dry season period. Maize stover biomass contribution to total in situ biomass was between 22% in Zimuto and 32% in Chikwaka, representing more than 50% reduction between the two time periods. Overall, there were narrower differences in total biomass between rich and poor fields during the late dry season compared with the early dry season period (Figure 4.2). However, neither field status nor farmer class significantly influenced late dry season maize stover biomass in Chikwaka. In Zimuto, maize stover biomass from rich fields was about double that from the poor fields, but overall quantities recorded did not exceed 0.2 t ha -1. Neither field type nor farmer class significantly affected non-stover biomass in all areas except in Chikwaka where rich fields recorded higher amounts than poor fields. The rich fields out-yielded poor fields by an average of 26% for Resource-endowed farmers, 33% for Intermediate and 38% for Resource-constrained farmers (Figure 4.2). Quantities of non-stover biomass measured ranged between 0.8 and 1.4 t ha -1 in Chikwaka, 0.4 and 0.5 t ha -1 in Chinyika and between 0.5 and 0.7 t ha -1 in Zimuto.

77 Potential C and N contributions from in situ biomass The total amount of C and N captured in situ at the end of the dry season under high (Chikwaka) and medium (Chinyika) rainfall conditions dropped by between 30-40% from early dry season figures of t ha -1 for C and 7-20 kg ha -1 for N (Table 4.3). The loss of maize stover contributed more to the reduction in potential C and N inputs than non-stover biomass. Over 60% of maize stover C was lost during the 3-month dry period of July to October, translating to about 300 kg C ha -1 in Chikwaka and 100 kg C ha -1 in Chinyika. The amount of biomass C and N from non-stover materials were significantly higher in rich than in poor fields under high rainfall conditions in Chikwaka (Table 4.3), while only N was significantly high under rich fields in Chinyika. In contrast, no significant differences between the two field types could be attested to maize stover in both these areas. Under semi-arid conditions in Zimuto, there was a significant interaction between field status and time of potential incorporation for both maize stover and non-stover biomass (Table 4.4). There was no significant difference between rich and poor fields in the amount of C and potentially recyclable N through maize stover biomass during the early dry season period. However, by the end of the dry season, the amount of recyclable N in the rich field was about twice that of the poor field, notwithstanding the significant C and N reductions in both field types between the two periods. This was attributed to generally better protection of rich fields against grazing. Contrary to maize stover, which contributed < 0.2 t C ha -1 non-stover materials gave up to 0.6 t C ha -1. There was significantly more recyclable N in poor than rich fields, although the overall amounts were < 6 kg N ha -1 (Table 4.4).

78 Table 4.3 Potential C and N contributions from maize- and non-stover biomass at different periods of incorporation under smallholder farmer management in high (Chikwaka) and medium (Chinyika) rainfall areas 54 Site, time of incorporation and field status Carbon (kg C ha -1 ) Nitrogen (kg N ha -1 ) Maize stover Non-stover Maize stover Non-stover a) Chikwaka (>750 mm) Early dry season Late dry season SED Rich field Poor field SED ns 30.2 ns 0.5 b) Chinyika ( mm) Early dry season Late dry season SED 12.6 ns 0.3 ns Rich field Poor field SED ns ns ns 0.2 SED standard error of the difference; ns not significant

79 Table 4.4 Potential C and N contributions from maize- and non-stover biomass at different periods of incorporation under smallholder farmer management under semi-arid conditions in Zimuto ( mm year -1 ) 55 Biomass type and time of incorporation Carbon (kg C ha -1 ) Nitrogen (kg N ha -1 ) Rich field Poor field Rich field Poor field Maize stover Early dry season Late dry season SED Non-stover Early dry season Late dry season SED SED standard error of the difference of means C and N release patterns from in situ biomass Organic materials collected from the two field types were not significantly different in quality for all the quality parameters tested except for N (Table 4.5). In Zimuto, in situ biomass from rich fields had at least 35% more N per unit mass compared with biomass from poor fields. Generally, the materials were of low quality with C:N ratios ranging between 45 and 65 (Table 4.5). Lignin contents of the field biomass were variable, with highest lignin contents of >10% on a dry weight basis

80 56 being for recorded biomass from fields in Zimuto, while that from Chinyika averaged 8.9 % (Table 4.5). All the organic materials analyzed had total soluble polyphenols of less than 1.6%, and gave a mean ash content of about 12%. Carbon and N mineralization patterns by the different various materials tested in the laboratory were significantly different throughout the 152 days of incubation. Groundnut (Arachis hypogaea) stover had the highest rate of CO 2 -C evolution, mineralising about 56% of the added C over the incubation period. The C mineralization pattern of cowdung was almost linear and showed no signs of levelling off after the 5 months of incubation (Figure 4.3). Maize stover released the least amounts of CO 2 -C while a combination of maize stover and non-stover biomass significantly improved C availability (Figure 4.3). Nitrogen release by the different organic materials was consistent with the carbon mineralization patterns. During the first 6 weeks of incubation, only groundnut stover had released mineral N in amounts exceeding the unamended control soil, showing a prolonged initial N immobilization phase for the rest of in situ biomass components. At the end of the incubation period, cumulative N mineralized from the different in situ biomass components was significantly different. Highest amounts of mineral N were released from groundnut stover, which had a cumulative total of 196 mg N kg -1 soil (Figure 4.4). Mineral N released from maize stover alone was significantly lower than that from a combination of maize stover and non-stover biomass. Sole maize stover had cumulatively immobilized about 24 mg N kg -1 by the end of the 5-month incubation period compared with in net mineralization of more than 10 mg N kg -1 for biomass from rich fields (Figure 4.4).

81 57 Table 4.5 Quality parameters of in situ biomass* on rich and poor fields of smallholder farms in three agroecological regions of Zimbabwe Site and quality attribute Rich fields Poor fields Chikwaka (>750 mm yr -1 ) Organic C (g kg -1 ) Total N (g kg -1 ) Total P (g kg -1 ) Lignin (%) Polyphenols (%) Ash (%) Chinyika ( mm yr -1 ) C (g kg -1 ) N (g kg -1 ) P (g kg -1 ) Lignin (%) Polyphenols (%) Ash (%) Zimuto ( mm yr -1 ) C (g kg -1 ) N (g kg -1 ) P (g kg -1 ) Lignin (%) Polyphenols (%) Ash (%) (5.8) 8.73 (0.6) 1.2 (0.0) 6.9 (0.2) 1.1 (0.1) 12.1 (0.4) (5.9) 7.4 (0.3) 0.9 (0.0) 1.6 (1.4) 0.8 (0.1) 12.1 (0.4) (7.8) 8.9 (1.3) 1.3 (0.1) 12.3 (1.7) 1.4 (0.8) 12.1 (0.4) (3.1) 7.1 (0.5) 1.1 (0.0) 9.7 (1.4) 1.6 (0.4) 11.8 (0.4) (9.3) 7.0 (0.3) 0.9 (0.0) 8.9 (1.4) 1.1 (0.2) 12.5 (0.4) (3.6) 6.5 (0.7) 1.3 (0.1) 10.6 (0.8) 1.0 (0.3) 12.3 (0.4) *Ratio of non-maize stover: maize stover biomass was generally 2:1. Figures in parentheses indicate SE of the mean

82 Cumulative CO 2 -C evolution (% of added C) Groundnut stover Cowdung Rich field biomass 1 part maize stover + 2 parts non-stover biomass Poor field biomass Maize stover only Incubation period (days) Figure 4.3 CO 2 -C release by different organic resources found on farmers fields following 150 days of incubation with soil. Bars indicate least significant differences at p < 0.05

83 SED Total N mineralized (mg N kg -1 soil) Groundnut stover Cowdung Maize stover only Rich field in situ biomass Poor field in situ biomass 1 part maize stover + 2 parts non-stover biomass mixture Biomass type Figure 4.4 Total mineralizable N (NH 4 + -N + NO 3 - -N) from different quality organic resources found on farmers fields following 150 days of incubation with soil. Ratio of nonmaize stover: maize stover biomass was ~2:1.

84 Discussion Major determinants for productive and non-productive fields The separation of rich from poor fields by farmers was consistent with the laboratory indices that included SOC content, texture, available P and ph. The results suggested that farmers criteria in identifying productive and non-productive fields or field sections is inclusive of the major physico-chemical and biological factors influencing crop growth at field-level, and qualitatively reflect laboratorybased indices. This is contrary to the assertion that soil textural properties and soil colour characterise farmers view of soil fertility with the role of other inherent properties rarely being prioritised (Murwira and Mukamuri, 1998; Joshi et al., 2004). Field-level characterization of soil fertility by farmers and researchers were congruent, further suggesting that, in principle, the targeting of soil fertility technologies is unlikely to be limited by farmers capacity to identify target areas within farms. Farmers were able to rank their fields according to productivity despite the general similarity in soils derived from the same parent material. Soils from all the three study areas were derived from granitic parent material (Nyamapfene, 1991) and had similar textural properties, suggesting that the observed soil fertility gradients were more a result of management factors rather than inherent soil properties. Apart from colour differences inherent in the parent material, the major reason why farmers often link soil colour to fertility (Joshi et al., 2004; Mtambanengwe and Mapfumo, 2005), is apparently due to the influence of SOC.

85 61 The significantly higher amounts of SOC in rich than poor fields suggested that organic inputs had been frequently targeted to specific fields (or fields sections), resulting in a gradual build up of SOC and improved fertility status of the soils over time. Differential access to organic inputs by different farmer classes may be the major factor determining the magnitude of SOC in their respective fields, with those fields belonging to Resource-constrained farmers having marginal SOC enrichments. Overall, the small SOC contents for both rich and poor field types and across farmer classes may be attributed to the poor capacity of sandy soils to physically protect soil organic matter from decomposition (Giller et al., 1997). Frequent tillage under continuous cultivation most likely resulted in stabilization of SOC at relatively low levels (Woomer et al., 1994; Six et al., 2002), especially with low rates of organic inputs. Capacity for high carbon storage in soils is particularly dependent on clay and silt contents (Hassink, 1997; Six et al., 2002; Mtambanengwe et al., 2004), and was likely to be limited for the soils used in this study, which had <10% clay. The high concentrations of nutrients such as N, Ca and Mg in the designated rich fields were indicative of improved cycling of a variety of nutrient elements contained in the organic inputs. Available soil P levels of <8 mg P kg -1 soil in all the three study sites suggested that the organic materials used by farmers contained very little recyclable P. The granite derived sandy soils in the study areas are well known for their inherently low P status (Mashiringwani, 1983). While these soils are known to be rich in K-containing feldspars (Nyamapfene, 1991), deficiencies have been shown to occur with continuous cropping of maize particularly under high rainfall conditions such as in Chikwaka (Mapfumo and Mtambanengwe, 1999). Narrower differences in SOC and nutrient status between rich and poor

86 62 fields in Chinyika than in Chikwaka and Zimuto could be attributed to the relatively short history of smallholder cropping in Chinyika. Chikwaka and Zimuto had over 70 years of maize-based smallholder agriculture compared with about 20 years for Chinyika resettlement area. There may therefore have been less time for SOC and nutrient build up in Chinyika. There were also relatively small differences in fertility between rich and poor fields across all farmer classes in Chinyika, providing further evidence that the productive patches within fields or farms arise from differences in management practices which manifest themselves over long periods of cropping (Mtambanengwe and Mapfumo, 2005). High crop yield responses to external inputs cited by farmers as a major criterion for identifying productive fields may be associated with the positive influences of SOC on other soil fertility attributes such as improved soil structure, CEC and moisture retention capacity (Woomer and Swift, 1994; Albrecht et al., 2004) Quantities of in situ biomass available for incorporation Adoption of organic matter use by smallholder farmers in Zimbabwe is relatively high in Zimuto (Nyathi and Campbell, 1993), particularly by Resource-endowed farmers who have enough resources to mobilize and handle organic materials such as maize stover, manure and woodland leaf litter. Efficient collection of maize stover from the cropped fields during the early dry season period by farmers in Zimuto may be the major reason why it contributed only 27% to total in situ biomass in this area compared with 45-51% for the other two study areas. Maize stover is often collected and stored on racks for use as a dry season feed supplement or to provide bedding in kraals in the wet season (Mugwira and Murwira, 1997). This in turn increases the amount of manure available for use the

87 following season. In all areas, high amounts of in situ biomass from the rich fields confirm the relatively high soil fertility status of this field type. 63 Following recommendations by the national extension to apply cattle manure, the most commonly used organic resource in Zimbabwe, at high rates of 37 t ha -1 every four years or 10 t ha -1 every year (Mugwira and Shumba, 1984), farmers have tended to use high application rates for all available organic nutrient resources although the recommended rates are rarely achieved (Mapfumo and Giller 2001). This concentration of large amounts of an organic nutrient resource over small areas, as opposed to applying thinly over relatively large areas, has been reported in other smallholder farming systems in sub-saharan Africa (Smaling et al., 2002). The farmers subsequently concentrate nutrients on such field sections where soils have already become productive, setting steep fertility gradients against the relatively neglected poor fields. This concentration strategy may account for the creation of the designated rich fields (Mtambanengwe and Mapfumo, 2005). A reduction of 30-46% in total in situ biomass from early to late dry season may largely be attributed to free-ranging livestock grazing during the dry season. Preferential grazing of maize stover to other forms of biomass may explain why reduction in its biomass was more than 50%. Results from this study also suggest that farms belonging to the relatively wealthy Resource-endowed farmers represent zones of nutrient accumulation. This group of farmers generally has adequate draught power and they are therefore able to capture about t ha -1 of biomass through early dry season winter-ploughing. Winter-ploughing is a common practice among farmers with access to draught power, and is aimed at

88 conserving soil moisture and reducing weed pressure during crop establishment phase in the following growing season (Agritex, 1985). 64 Livestock play an important role in the transfer of nutrients, not only between the arable and grazing sub-systems (Swift et al., 1989), but also across farms. The biomass lost through grazing from Resource-constrained farmers fields is likely to benefit Resource-endowed and Intermediate farmers who own cattle through manure application. The general gradient of both SOC and in-situ biomass across farmer classes showed that Intermediate farmers may be representative of a transitional group in terms of organic matter and general soil fertility management. Detailed monitoring of this group could therefore provide insights on the dynamics of technology adoption Carbon contributions and nutrient release from in situ biomass The amounts of in situ biomass measured were less than a third of the estimated 10 t ha -1 required to effect a significant increase in SOC in tropical soils (Palm et al., 2001a). What still remains unclear is the potential role of such small annual inputs in maintaining the critical levels of SOC required to enhance productivity in these nutrient depleted soils. It is also evident from this study that direct C contribution to soil by maize stover under current management practices is very little. Instead, maize stover is apparently a major nutrient loss pathway from cropped fields, particularly for Resource-constrained farmers who have limited capacity to reclaim these nutrients. On average 1.5 t C, 25 kg N and 5 kg P ha -1 are potentially lost of through maize stover by the end of the dry season, in addition to amounts deliberately removed by farmers through harvests and stover

89 65 collection for livestock. Up to 72% of the N contained in maize stover after harvesting is lost from poor fields by the end of the dry-season period. There is therefore scope for increasing the efficiency with which crop residues are utilized to enhance soil fertility, particularly by Resource-constrained farmers. According to the organic resource quality decision guide (Palm et al., 1997; Palm et al., 2001b), the biomass collected from both field types could be classified as low quality on the basis of their low N concentration. However, the C and N mineralization patterns (Mtambanengwe and Mapfumo, 2005) suggested that in situ biomass was generally of superior quality to maize stover alone. There was a positive net N release by biomass collected from rich fields while maize stover alone and biomass from the poor fields had a net immobilization effect. These findings may suggest that the rich fields are more likely to provide N during early phases in crop establishment than poor fields where immobilization is likely to occur. Flushes of N mineralization at the start of the rainy season following dry conditions (Birch, 1964) could play a significant role in influencing maize growth performance and subsequent yields on sandy soils despite the major challenges associated with management of this N (Chikowo et al., 2003). Work on improved fallow and grain-legume rotations under similar smallholder farming systems in Zimbabwe (Chikowo et al., 2004), suggests that farmers who are able to establish their crops early are likely to achieve high N-use efficiency. In this study, rich fields were typically prioritized with respect to early land preparation and planting of crops.

90 Conclusions The criteria used by farmers to identify and classify fields according to productivity potential is holistic and consistent with laboratory-based scientific indices, implying that farmers criteria could be useful in wide-scale targeting of soil fertility technologies. Manifestation of within-field/farm soil fertility gradients on sandy soils under smallholder farming systems is primarily a function of differential capacity by farmers to manage organic matter farmer which in turn is driven by their resourceendowment. Designated rich fields consistently contain higher levels of SOC than corresponding poor fields (or field sections), apparently due to cumulative effects of applying substantial amounts of organic matter to such specific areas on a regular basis. Organic matter is mobilized from extensive areas within and outside individual farms through processes that discriminate against resource-constrained farmers. Although the potential in-situ biomass inputs measured in both rich and poor fields were apparently too small to influence SOC, loss of potentially recyclable N was significantly higher in poor fields. Management of soil fertility gradients in smallholder farming systems in Zimbabwe will most likely hinge on development of strategies that promote efficient capture of organic matter and recycling of nutrients at both field and farm levels. The key challenge, however, is that of enabling farmers to generate sufficient biomass quantities during each cropping cycle in order to maintain the productivity of rich fields while rehabilitating the nonproductive ones.

91 67 CHAPTER 5 Comparative short-term effects of different quality organic resources on maize productivity under two different environments 5.1 Abstract Major challenges for combined use of organic and mineral nutrient sources in smallholder agriculture include variable type and quality of the resources, their limited availability, timing of their relative application and the proportions at which the two should be combined. This Chapter gives an overview of the nutrient supply capacity to a growing maize crop of five different quality organic resources ranging from high to low quality. The materials sunnhemp (Crotalaria juncea) green manure, calliandra (Calliandra calothyrsus) prunnings, cattle manure, maize stover and pine (Pinus patula) sawdust. The study was conducted on-station on two contrasting soil types namely coarse sand at Makoholi and sandy clay loams at Domboshawa. Each organic resource treatment was applied at low (2.5 t C ha -1 ) and high (7.5 t C ha -1 ) biomass rates at each site. Each plot was sub-divided into two with one half receiving 120 kg mineral N ha -1 against zero in the other. At Makoholi, there was a nine-fold increase in maize grain yield under high application rates of C. juncea over the unfertilized control, which yielded only 0.4 t ha -1. Combinations of mineral N with the leguminous resources and manure resulted in % increase in grain yield against sole fertilizer, implying an increased nutrient recovery by the maize test crop under organic-mineral combinations. Maize biomass measured at 2 weeks after crop emergence already showed treatment differences with biomass yields increasing linearly with soil mineral N availability (R 2 = 0.75). This 2-week maize biomass in turn gave a positive linear relationship (R 2 = 0.82) with grain yield suggesting that early season soil mineral N availability largely determined final yield. For low quality resources of maize stover and sawdust, application of mineral N fertilizer resulted in at least a seven-fold This Chapter has been accepted for publication in a modified formart as: Mtambanengwe, F., Mapfumo, P. and Vanlauwe, B Comparative short-tem effects of different quality organic resources on maize productivity under two different environments in Zimbabwe. Nutrient Cycling in Agroecosystems (in press)

92 grain yield increase compared with sole application of the organic resources. Such nutrient combinations resulted in grain harvest indices of between 44 and 48%, up from a mean of 35% for sole application, suggesting the potential of increasing maize productivity from combinations of low quality resources with mineral fertilizer under depleted soils. At Domboshawa, grain yields averaged 7 t ha -1 and did not show any significant treatment differences and this was attributed to relatively high levels of fertility under the sandy-clay loams during this first year of the trial implementation. Differences in N supply by different resources were only revealed in grain and stover uptake. Grain N concentration from the high quality leguminous resources averaged 2% against 1.5% from sawdust treatments. It was concluded that early season soil mineral N availability is the primary regulatory factor for maize productivity obtainable under poor sandy soils. Maize biomass at 2 weeks is a potential tool for early season assessment of potential yields under constrained environments Introduction Mineral fertilizer use by smallholder farmers in Southern Africa, including Zimbabwe, is severely limited by prohibitive purchasing costs and general lack of availability (Scoones et al., 1996; Quiñones et al., 1997). This has resulted in dominantly low-input agricultural systems, which unfortunately cannot sustain food requirements. In addition, low soil N levels account for continued declines in maize production in the majority of smallholder farms (Woomer and Swift, 1994; Sanchez et al., 1997). Consequently, farmers exploit a variety of organic inputs as alternative or supplementary nutrient sources in order to improve and sustain soil productivity (Mugwira and Murwira, 1998; Mapfumo and Giller, 2001; Giller, 2002). Locally available organic nutrient sources are often added in the form of farmyard manure (Mugwira and Murwira, 1997), leaf litter (Nyathi and Campbell, 1993), crop residues (Campbell et al., 1998; Powell and Unger, 1998), green manures (Giller et al., 1998) or agroforestry tree prunings (Mafongoya and Nair, 1997; Chikowo et al., 2004). However, most of the available organic resources are of medium to poor quality, and there is paucity of information on their potential to build up the fertility status of these soils or influence their short-term productivity.

93 69 Organic resource quality is usually described by the relative concentration of nitrogen (N), lignin and polyphenol in the material, with high-quality resources having high N and low lignin (Heal et al., 1997). These quality parameters form the basis of a Decision Guide for organic N management (Palm et al., 1997, 2001a; Giller, 2000), which gives a step-by-step characterization of organic resource management based on their N, lignin and polyphenol contents. The Decision Guide proposes critical limits of 2.5% N, 15% lignin and 4% polyphenols. On-farm generation of N rich organic inputs for soil fertility improvement includes crop sequences with leguminous plants or biomass-transfer of green manure species. Species of Crotalaria and Mucuna were found to have a greater positive effect on maize yields (Rattray and Ellis, 1952; Kumwenda and Gilbert, 1998). Green manures have the potential to accumulate >200 kg N ha -1 year -1 (Mapfumo, 2000; Giller, 2001) resulting in significant cereal yield increases. Agroforestry tree species like Calliandra calothyrsus are used as soil ameliorants in maize systems due to its high biomass production, high tissue N (Handayanto et al., 1997) and grow well on both poor and fertile soils (Mafongoya and Nair, 1997). Incorporation of crop residues favours short-term N immobilization because of their high C:N ratios but repeated addition of crop residues has been known to increase soil organic matter levels (Nicholson et al., 1997). While it is known that high quality organic inputs release nutrients for uptake by plants in the short-term, information on crop-nutrient interactions necessary for maximizing N availability and N-use efficiency by crops under low to medium quality organic resource management is only beginning to emerge (Giller, 2002; Vanlauwe et al., 2002a). Such an understanding of nutrient release dynamics will

94 70 enable smallholder farmers to manage the different quality organic resources in a manner that optimises nutrient uptake and plant productivity. It is therefore imperative that a scientific understanding of how repeated applications of organic resources of the same quality impact on the short- to long-term fertility status of the soils is developed. This chapter gives an evaluation of the effects of organic resource quality and quantity on maize productivity and fertilizer use efficiency of different organic C sources. Specific objectives were to: i. determine how maize productivity is influenced by different organic resources applied at different C rates, varying organic resource quality and combined effect of mineral N fertilizer and organic resource quality/quantity; ii. assess the influence of organic resource quality on maize productivity under two soil types and different rainfall regimes. 5.3 Materials and methods Organic resource selection and characterization The study was conducted on-station sites at Domboshawa Training Centre and Makoholi Research Station (see Chapter 3). Soils at Domboshawa were sandy clay loams while those at Makoholi were coarse sands (see Table 3.3). The field experiment was part of a long-term trial established in 2001 in collaboration with Tropical Soil Biology and Fertility s Institute of CIAT (TSBF- AfNet). The study was aimed at investigating the influence of continuous and repeated application of different quality and quantities of organic resources on SOM dynamics (Mapfumo et al., 2001a). Five different quality organic resources, four of which conformed to the

95 71 four categories identified in the Decision Guide for organic N management (Palm et al., 1997; Giller, 2000), were broadcast and hand-incorporated to a depth of about cm at the Domboshawa and Makoholi experimental sites about two weeks before planting a maize (Zea mays L.) test crop. The materials were: i. Crotalaria juncea (crotalaria) green manure - high quality with N >2.5%, lignin <15% and polyphenols <4% ii. Calliandra calothyrsus (calliandra) prunings - medium quality with N >2.5%, lignin >15% and polyphenols >4% iii. maize stover - low quality with N <2.5%, lignin <15% and polyphenols <4% iv. Pinus patula sawdust (sawdust) low quality with N <2.5%, lignin >15% and polyphenols <4% (Table 5.1). v. The fifth organic fertilizer was cattle manure, a common soil amendment used by many smallholder farmers which, because of variability in quality, does not generally conform to Decision Guide (Murwira et al., 2002). Laboratory analysis showed that the manure used for the study was of medium quality with N <2.5%, lignin <15% and low polyphenol contents of <4%. The C:N ratios of the different materials ranged from 14 for crotalaria to 163 for sawdust (Table 5.1) Generation of organic resources During the cropping season, crotalaria and a short-season maize hybrid cultivar SC 513 (140 days to maturity) were planted at Domboshawa and Makoholi. At flowering, crotalaria was harvested and air-dried in the shade away from direct sunlight to maintain optimum tissue N contents. The maize crop was allowed to reach physiological maturity before harvesting.

96 Table 5.1 Quality of organic resources at time of field incorporation at Domboshawa and Makoholi experimental sites Organic resource type N C C:N Lignin Polyphenol % % Crotalaria juncea green manure Calliandra calothyrsus prunings Zea mays stover Pinus patula sawdust Cattle manure (Domboshawa) Cattle manure (Makoholi) Both crotalaria and mature maize stover were chopped into pieces ranging between 15 and 25 cm before incorporation. Calliandra prunings were acquired from the World Agroforestry Centre (ICRAF) sites at both Domboshawa and Makoholi. Cattle manure was acquired locally at each site as each of the respective sites have a livestock component. The manure was heap stored for four months before field application, as is the local practice among many Zimbabwean smallholder farmers, before incorporation. Pine sawdust was collected from a sawmill in Marondera, about 75 km east of Harare Field layout and experimental treatments Each of the five organic resources described above was applied at two carbonbased rates of 2.5 t C ha -1 (low rate) and 7.5 t C ha -1 (high rate). Plots receiving each of these treatment levels, including a non-amended control, were split into two, with one half receiving 120 kg N ha -1 while the other received no mineral N fertilizer. The experiment was a split plot design with mainplots allocated to organic resource quality x C application rate and sub-plots to the two mineral N

97 fertilizer levels. Each mainplot measured 12 x 6 m 2 and subplot measured 6 x 6 m 2. Each treatment was replicated three times at each site. 73 All plots received a blanket basal application of P and K at 16 kg P ha -1 and 15 kg K ha -1 prior to planting a maize test crop in line with the area recommended rates. The maize test-crop was planted on 11 December, 2002 at Domboshawa and on 17 December, 2002 at Makoholi, soon after the first effective rains that marked the beginning of the cropping season. An early maturing cultivar (SC 401) was planted under low rainfall at Makoholi while a medium maturing cultivar (SC 513) was planted at Domboshawa. A spacing of 0.3 m within rows and 0.9 m between rows was used. Two seeds were planted at each station, and the seedlings thinned to one per station at 2 WAE. The maize was kept weed-free through hand hoeing. 120 kg N ha -1 in Ammonium nitrate form (34.5% N) was applied in three splits. The first split was applied at 2 weeks after crop emergence (WAE) (30% of total) followed by 40% at 6 WAE and finally the last 30% was applied at 9 WAE when the maize was silking. At 6 WAE, the maize crop was treated for maize stalk borer (Buseola fusca) using Kombat (2.5% Carbaryl) at 3-4 kg ha -1. Maize shoot biomass and grain yield determinations were made from a net plot measuring m 2 for each sub-plot. Maize biomass yields were determined (i) during thinning at 2 WAE before the first split of mineral N application, and (ii) at the end of the season during which grain and stover yields were also determined. Grain yield was calculated at 12.5% moisture content. Grain harvest index was calculated in terms of grain yield expressed as a percentage of the total shoot biomass.

98 Mineral N dynamics Soils from the different treatments were collected from a depth of 0-20 cm for mineral N (NH + 4 -N and NO - 3 -N) determination at approximately four weeks after organic resource incorporation. Sampling was done before application of mineral N fertilizer at 2 WAE. Soil samples were collected from at three points within each subplot, using an auger, before a composite sample was drawn for analysis. The composite samples were put in airtight polythene bags and stored at 4 C prior to extraction with 1M KCl within two days of sampling. In the laboratory, 10 g of field moist soil were weighed into a 100 ml container for extraction with 50 ml of 1M KCl. The soils were shaken on an end-over-end shaker for one hour, centrifuged and the clear supernatant transferred into a new set of 100 ml plastic containers. Another subsample of 25 g soil was placed in an oven at 105 C for 24 hours to determine the soil moisture content at the time of sampling. Both NH + 4 -N and NO - 3 -N were determined colorimetrically using a UV- visible spectrophotometer, Shimadzu BioSpec Model Ammonium-N was determined using the phenate method while quantification of soil NO - 3 -N was done through the NO - 2 -N cadmium reduction method as described by Keeney and Nelson (1982). Total plant available mineral N was calculated as the sum of NH N and NO - 3 -N Data analysis Data were analyzed by analysis of variance and mean comparisons on the effects of the five organic resources with and without mineral N applications on maize yield were done using Genstat for Windows Discovery Edition 1 (2003). Regression analyses were carried out to determine relationships between (i) early

99 mineral N availability and maize biomass at 2 weeks after crop emergence, and (ii) maize biomass at two weeks after crop emergence and final grain yield Results Influence of organic resource quality and quantity on maize productivity Treatment effects on maize productivity were already apparent within two weeks of crop emergence at both sites, with yields ranging between 4-18 kg ha -1 at Makoholi and 7-31 kg ha -1 under high rainfall at Domboshawa. Increasing organic resource application rates from 2.5 to 7.5 t C ha -1 significantly improved maize productivity by over 50% for Crotalaria and Calliandra treatments at Makoholi. During the same period, maize biomass yields under maize stover and sawdust treatments were depressed by between 14% (low rate maize stover) and 27% (low rate sawdust) against the control. Overall, maize productivity during this early growth phase increased linearly with soil mineral N availability at both Makoholi (R 2 = 0.75) and Domboshawa (R 2 = 0.61) (Figure 5.1). At Makoholi, maize biomass at 2 WAE following calliandra and crotalaria were % higher than the control. Early season mineral N availability was highest under the high rate crotalaria treatment, with about 20 mg N kg -1 soil in the top 20 cm of the soil profile four weeks after biomass incorporation at Makoholi. The remainder of the treatments mineralized <12 mg N kg -1, with the least amounts of plant available N being found in soils under sawdust, maize stover and control treatments (Figure 5.1).

100 76 40 a) Makoholi Y = 1.7x R 2 = y = x + 4 R 2 = Maize biomass at 2 weeks after emergence (kg ha -1) b) Domboshawa Y = 0.6x R y = 0.6x + 15 R 2 = Soil mineral N (mg kg -1 soil) 2.5 t C ha -1 Crotalaria juncea 7.5 t C ha -1 Crotalaria juncea 2.5 t C ha -1 Calliandra calothyrsus 7.5 t C ha -1 Calliandra calothyrsus 2.5 t C ha -1 Maize stover 7.5 t C ha -1 Maize stover 2.5 t C ha -1 Sawdust 7.5 t C ha -1 Sawdust 2.5 t C ha -1 Manure 7.5 t C ha -1 Manure Control Figure 5.1 Relationship between soil mineral N availability (before mineral N fertilizer application) and a 2 week-old maize crop biomass at Makoholi (a) and Domboshawa (b) under different quantities and quality organic resources The same pattern was observed at Domboshawa, although the magnitude of differences in maize biomass yields among treatments was low. High application rates of Crotalaria gave at least 60% more biomass than the control, and soil

101 77 mineral N availability in the top 20 cm of the profile under this treatment averaged 25 mg N kg -1 soil within four weeks of biomass incorporation (Figure 5.1). The rest of the treatments mineralized between 6 and 16 mg N kg -1 soil during the same period, except sawdust and high rate maize stover which had <4 mg N kg -1 soil. This could partly explain the low yield recorded under these treatments. Both resource quality and application rate had a significant (p< 0.001) effect on maize grain and total biomass yield at Makoholi. Grain yields ranged from 0.1 t ha -1 under sawdust treatments to 4.1 t ha -1 under high rate Crotalaria plus mineral N fertilizer (Table 5.2), and the respective biomass yields ranged between t ha -1. Addition of mineral N fertilizer to the high rate Crotalaria treatment only resulted in a 14% increase in maize grain yield compared with a more than tenfold increase under sawdust treatments. In comparison with the control, high rate crotalaria gave a yield increase of >800% while sawdust application resulted in an apparent grain yield loss of >60%. Grain harvest indices (GHI) under the different treatments ranged from 27% in the unfertilized control to 56% under Crotalaria at Makoholi. This suggested a wide variability in relative contributions by the different quality materials towards the grain yield component. In contrast, there was little variability in GHI at Domboshawa ranging from 44 under maize stover (unfertilized) to 59% under the N-fertilized control (Table 5.2). Overall, it was apparent that application of mineral N improved GHI for all the treatments at Makoholi, but there were no clear trends at Domboshawa probably due to the minimal benefits of the applied N fertilizer.

102 Under relatively high rainfall at Domboshawa, similar maize grain yield patterns were observed although there were no significant treatment differences. Total 78 maize biomass yields only ranged between 14 and 18 t ha -1 for the different treatments with the high quality legumes resources and manure consistently outyielding maize stover, sawdust and control treatments. Lack of treatment differences was attributed to a relatively high background fertility of soils in this first year of cropping. The Domboshawa site had been uncropped for two previous seasons and was being used as a pasture. This form of management could partly explain the high N supply capacity of these soils. Addition of mineral N fertilizer did not result in any significant (p< 0.05) yield differences relative to unfertilized treatments. The highest grain yields of 8.3 t ha -1 were under the high rate manure plus mineral N, while the least was 5.2 t ha -1 under high rate of sawdust combined with mineral N fertilizer (Table 5.2). At both study sites, the final grain yield patterns were reflected in the biomass yields at 2 WAE with regression analysis showing significant linear relationships (R 2 = 0.82) between biomass at 2 WAE and grain yield (Figure 5.2) Relative contributions of different nutrient sources on grain yield Partitioning of treatment effects on grain yield at Makoholi, showed net yield benefits from mineral N fertilizer for all treatments, with low rate manure giving the highest fertilizer returns of up to 1.3 t ha -1 (Table 5.3). There was apparently little additional yield benefit in applying N fertilizer to the high rate Crotalaria treatment, as this accounted for only 3% total yield.

103 Table 5.2 Maize grain yield and harvest index as influenced by organic resource quality and application rate under contrasting environments 79 Treatment Biomass application rate N application rate Makoholi (Mean annual rainfall < 650 mm) Domboshawa (Mean annual rainfall > 750 mm) (t C ha -1 ) (kg ha -1 ) Grain yield (t ha -1 ) GHI* (%) Grain yield (t ha -1 ) GHI* (%) Crotalaria juncea Calliandra calothyrsus Maize stover Pinus patula sawdust Cattle manure Control n/a n/a SED 1 SED 2 n/a n/a n/a n/a * - Grain Harvest Index; SED = Standard error of the difference between means for 1 Mineral N fertilizer effects, and 2 Organic resource quality

104 80 4 a) No mineral fertilizer N addition 3 Y = 1.1x R 2 = Grain yield (t ha -1 ) b) Plus 120 kg N ha -1 Y = 0.9x R 2 = Maize biomass at 2 weeks after emergence (kg ha -1 ) 2.5 t C ha -1 Crotalaria juncea 7.5 t C ha -1 Crotalaria juncea 2.5 t C ha -1 Calliandra calothyrsus 7.5 t C ha -1 Calliandra calothyrsus 2.5 t C ha -1 Maize stover 7.5 t C ha -1 Maize stover 2.5 t C ha -1 sawdust 7.5 t C ha -1 Sawdust 2.5 t C ha -1 Manure Control 7.5 t C ha -1 Manure Figure 5.2 Relationship between maize productivity at two weeks after emergence and final grain yield under low rainfall at Makoholi (a) with no mineral fertilizer N addition and (b) plus 120 kg N ha -1.

105 81 Mineral fertilizer effects were more significant under low rate organic resource application compared to higher application rates of the same quality resources. At these low rates, more than 50% of total yield attained under medium to low quality resources was apparently due to mineral N fertilizer effects, against 27% for the high quality crotalaria. In contrast, mineral N fertilizer accounted for mere 3 to 16% of total yield under high organic resource application (Table 5.3). Irrespective of application rates, organic x mineral N fertilizer interaction apparently depressed potential grain yield for both high quality (crotalaria) and low quality (sawdust) treatments. Pronounced positive effects were only revealed under the medium quality resources. For instance, calliandra, low application rates of manure and maize stover exhibited positive benefits from the organic x mineral N combination effects (Table 5.3). Contrary to the patterns observed at Makoholi, mineral N fertilizer addition had a depressive effect on yield across all treatments under the relatively fertile soils at Domboshawa. Potential yield losses of > 6 t ha -1 were apparent for all treatments except low rate sawdust with an apparent loss of only 0.7 t ha -1. The true mineral N fertilizer effects as measured in the control only accounted for 8% of total yield (Table 5.3). The results suggested that yield gains were attainable with sole applications of medium to high quality organic resources. The organic x mineral N interaction effects were only positive for low rate crotalaria and high rate manure where they contributed 3 and 8% of total yield respectively (Table 5.3).

106 Table 5.3 Relative contribution of mineral fertilizer and organic x mineral fertilizer interaction effects to maize grain yield as influenced by organic resource quality under different environments 82 Treatment Makoholi Yield benefits (kg ha -1 ) Domboshawa 2.5 t C ha t C ha t C ha t C ha -1 Crotalaria juncea Mineral fertilizer effects Interaction effects Calliandra calothyrsus Mineral fertilizer effects Interaction effects Manure Mineral fertilizer effects Interaction effects Maize stover Mineral fertilizer effects Interaction effects Pinus patula sawdust Mineral fertilizer effects Interaction effects True fertilizer effects 3 Control Mineral fertilizer effects = Apparent fertilizer effects: (Organic plus mineral N fertilizer treatment sole organic treatment) 2 Interaction effects = [Organic plus mineral N fertilizer treatment (true fertilizer effects - true organic treatment) unamended control] 3 True fertilizer effects = (Fertilizer treatment control)

107 Nitrogen uptake patterns Contrary to grain and biomass yields, N uptake in grain and stover showed significant treatment effects at Domboshawa. Carbon application rate, N level and organic resource quality all had a significant effect on grain and stover N contents. Notable was the highly significant (p < 0.001) effect of organic resource quality on maize N quality (Table 5.4). Table 5.4 Statistical significance of organic and mineral nutrient sources on maize and stover N quality at Domboshawa Source of variation Grain N Stover N Organic resource quality C rate 1 N level 2 Organic resource quality x C rate Organic resource quality x N level C rate x N level Organic resource quality x C rate x N level *** ** * * ns ns ns *** ** *** * ns ns ns 1 Carbon application rate (2.5 and 7.5 t C ha -1 ) 2 Mineral N fertilizer level at 0 and 120 kg ha -1 *** - p < 0.001; ** - p < 0.01; * - p < 0.05; ns not significant at p < 0.05 Maize grain from higher quality organic resource treatments had superior grain N concentration compared to that from low quality resources. For example, a mean of 2.1% grain N for high rate crotalaria compared with 1.5% N for sawdust (Table 5.5). High application rates of medium to high quality resources improved the grain N concentration by as much as 10%. The highest increase in stover N concentration of ~ 25% was under cattle manure. However, there was no

108 significant difference between the two C application rates with respect to grain and stover N contents under sawdust, maize stover and control treatments (Table 5.5). 84 Table 5.5 The effect of organic resource quality and quantity of application (carbon basis) on maize grain and stover N concentration at Domboshawa in Zimbabwe Organic resource quality Grain N (%) Stover N (%) 2.5 t C ha t C ha t C ha t C ha -1 Crotalaria juncea Calliandra calothyrsus Manure Maize stover Pinus patula sawdust SED SED Standard error of the difference of means Mineral fertilizer addition increased the N concentration of both grain and stover under the different treatments. The N fertilizer effect was more pronounced in stover than grain (p < 0.001). On average, grain N was increased from 1.72 (0.02) to 1.78 (0.02) % N under mineral N fertilization. Without N fertilization, the maize stover had about 11% less N than under N fertilization. Total plant N uptake gave a significant linear relationship with grain yield from both N-fertilized (R 2 = 0.66) and unfertilized treatments (R 2 = 0.74) (Figure 5.3). Between 140 and 260 kg N ha -1 was accounted for in total plant N uptake under the N-fertilized treatments revealing a wider separation of treatment effects compared to only 140 and 200 kg N ha -1 under sole application. This implied an

109 85 9 With N Y = 1.9x R 2 = 0.66 Maize grain yield (t ha -1 ) Without N Y = 1.5x R 2 = Total maize N uptake (kg N ha -1 ) Crotalaria juncea Calliandra calothyrsus Maize stover Sawdust Manure Control Crotalaria juncea + N Calliandra calothyrsus + N Maize stover + N Sawdust + N Manure + N Control + N Figure 5.3 Relationship between maize total N uptake and grain yield under high rainfall conditions at Domboshawa. (Larger symbols of the same shape denote high biomass application rates of 7.5 t C ha -1 (versus 2.5 t C ha -1 ) for the same organic resource. Solid symbols denote mineral N fertilized treatments) apparent high plant-n utilization under N fertilized treatments (a slope of 1.9) compared to unfertilized treatments (a slope of 1.5) (Figure 5.3). However, more efficient uptake of plant-available N appeared to be under unfertilized treatments as there was potentially 47 kg grain kg -1 N taken-up under poor quality resource

110 and 35 kg grain kg -1 N under high quality Crotalaria. Corresponding values were 42 and 31 kg grain kg -1 N uptake under fertilized treatments (Figure 5.3) Discussion Maize productivity following organic resource incorporation primarily hinged on early season N-supply capacity of the different nutrient sources. Significant responses in maize biomass evident as early as two weeks after crop emergence indicated high N requirement by maize during early growth phase (Oikeh et al., 1996). The study suggests that it is this early and consistent supply of N that determines grain yield, as was revealed by a significant relationship between biomass at 2 weeks after crop emergence and final yield. It was apparent that without fast-n-releasing or high quality organic inputs or mineral fertilizer, biomass accumulation by maize is severely compromised, particularly under sandy soils such as those at Makoholi. Unfortunately, much of arable farmland on smallholder farms are typically sandy and inherently contain low amounts of soil organic matter (Grant, 1981; Giller et al., 1997). External nutrient supplementation, particularly N, govern crop production on these soils. Soil mineral N availability could be explained by both the quality and quantity of the different organic resources added, which contained variable amounts of readily mineralizable N. The high performance of maize under Crotalaria could be attributed its rapid decomposition and mineralization due to a narrow C:N ratio. The relative proportion of these elements has traditionally been widely accepted as a major determinant of short-term N release patterns (Iritani and Arnold, 1960, Swift et al., 1979; Frankenberger and Abelmagid, 1985).

111 87 Research over the last one and half decades has however, included lignin and polyphenol contents as key modifiers governing N mineralization/ immobilization patterns from different quality materials (Palm and Sanchez, 1991; Constaninides and Fownes, 1994; Mafongoya et al., 1998). Still, the robustness of the C:N ratio over lignin content in predicting N release from organic materials was implied under medium to high quality calliandra which yielded at least nine-fold against the control. Any immobilization likely to emanate from the highly lignified Calliandra, which was way above the critical level of 150 mg kg -1 (Palm et al., 1997) was not evident, suggestive of the dominance of other resource quality modifiers other than lignin and polyphenols. Lack of significant interactions between mineral N fertilizer and with neither organic resource quality nor biomass application rate means that mineral fertilizer had additive effects with the different quality organic resources. Partitioning of treatment effects on maize yield at both Makoholi and Domboshawa showed marginal positive to negative yield benefits following addition of mineral N to either high or low quality organic resources. While possible short-term consequences of such nutrient combinations may negatively impact on the final yield realized, it was assumed that the mechanisms responsible for this reduction at the two extremes of the organic quality scale might be completely different. For example, consistently poor maize productivity observed under low quality resources throughout the season might be attributed to a low tissue N concentration of the materials, which was three and eight times below the critical level of 2.5% (Palm, 1995). Addition of 120 kg N ha -1 to these treatments probably did not raise the C:N ratio enough to offset immobilization as maize grain yield continued to be lower than that of the control, particularly under high organic

112 88 resource application rates. Conversely, addition of mineral N to high quality resources may have resulted poor N utilization by the maize crop due to excessive N loading and resultant leaching. Analysis of the grain from the different treatments however, revealed that much of the N taken up is channelled towards the grain, and the grain quality increases with mineral N addition or application of medium to high quality materials. An apparent 10% decrease in grain yield realized from every kilogram of N taken up under mineral N fertilized compared to unfertilized treatments may imply that an enhanced N pool does not necessarily mean high yield. High N availability at early crop growth stages has been deemed undesirable as this promoted luxuriant vegetative growth (Nandwa and Chege, 1996) at the expense of cob development. Plant N quality analysis displayed differential effects of N source between stover and grain in the short-term. For instance, the influence of organic resource quality and mineral N addition was more pronounced on stover than grain. The N uptake results suggest that changes in nutrient sources manifest themselves in stover before they can be picked up in grain. However, these results are not conclusive as other factors such as crop hybrid type, soil and environmental conditions affect nutrient patterns (Ojiem et al., 1996). Grain yield results from Domboshawa revealed that an N uptake of about 160 kg N ha -1 (under low quality resources) could result in grain yields of up to 7 t ha -1 suggesting N dilution by the maize crop (Janssen et al., 1990). In comparison, yield increments of <1 t ha -1 were realized under twice the amount of N taken-up under higher quality organic resource treatments. This means that under relatively

113 fertile soils such as those at Domboshawa, substantial maize productivity can be obtained with minimum N management in short-term. 89 The general lack of treatment differences at Domboshawa was attributed to a relatively high background fertility of the sandy clay loam soil during this first year of trial. For instance, grain yield increased only 14% following addition of 540 kg N ha -1 in crotalaria biomass. Conversely, application of lignified sawdust depressed yields by only 5% against the control. These patterns suggest that there was probably enough mineral N in the Domboshawa to offset any immobilization that might be caused by low quality materials such as maize stover and sawdust. Preseason analysis of the Domboshawa soils indicated a potential N release capacity of >50 kg N ha -1 within one season. Such amounts would also exclude any significant chances for responses to external addition of high quality N sources in short-term. Under semi-arid conditions at Makoholi, mineral N combinations with low quality resources improved grain harvest indices from <0.35 under the control to >0.45. Such management option implies that if farmers in low potential environments combine mineral N fertilizer with low quality organic resources which are often more readily available compared to higher quality resources, they may be able to significantly increase crop productivity. Nitrogen uptake was more efficient under low N conditions. While use of mineral N fertilizer is not widespread particularly under semi-arid environments of Zimbabwe since it is considered a risky investment because of unpredictable weather (Mapfumo and Giller, 2001), farmers need exposure to such technologies in order to maximize crop productivity and hence food security.

114 90 Defining manure quality and predicting nutrient release dynamics for arable use has always been problematic due to variability in origin and handling. Contrary to previous findings that manure with a C:N ratio of >23 delays net N release (Murwira and Kirchmann, 1993a), significant biomass and yields attained under manure treatment (C:N < 23) which was of medium quality. Vanlauwe et al., 2002b argue that manure possible has multiple roles other than supplying N in crop productivity. Some mineralization studies (Olsen, 1986) have shown that N release from manure is low but can persist throughout the maize growth period. Thus, the high yields attainable under manure plus N-fertilizer treatments were probably due to an enhanced available N pool. Overall, use of organic resources did make a difference on maize productivity particularly on poor sandy soils, thus management strategies that favour the promotion of organic matter application to arable lands on predominantly sandy soils. 5.5 Conclusions Maize productivity was governed by N availability with an early supply of N crucial role in crop establishment, plant vigour and, therefore, final yield. A two-week maize crop can be used to estimate grain yield under normal seasons. High quality materials like Crotalaria can be used directly as an N source under maize-based systems with increased nutrient use efficiency at higher rates. For low quality organic resources, low application rates gave higher grain yields compared to high rates due to a shortened N immobilization phase. It was concluded that cattle manure used was of intermediate quality and lies between maize stover and Calliandra. The N release capacity of low quality resources can be enhanced by adding mineral N fertilizer, a management option which may be desirable to smallholder farmers who characteristically have access to little amounts low

115 91 quality organic nutrient sources. However, the nature of added benefits realized through combinations of the two nutrient sources still needs further investigation. While these findings conform to the Decision Guide for organic N management, the likely long-term effect of repeated applications of high amounts of high quality (high N) organic resources remain a challenge.

116 92 CHAPTER 6 Differential effects of organic resource quality on soil profile N dynamics and maize yields on sandy soils in Zimbabwe 6.1 Abstract This Chapter focuses at determining the differential N supply effects of different quality and quantities of organic nutrient sources on maize productivity. Optimising the use efficiency of nitrogen (N) derived from different quality organic resources and mineral fertilizers on sandy soils with <100 g clay kg -1 is a major challenge for smallholder farmers in Southern Africa. Crotalaria juncea, Calliandra calothyrsus, cattle manure, maize stover and Pinus patula sawdust which represented high to low quality materials respectively, were each incorporated into soil at 1.2 t C ha -1 and 4 t C ha -1 at Makoholi Research Station and tested against a sole mineral N fertilizer and non-amended control treatments. Commonly available organic materials, including manure and composted miombo leaf litter, applied in varying amounts by farmers were evaluated under different rainfall zones in Zimuto, Chinyika and Chikwaka. Nitrogen release patterns were consistent with differences in resource quality. At three weeks after incorporation into soil at the onset of the rains, C. juncea and C. calothyrsus had released as high as 24 and 13 % of added N respectively, compared with no more than 5-6% for the rest of the amended treatments. Most of the N released was lost through leaching as evidenced by progressive movement of NO 3 - -N bulges beyond maize rooting depth following major rainfall events. Maize yields were significantly related to the size of profile mineral N fluxes, with the best linear relationship (R 2 = 0.88) obtained with N available in the top 30 cm of soil at maize flowering. High grain yields of ~ 3 t ha -1 were only achieved with C. juncea applied at 4 t C ha -1, which also had highest NO 3 - -N leaching losses. Conversely, the same application rate increased N immobilization by 30 and 42% under maize stover and sawdust respectively, relative to the control. A modified version was accepted as: Mtambanengwe, F. and Mapfumo, P Effects of organic resource quality on profile N dynamics and maize yields on sandy soils in Zimbabwe. Plant and Soil 281:

117 Apparent N use efficiency was highest under sole mineral N fertilizer application averaging 11 kg grain kg -1 N added while all the organic resource treatments yielded <7 kg grain kg -1 N added. Results from farmers fields showed that organic resources traditionally used on smallholder farms are invariably of low quality relative to C. juncea and C. calothyrsus. However, they exhibited shorter N immobilization effects than was shown for maize stover and sawdust at Makoholi, suggesting that pre-application treatments, such as composting, employed by farmers enhance seasonal N benefits from these materials. Maize yields increased linearly with total N added in these resources in combination with N fertilizer, justifying the high organic matter loading strategy (e.g. > 20 t ha -1 for manure, fresh litter and composted litter) used by farmers who often achieve high crop yields on such coarse sandy soils in Zimbabwe Introduction Efficient nitrogen (N) management is arguably the most challenging aspect of tropical smallholder agriculture in sub-saharan Africa including Zimbabwe (Chikowo et al., 2004a; Giller, 1997). Mineral fertilizer use in smallholder cropping systems remains insufficient to meet crop N demand on a sustainable basis, partly because of prohibitive costs and/or lack of availability. Organic resources are used as alternative nutrient sources or in combination with mineral fertilizers, but their quantities are also severely limited. Although organic and inorganic combinations are, in principle, more beneficial than sole applications (Grant, 1967; Palm et al., 1997), the nature and levels of the combinations are seldom a matter of choice as the main determining factor is availability (Mapfumo and Giller, 2001). This therefore compromises the efficiency with which the various nutrient resources are utilized. Most of the organic resources available to smallholder farmers are generally of poor quality and are therefore poor sources of N (Grant, 1967; Palm et al., 2001). Consequently, their beneficial utilization by farmers in the short-term requires additional application of mineral forms of N. On the other hand, high quality organic resources (e.g. leguminous materials) which mineralise over short period

118 94 of about 3-4 weeks after incorporation, present management problems associated with high nutrient losses, especially N (Nyamangara et al., 2003; Chikowo et al., 2004a). Achieving optimal levels of nutrient use efficiency, particularly N, under these circumstances is therefore a major challenge for soil fertility research. Soil textural properties determine soil organic matter (SOM) stabilization and it is this stabilized SOM, which usually serves as a sink and source for plant nutrients (Duxbury et al., 1989; Oades, 1984; Six et al., 2002). Sandy soils, such as those predominant in Southern Africa, invariably contain a small amount of SOM because of their lack of capacity to protect organic matter from microbial degradation under climatic conditions that promote high turn over rates (Giller et al., 1997). However, the predominantly resource-constrained farmers in these farming systems still rely, to a greater extent, on nutrients mineralised from these small amounts of SOM to sustain crop productivity (Mapfumo and Giller, 2001). There is, hence, an increasing focus on the potential roles of different quality organic resources in influencing both short- and medium-term nutrient availability, especially N. Understanding the influence of such processes on potential N availability from different nutrient sources will assist in enhancing the efficiency of N management. This should culminate with a formulation of management strategies that minimize N losses on smallholder farms, particularly for nitrate-n leaching which remains a major challenge on sandy soils. For instance, high quality legume biomass from improved fallow systems showed early season nitrate-n leaching losses exceeding 20 mg NO - 3 -N kg -1 soil within nine weeks of maize growth on a sandy soil (Chikowo et al., 2004a).

119 95 The development of an organic resource database for organic resources quality (Palm et al., 2001) paved the way for strategic manipulation of organic inputs on smallholder farms. However, empirical evidence on how the quality and quantities of such resources impact on soil profile N dynamics and crop yields, is only beginning to emerge. Such a quantitative understanding will enhance efficiency of nutrient use and increase investment returns to mineral fertilizer use. The purpose of this study was to characterize the different organic nutrient resources under smallholder farming systems and determine their N supply characteristics in relation to soil profile N changes and maize productivity on sandy soils. Specific objectives were to: i. Determine the effect of application of different quality organic resources on soil mineral N availability and maize yields ii. Monitor and quantify NO 3 - -N and NH 4 + -N movements in sandy soil profiles following application of different quality organic resources in varying quantities iii. Characterize organic resources available for use on smallholder farms according to quality as reflected by N supply potential to maize 6.3 Materials and Methods Experimental treatments and management on-station The study was carried at Makoholi Experimental Station and at three on-farm sites in Chikwaka, Chinyika and Zimuto Communal Areas (Chapter 3). The field experiment at Makoholi was established in November 2002 as part of a long-term trial aimed at investigating the influence of continuous but repeated application of

120 96 different quality and quantities of organic resources on soil organic matter dynamics (Mapfumo et al., 2001a). Five different organic resources ranging from high to low quality were applied at two carbon rates of 1.2 and 4.0 t C ha -1. Subsamples of the organic materials were milled to pass through a 1 mm sieve and analysed for total C, N, P and lignin (Anderson and Ingram, 1993). Total soluble polyphenols were also measured using the Folin-Denis method (Quarmby and Allen, 1989). The organic materials were hand-incorporated, into plots measuring 6 x 6 m 2 in gross area, using hoes to a depth of 0.15 m at the beginning of the growing season. The treatments were: (i) Crotalaria juncea L.; (ii) Calliandra calothyrsus Meissn.; (iii) Maize (Zea mays L.) stover; (iv) Pinus patula Schiede & Schltdl. & Cham. (v) Cattle manure; (vi) Mineral N fertilizer only; and (vii) Control as described in Chapter 5. The field experiment was a factorial in randomized complete block design with each treatment replicated three times. The plots received the same quantities of the organic resources at the start the cropping season (November) for two seasons, namely 2002/03 and 2003/04. Maize was planted with the first effective rains at a spacing of 0.9 m between rows and 0.25 m within rows and two seed per planting station. Prior to planting of a maize test crop, all the plots had received a basal application of 16 kg P ha -1 and 15 kg K ha -1 following soil analysis. Mineral N fertilizer in the form of ammonium nitrate (AN) was broadcast to all but the control plots at a rate of 120 kg N ha -1 in three splits: 30% at 2 weeks after emergence (WAE); 40% at 6 WAE and 30% at 9 WAE. The high N application rate simulated rates used for maximum maize yield potential in Zimbabwe (Agronomy Research Institute, 2002).

121 97 The maize crop was kept weed-free and received a single application of Dipterex (1% Thiodan) at 3-4 kg ha -1 as protection against stem borer (Busseola fusca Fuller), a common maize pest in the study areas. The first N fertilizer application was done soon after the maize was thinned to one per planting station. During thinning, a sub-sample of ten plants was drawn from within a net plot area (2.7 m x 4 m) and used to determine shoot biomass yield at 2 WAE. The biomass was first air-dried under shade before being oven-dried at 60 C to a constant mass. At maturity, total shoot biomass and grain yields were determined from the net plot. For each treatment, harvested ears (grain + cob) were dried in a green house at about 35 C until the grain moisture content was about 12.5%, after which grain yield was determined. Like the biomass at 2 WAE, the stover oven-dried to constant mass at 60 C following air-drying under shade On-farm experimental treatments and management Farmer-managed experiments were established in the 2003/04 season in Chikwaka, Chinyika and Zimuto smallholder areas using different quality organic resources identified by farmers during participatory workshops (Table 6.1). The materials were sub-sampled for C and N analysis (Anderson and Ingram, 1993) before being broadcast at variable rates as determined by farmers (Table 6.1). All the resources had <15 mg N g -1 except C. juncea (>30 mg N g -1 ) while C:N ratios ranged from 5 in termitaria soil to 56 in maize stover. The C. juncea was included among farmer treatments as a reference.

122 98 Table 6.1 Organic and mineral nutrient sources used as soil amendments by farmers in Chikwaka, Chinyika and Zimuto smallholder farming areas Treatment Chikwaka (>750 mm yr -1 ) Chinyika ( mm yr -1 ) Zimuto ( mm yr -1 ) Application rate (t ha -1 ) C:N Application rate (t ha -1 ) C:N Application rate (t ha -1 ) C:N Cattle manure Composted maize stover Not used n/a Not used n/a Composted woodland litter Not used n/a Not used n/a Compound D* Not used n/a 0.2 n/a Not used n/a Crotalaria juncea Fresh woodland litter Maize stover Not used n/a Mineral N fertilizer 0.2 n/a 0.2 n/a 0.15 n/a Termitaria Not used n/a Dry weight basis; *Compound D (7%N:6%P:7%K: 7%S) applied two-three weeks after crop emergence; n/a = not applicable

123 99 materials were incorporated by hand-hoes to a depth of 0.15 m on plots measuring 4.5 m x 8 m, two weeks prior to planting of a maize test crop. The experiment was a randomised complete block design with three replicates at each of the study sites. All the plots except the unamended controls received a basal application of a local NPKS fertilizer (0%N:32%P 2 O 5 :16%K 2 O:5%S) at 26 kg ha -1 P and 24.5 kg K ha -1 for Chikwaka and Chinyika, and at 18 kg P ha -1 and 17 kg K ha -1 under semiarid conditions in Zimuto. These rates were consistent with local extension recommendations for smallholder farmers (Agronomy Research Institute, 2002). A non-amended and mineral N control treatments were included at each experimental site. Mineral N fertilizer was applied in three splits as earlier described, in the form of AN at 69 kg N ha -1 for NR II and III and 51 kg N ha -1 for the semi-arid NR IV. The maize was planted within two weeks of the start of the rainy season as farmers had their own priority fields relative to experimental sites (Figure 6.1). Plants were thinned to one per planting station at 2 WAE, coinciding with the first weeding and N fertilizer application. At maturity, the maize was harvested from a net plot of 2.7 m (3 plant rows) x 6 m to determine total shoot biomass and grain yields as earlier described Sampling for mineral N dynamics At Makoholi, mineral N dynamics in the soil profile were monitored over seven time periods in response to rainfall (Figure 6.1). Soil sampling was done from 0-15, 15-30, 30-45, 45-60, and cm depths in each plot using corers. The first sampling was done with the first effective rains at the end of November 2003, (T1) about two weeks after incorporation of organic materials, and the last at harvesting (T7).

124 M akoholi Date of incorporation 15/11/2003 Planting date Time 1 soil sampling: 28/11/2003 Tim e 2 soil sam pling 5/12/2003 Tim e 3 soil sam pling: 23/12/2003 Tim e 4 soil sam pling: 27/12/2003 Tim e 5 soil sam pling: 03/02/2004 Time 6 soil sam pling: 01/03/2004 Tim e 6 soil sam pling: 15/03/2004 Time 7 Maize harvest: Maize harvest: 21/04/ /04/ Daily rainfall (mm) Zim uto date of incorporation: 12/12/ 2003 Planting date: 24/12/2003 mid-season soil sam pling: 13/02/2004 end of season soil sampling: 21/04/2004 Maize harvest 28/04/ October Novem ber Decem ber January February March April M ay Time (days) Figure 6.1 Rainfall distribution during the season at Makoholi (total = 647 mm) and Zimuto (total = 659 mm). (Major events during the season are indicated by arrows)

125 101 During each sampling and for all depths, soil was collected from three replicate points within a plot before a composite sample was drawn for analysis. Where possible, a second sampling was done for the same rainfall event (Figure 6.1). All samples were put in airtight polythene bags and stored at 4 C prior to extraction with 1M KCl. All samples were analysed within five days of sampling. Within the farmer-managed experiment at Zimuto, differences in N supply patterns by the various organic resources were captured through two snap-shot surveys of the soil profile N. Composite soil samples were collected from 0-20, 20-40, 40-60, and cm depths, with the first set of samples taken during the midseason period in February (Figure 6.1). The rationale was that definitive N mineralization would have occurred for most of the decomposing organic resources to enable detection of any possible differences. The second sampling was done at the end of rainy season in April, one week before the maize crop was harvested for grain. At each of the Makoholi and Zimuto sites, bulk density measurements were initially taken at the respective sampling depths from representative soil profile pits. Undisturbed soil samples were collected in cores measuring 72 mm in diameter and 50 mm in height. The resultant core samples were weighed for fresh mass and then oven-dried at 105 C to a constant mass for dry mass determination Ammonium-N and Nitrate-N analyses For each test sample, a ten-gram sub-sample was weighed into a 100 ml container for extraction with 50 ml of 1M KCl. The soils were shaken on an endover-end shaker for one hour, centrifuged, and the resultant clear supernatant

126 102 transferred into a new set of 100 ml plastic containers. In parallel, another subsample of 25 g soil was placed in an oven at 105 C for 24 hours to determine the soil moisture content. Both NH + 4 -N and NO - 3 -N were determined by methods described by Keeney and Nelson (1982), with the NO - 2 -N cadmium reduction method used for NO - 3 -N determination and NH + 4 -N determined by the phenate method. In each case, the ionic concentrations were measured colorimetrically using a UV-visible spectrophotometer (Shimadzu BioSpec, Model 1601). Total plant available mineral N was calculated as the sum of NH + 4 -N and NO - 3 -N. Soil bulk densities at corresponding depths were used to quantify NH + 4 -N and NO - 3 -N contents on an area basis Data analyses Statistical analysis was done using Genstat statistical package (Genstat Discovery Edition 1, 2003). Analysis of variance (ANOVA) was used to separate resource quality and application rate effects on maize yields. ANOVA was also used to determine the treatment effects, including soil depth, on soil profile nitrate-n, ammonium-n and total mineral N contents at each sampling time. Relationships between maize shoot biomass and grain yield with soil mineral N availability and organic resource quality were tested using simple linear regression techniques. All mean comparisons were considered significant at P< Results Influence of organic quality and C application rate on soil NH 4 + -N Soil NH 4 + -N concentration was significantly influenced by resource quality, C application rate and soil depth for the different sampling times at Makoholi. There

127 103 was a significant (P<0.01) interaction between resource quality and soil depth. Application rate did not significantly (P<0.05) interact with either resource quality or sampling depth, suggesting that N-mineralization patterns of the different organic resources were generally the same irrespective of application rate. At first sampling (T1) following application of organic resources at 1.2 t C ha -1, the soil NH + 4 -N concentration in the top 30 cm of the soil profile was significantly higher under C. juncea than all other treatments except C. calothyrsus (Figure 6.2a). Calliandra calothyrsus did not differ significantly from manure but was higher than sawdust and maize stover treatments. The NH + 4 -N concentration in plots that had received high quality organic resources increased by 10-20% one week after the first sampling (T2). In contrast, NH + 4 -N changes remained least under maize stover and sawdust treatments (Figure 6.2) despite wet conditions that prevailed between T1 and T2 (see Figure 6.1). After applying the first split of mineral N fertilizer at 2 WAE, there was a significant decrease in topsoil NH + 4 -N release at T3 and T4. At the same time (T3), an NH + 4 -N bulge, which was significantly higher under manure than for all other treatments, was observed in the cm depth of the soil profile (Figure 6.2c). Within five days (T4), the relative position of this bulge had become apparent at cm depth at T4 (Figure 6.2d). Soil NH + 4 -N concentration in the profile decreased gradually as the season progressed showing no significant treatment differences at T5 and T6 (Figure 6.2e&f). However, there was a significant resurgence in NH + 4 -N release under legumes relative to other treatments in the 0-15 and cm depths by the end of the season (Figure 6.2g).

128 Soil ammonium-n (mg kg -1 soil) Soil depth (cm) a) T1 b) T2 c) T3 d) T e) T5 f) T6 g) T7 Crotalaria juncea Calliandra calothyrsus Maize stover Sawdust Manure Mineral N fertilizer Control SED Figure 6.2 Soil NH 4 + -N dynamics under different quality organic resources applied at 1.2 t C ha -1 at Makoholi. T1 to T7 were independent sampling times following a rainfall event between 28 November, 2003 and 21 April, 2005.

129 105 When high biomass application rates (4 t C ha -1 ) were used, similar NH + 4 -N release patterns were observed although the magnitude of treatment effects was significantly higher than at the low rate (1.2 t C ha -1 ). In the top 15 cm of the soil profile, there was a 50% increase in the amount of NH + 4 -N released under C. juncea and C. calothyrsus treatments between T1 and T2 (Figure 6.3), following 38 mm of rainfall (see Figure 6.1). Total amounts of NH + 4 -N measured under C. juncea and C. calothyrsus at T2 averaged about 40 and 23 kg NH + 4 -N ha -1 respectively, compared with <5 kg NH + 4 -N ha -1 under manure, maize stover and sawdust treatments (Figure 6.3b). The control released a significantly higher amount (~ 2 times) of NH + 4 -N than the manure, maize stover and sawdust treatments during the same period (T2). There was a general decline in amounts of NH + 4 -N released as the season progressed, with no significant treatment differences at T5 and T6. However, manure and C. calothyrsus treatments showed a renewed and significant NH + 4 -N release at the end of the cropping season (T7). Amounts of subsoil ( cm) NH + 4 -N increased at T1 and T2, with C. juncea significantly out-performing the other treatments (Figure 6.3a & b). Significantly higher amounts of NH + 4 -N were measured under legumes relative to other treatments at T5, and under manure compared with maize stover, mineral N fertilizer and control treatments at the end of the season (T7).

130 Soil ammonium-n (mg kg -1 soil) Soil depth (cm) a) T1 b) T2 c) T3 d) T e) T5 f) T6 g) T7 Crotalaria juncea Calliandra calothyrsus Maize stover Sawdust Manure Mineral N fertilizer Control SED Figure 6.3 Soil NH 4 + -N dynamics under five different quality organic resources applied at 4.0 t C ha -1 at Makoholi. T1 to T7 were independent sampling times following a rainfall event between 28 November, 2003 and 21 April, 2005.

131 Influence of organic quality and C application rate on soil NO - 3 -N Under low rate of biomass application (1.2 t C ha -1 ), there were no significant treatment differences in soil NO - 3 -N concentration in the top 45 cm at first sampling (T1) following biomass incorporation (Figure 6.4a). Treatment effects in the top horizons only became apparent at T2, three weeks after biomass incorporation. Significantly higher NO - 3 -N levels were found in the top 60 cm of the C. juncea compared to maize stover and sawdust plots (Figure 6.4b). A separation of treatment effects was evident at T3, with C. juncea and C. calothyrsus exhibiting significantly higher concentrations of NO - 3 -N than the sawdust and control treatments at all sampling depths (Figure 6.4c). Sawdust released the least amounts of NO - 3 -N. The increase in soil NO - 3 -N under C. calothyrsus and C. juncea treatments amounted between 9 and 17 kg NO - 3 -N ha -1. The C. calothyrsus treatment had the highest concentration of NO - 3 -N (up to 9.5 mg kg -1 soil) within the top cm, followed by C. juncea with ~6 mg kg -1 soil. Crotalaria juncea plots had the highest soil NO - 3 -N concentration in the top 45 cm at T4. Calliandra calothyrsus also exhibited the highest concentration at depths below 45 cm although this was not significantly different from sawdust and C. juncea treatments. Both C. juncea and C. calothyrsus treatments showed a gradual downward shift of NO - 3 -N bulges with each consecutive sampling from T4 through to T7. There was a sudden increase in soil NO - 3 -N concentration in the cm depth under the mineral N fertilizer treatment at T5, apparently in response to the second split of N applied a week before.

132 108 Soil nitrate-n (mg kg -1 soil) Soil depth (cm) a) T1 b) T2 c) T3 d) T e) T5 f) T6 g) T7 Crotalaria juncea Calliandra calothyrsus Maize stover Sawdust Manure Mineral N fertilizer Control SED Figure 6.4. Soil NO 3 - -N dynamics under different quality organic resources applied at 1.2 t C ha -1 at Makoholi. T1 to T7 were independent sampling times following a rainfall event between 28 November, 2003 and 21 April, 2005.

133 Soil nitrate-n (mg kg -1 soil) Soil depth (cm) a) T1 b) T2 c) T3 d) T e) T5 f) T6 g) T7 Crotalaria juncea Calliandra calothyrsus Maize stover Sawdust Manure Mineral N fertilizer Control SED Figure 6.5 Soil NO 3 - -N dynamics under five different quality organic resources applied at 4.0 t C ha -1 at Makoholi. T1 to T7 were independent sampling times following a rainfall event between 28 November, 2003 and 21 April, 2005.

134 110 The same treatment had the least NO - 3 -N concentration by the end of the sampling period (T7). Apart from the small increases at lower depths, maize stover, sawdust and manure consistently released small amounts of NO - 3 -N with no significant differences among the treatments between T4 and T7 (Figure 6.4dg). Following application of the organic materials at 4.0 t C ha -1, soil NO - 3 -N at T1 and T2 showed trends similar to those observed at low application rates although the amounts were significantly higher. At crop emergence, about 3 weeks after incorporation (T2), the amount of NO - 3 -N in the 0 15 cm layer under the C. juncea treatment was up to 4 times that of the other treatments (Figure 6.5a). For instance, C. juncea plots contained 30 kg NO - 3 -N ha -1 in this top layer compared with 9 kg NO - 3 -N ha -1 under C. calothyrsus. A major difference from the plots receiving low application rates was a high concentration of NO - 3 -N under the manure treatment between T3 and T4. There was also a significant release of NO - 3 -N from the maize stover and manure towards the end of the sampling period (T7). The sawdust treatment consistently exhibited low NO - 3 -N concentration despite additions of mineral N fertilizer to the plots, for instance between T3 and T4. There were apparent differences in the relative movement of NO - 3 -N down the soil profile, with the bulge under the manure treatment ahead of C. calothyrsus, which in turn was ahead of C. juncea (Figure 6.5d-g). During mid-season (T5), there was a significant increase in NO - 3 -N in the lower depths (30 60 cm layers) of up to 38 kg NO - 3 -N ha -1 compared with amounts measured in previous sampling at T4. As

135 111 at low rate of organic matter application, there was a sudden build up in NO - 3 -N concentration at cm depth in the control plots from T4 to T5, and this had reduced to a minimum by T6 (Figure 6.5d-f) Maize productivity in response to organic resource application on-station (Makoholi) Biomass yields at 2 WAE ranged between 8-17 kg ha -1 at low rate (1.2 t C ha -1 ), compared with 7 to 22 kg ha -1 at high application rate (4.0 C t ha -1 ). Treatment effects were already apparent at this stage, particularly under high application rate. Crotalaria juncea had significantly more yield than all treatments except C. calothyrsus (Table 6.2). Legume treatments yielded significantly more maize biomass than the manure and control, which in turn significantly out-yielded maize stover and sawdust, giving three distinct resource categories. At high application rate, C. juncea and C. calothyrsus treatments significantly outyielded maize stover and sawdust by up to 113% (Table 6.2). The control had 38 and 46% more maize biomass than the maize stover and sawdust treatments, respectively. At maturity, C. juncea significantly out-yielded all other treatments in terms of biomass, giving 4.6 t ha -1 and 7.2 t ha -1 of dry matter at low and high application rate, respectively (Table 6.2). Sawdust gave <2 t ha -1 for both rates, but yielded significantly higher than the control. The C. juncea treatment also had significantly higher yields than the rest of the treatments when high application rates were used.

136 Table 6.2 Effect of organic resources quality on maize productivity for different application rates at Makoholi Experimental Station during cropping season 112 Application rate N applied Biomass Total biomass Grain Apparent N and in 2WAE at maturity yield use efficiency Treatment resource kg ha -1 (kg grain kg -1 N added) Application rate: 1.2 t C ha -1 Crotalaria juncea a 4559 a 1978 a 8 ab Calliandra calothyrsus a 2949 b 1442 ab 6 c Maize stover b 2613 bc 1192 b 7 ac Pinus patula sawdust b 1940 c 1004 b 6 c Cattle manure ab 3890 d 1915 a 9 b Mineral N fertilizer 120 *n/a 2851 b 1541 ab 11 d Control 0 13 ab 574 e 247 c n/a SED nd Application rate: 4.0 t C ha -1 Crotalaria juncea a 7150 a 3140 a 7 b Calliandra calothyrsus a 4849 b 2361 b 6 ab Maize stover b 2579 c 1328 cd 6 ab Pinus patula sawdust b 1672 c 759 d 3 a Cattle manure c 5099 b 1887 bc 5 ab Mineral N fertilizer 120 *n/a 2851 c 1541 c 11 c Control 0 13 c 574 d 247 e n/a SED nd Figures in the same column followed by the same letter are not significantly different at p < 0.05; n/a = not applicable; nd = not determined; *The first application of mineral N was soon after sampling

137 113 However, there were no significant differences among C. juncea, C. calothyrsus, manure and mineral N fertilizer at low application rate. In the amended treatments, grain yields were consistently lowest under sawdust and highest under C. juncea. They ranged from 1.0 to 2.0 t ha -1 at low application rate, and from 0.8 to 3.1 t ha -1 at high rate (Table 6.2). Irrespective of application rate, all amended treatments had significantly higher yields than the control, which had <0.3 t ha -1. Overall, maize grain yield was linearly related to availability of mineral N released within the top 1 m of the soil profile from the different quality organic resources used. The amount of mineral N in the top 30 cm of the soil profile during middle part of the growing season (February) was best predictor for grain yield, with an R 2 value of 88% (Figure 6.6). The data showed that the grain yield response was consistent with quality of organic resources added, and this was also reflected in the apparent N use efficiency values (Table 6.2). Mineral N fertilizer had an apparent N use efficiency of 11 kg grain kg -1 N added, which was significantly higher than all the organic treatments. The N use efficiencies for C. calothyrsus, maize stover and sawdust were not significantly different, with <7 kg grain kg -1 N added. Application of the organic material at high rate further decreased the N use efficiency values, ranging from 3 for sawdust to 7 kg grain kg -1 N added for C. juncea Soil N changes and maize productivity under smallholder farmer management Total biomass and N contents of the different organic materials used by farmers were highly variable and translated to N input rates ranging from 32 to 588 kg N ha -1 (Table 6.3).

138 cm depth Maize grain yield (t ha -1 ) Y = 0.04x R 2 = 0.86; p < Soil mineral N (kg N ha -1 ) Crotalaria 1.2 t C ha -1 Crotalaria 4.0 t C ha -1 Calliandra 1.2 t C ha -1 Calliandra 4.0 t C ha -1 Maize stover 1.2 t C ha -1 Maize stover 4.0 t C ha -1 Sawdust 1.2 t C ha -1 Sawdust 4.0 t C ha -1 Manure 1.2 t C ha -1 Manure 4.0 t C ha -1 Unamended control N fertilized control Figure 6.6 Relationship between maize grain yields and mid-season (Feb.) soil N availability in the top 30 cm of the profile following incorporation of different organic nutrient sources at two carbon rates on a sandy soil at Makoholi With the exception of maize stover and C. juncea, organic materials in all three study areas were applied in very high quantities that ranged from about 20 to >40 t ha -1, resulting in high N loading (also see Table 6.1). Application rates were generally high in semi-arid Zimuto. Monitoring of available soil mineral N in Zimuto showed that the amount of profile mineral N under the C. juncea and mineral fertilizer treatments was significantly higher during the mid-season period (February) than at the end of cropping season in April (Figure 6.7).

139 115 Table 6.3 Maize biomass production and grain yields from different quality nutrient sources used in experiments designed and managed by farmers in three smallholder areas of Zimbabwe during the season Treatment N applied in resource (kg ha -1 ) Maize shoot biomass (kg ha -1 ) Maize Grain yield (kg ha -1 ) Apparent N use efficiency (kg grain kg -1 N added) Chikwaka (765 mm ) Crotalaria juncea Fresh litter Maize stover Cattle manure Mineral N fertilizer Unamended control SED n/a nd 655 a 577 ab 459 ab 923 a 441 ab 108 b a 192 ab 140 ab 390 a 107 b 6 b n/a ns Chinyika (631 mm) Crotalaria juncea Fresh litter Maize stover Cattle manure Termitaria Compound D* Mineral N fertilizer Unamended control SED n/a nd 5997 a 6302 a 3959 ab 5598 a 5600 a 4819 a 5008 a 2199 b a 2553 a 1575 bc 2644 a 2279 ab 2007 ab 2194 ab 729 c b 6 a 8 ab 6 a 6 a 15 c 21 d n/a 2 Zimuto (659 mm) Composted litter Composted maize stover Crotalaria juncea Fresh litter Cattle manure Termitaria Mineral fertilizer Unamended control SED n/a nd 4408 a 4214 a 3395 ab 3860 a 5728 a 2040 bc 2054 bc 962 c ab 1579 ac 1595 ac 1497 ac 2814 b 792 cd 818 cd 257 d a 6 ab 7 b 3 a 5 ab 3 a 8 b n/a 2 Current season rainfall; Figures in the same column followed by the same letter are not significantly different at p < 0.05; ns = not significant; *This treatment received Compound D (7%N:6%P:6%K:7%S) instead of the blanket basal PKS (0%N:14%P:13%K:5%S) given to all others but the control; n/a = not applicable; nd = not determined

140 116 Available soil mineral N (mg N kg -1 soil) Crotalaria Composted litter Soil depth (cm) Fresh litter Composted maize stover Cattle manure 80 Termitaria Basal PKS fertilizer Unamended control Mid-season End of season Figure 6.7 Soil available mineral N during mid (February) and end (April) of the season (2003-4) following incorporation of different nutrient sources in a sandy soil by smallholder farmers in Zimuto

141 117 In contrast, manure, and composted- and fresh-litter exhibited more profile mineral N at the end than during mid-season, suggesting that these materials released most of their N late in the growing season. Results from Chinyika and Chikwaka followed a similar pattern (data not shown). There was no obvious relationship between N application rates and profile N for all the treatments for both sampling times. Manure and composted litter treatments had the highest profile N of 108 and 122 kg N ha -1, respectively at the end of season, compared with <40 kg N ha -1 for the control. Mineral N availability under termitaria was not significantly different at both sampling times, averaging 56 kg N ha -1. Maize productivity was generally high under manure for all the three study areas, with ~ 3.5 times more grain yield than the control in Chinyika and about 10 times more in Zimuto (Table 6.3). While Chikwaka received the highest annual rainfall, the maize yields were drastically low, most likely due to a combination of late planting and prolonged delays in weeding by farmers. Resultant maize biomass yields for all treatments were <1 t ha -1 although treatment differences were significant (P<0.05). Maize grain yields under fresh litter and C. juncea were not significantly different in all three sites, and averaged 2.5 and 1.5 t ha -1 in Chinyika and Zimuto respectively. Use of termitaria did not significantly improve grain yields compared with mineral fertilizer in these two sites (Table 6.3).

142 a) Chikwaka (>750 mm yr -1 ) Crotalaria Fresh litter Maize stover Manure Mineral fertilizer Control 0.0 Y = 0.01x R 2 = 0.823; p < 0.01 Maize grain yield (t ha -1 ) b) Chinyika ( mm yr -1 ) Y = 0.005x R 2 = 0.654; p < 0.05 Crotalaria D after emergence Fresh litter Maize stover Manure Mineral fertilizer Termitaria Control c) Zimuto ( mm yr -1 ) Crotalaria Composted litter Fresh litter Composted maize stover Manure Mineral fertilizer Termitaria Control Y = 0.003x R 2 = 0.710; p < Total N applied (kg N ha -1 ) Figure 6.8 Relationship between total amount of N supplied in different nutrient sources and maize grain yield under smallholder farmer management in Chikwaka, Chinyika and Zimuto

143 119 Grain yields were dependant on the total amount of N added, and there was a significant linear relationship between the two parameters (Figure 6.8). Combinations of organic and mineral fertilizers improved this relationship, with R 2 values of 88%, 82% and 84% for Chikwaka, Chinyika and Zimuto respectively. Apparent N use efficiencies were characteristically low, yielding <8 kg grain kg -1 N added for all organic treatments except C. juncea (Table 6.3) in Chinyika. In contrast, mineral fertilizer alone gave significantly high values of 8 to 21 kg grain kg -1 N added in Zimuto and Chinyika. Poor yields in Chikwaka resulted in extremely low N use efficiencies with in significant treatments differences. 6.5 Discussion Mineral N (NH + 4 -N + NO - 3 -N) release patterns of the different quality organic resources were influenced by rainfall events throughout the season, with notable fluctuations closely following within-season wet and dry spells. Significant conversion of NH + 4 -N into nitrate was only evident after the first three weeks of incorporating organic materials into moist soil. Apart from demonstrating the relatively well-known Birch effect (Birch, 1964; Chikowo et al, 2004a), the findings suggest that the threat of NO - 3 leaching only occurs at least three weeks after either incorporation of organic material into moist soil or wetting of a soil containing decomposable organic matter. Release of large amounts of NO - 3 -N under C. juncea only three weeks after incorporation suggests that the N released from such high quality materials is most susceptible to leaching. Progressive changes in the NO - 3 -N bulge down the profile in this study was considered an exhibition of leaching. This was further exemplified

144 120 by the mineral N fertilizer treatment under which there was a dramatic increase in NO - 3 -N in the cm depth within a week of a single rainfall event following N fertilizer application. The NO - 3 -N bulge had disappeared in less than four weeks, demonstrating that the N applied to these soils in fertiliser is lost over relatively short periods. Nitrate leaching is a major threat to smallholder cropping systems of sub-sahara Africa, particularly under sandy soils of Southern Africa where the applied N can be leached with the early rains (Hagmann, 1994; Nyamangara et al., 2003) before crops develop a sufficiently dense root system for efficient uptake (Chikowo et al., 2003). Late planting can exacerbate the problem. Increasing the quantity of organic materials applied per plot, at Makoholi, did not seem have a differential effect on N mineralization by the different treatments, but simply increased the total amounts of N released or the magnitude of immobilization. The warm and wet conditions marking the beginning of the cropping season, coupled with an increase in soil system C, primed increased microbial activity (Amato and Ladd, 1992; Killham et al., 1993), resulting in immediate organic matter mineralization for N-rich treatments. Applications of the high quality C. juncea and C. calothyrsus at high rates evidently resulted in increased N release as well as losses. On the other hand, high quantities of the low quality maize stover and sawdust prolonged their N immobilization effects. Adding large amounts of oxidizable C from resources with <25 mg N g -1 create a microbiological demand for N (Palm, 1995; Palm et al., 1997), possibly inducing immobilization of both organic- and soil-derived mineral N. Resource quality (Heal et al., 1997) was therefore a primary cause for the observed treatments differences.

145 121 Little NO - 3 -N was observed in the top 40 cm of the soil profile across all treatments at Makoholi when low rates of organic matter application were used. This was partly attributed to uptake by the growing maize crop, apart from leaching and utilization by the decomposer microorganisms (Reinersten et al., 1984). Research in similar farming systems demonstrated that other forms of N losses such as denitrification and ammonia volatilisation rarely exceed 10 kg ha -1 yr -1 (Chikowo et al., 2004b; Mapfumo et al., 2001b). Large NO - 3 -N bulges below the 40 cm depth further suggests little nutrient uptake by the crop beyond this depth. Maize has been shown to have less than the optimal root-length density for effective nutrient uptake beyond a soil depth of 60 cm (Chikowo et al., 2003). In this study organic application rates were based on C, and this obviously resulted in large initial treatment differences with respect to N inputs. For instance, high application rates of C. juncea, C. calothyrsus and manure resulted in N inputs of >230 kg N ha -1 compared with only 28 and 71 kg N ha -1 for sawdust and maize stover respectively. Such high N loading meant that significantly large amounts of mineral N were available early in the season for high quality materials, inevitably resulting in increased NO - 3 -N leaching. Studies by Nyamangara et al. (2003) on similar soils indicated that as much as 56 kg N ha -1 yr -1 is potentially lost through leaching under manure and high mineral N fertilization rates. Conversely, loading the system with low quality maize stover and sawdust negatively impacted on mineral N availability, with a 30 and 42% reduction in mineral N release when the materials were applied at high rates respectively. Application of high quality materials at low rates gave no grain yield advantage over the manure and mineral N fertilizer treatments at Makoholi despite the

146 122 relatively high amounts of N released. Significantly high grain yields and separation of treatment effects were only achieved at high application rates, suggesting that N recovery by the crop was simply dependent on factors that increase within-season available soil mineral N fluxes. While previous research has shown a significant relationship between pre-season mineral N and maize yields (Barrios et al., 1998; Mapfumo, 2000), findings in this study (Figure 6.8) suggested that mid-season soil N availability was a better predictor for yield. The linear increase in maize yield with increasing soil profile mineral N during midseason further suggests that mineral N within rooting zone may better account for yields often observed on sandy soils than simply topsoil N (0-15 cm). Maintaining high fluxes of mineral N in such porous soils (<100 g clay kg -1 ) and simultaneously increasing its recovery by crops is a key management challenge, as evidenced by the invariably low N use efficiency for the organic materials despite the high N input rates used. The on-station findings at Makoholi were consistent with on-farm results where a linear relationship between grain yield and total N added in organic materials was also observed under smallholder farmer management. Mineral N release patterns for all organic materials used by farmers showed that they were invariably of low quality compared to C. juncea, which was used as a reference. However, the materials did not prolong N immobilization to the same extent as maize stover and sawdust, releasing significant amounts of their N towards the end of the season. This suggested that farmers handling practices such as composting were beneficial when the materials were subsequently used in combination with mineral fertilizer.

147 123 Since all the materials had generally similar N mineralization patterns, it was primarily the quantities added that accounted for the observed yield differences. This may explain why smallholder farmers in the respective study areas used substantially high rates of these low-n organic inputs. In the case of manure, application rates of >40 kg ha -1 partly emanate from historical recommendations of 37 t ha -1 every four years by the national extension (Mugwira and Shumba, 1986). A key question is to what extent this N loading can be balanced with the required level of crop nutrient use efficiency to attain high yields. For instance, no more than 2.8 t ha -1 was obtained with >450 kg ha -1 of total N input in Zimuto, while similar yields were attained with ~ 250 kg N ha -1 in Chinyika (Figure 6.7). However, absolute amounts of soil mineral N found under C. juncea and mineral N fertilizer treatments during the season were not significantly different (Figure 6), implying that two N sources could have a substitutive role. This may explain why Itimu et al. (1998) found no significant interaction effects between high quality legume tree prunings and N fertilizer in Malawi. On the other hand, low N release from termitaria soil may be attributed to its relatively high amounts of clay. Clay stabilizes soil organic matter, reducing mineralization (Hassink, 1997; Sorensen, 1981). The highest maize yields under farmer management were obtained under cattle manure which is the most widely used organic resource in the smallholder farming systems of Zimbabwe (Mapfumo and Giller, 2001). The behaviour of manure was consistently similar both on-station and on-farm, exhibiting a delay in mineral N release until about the mid-season period. The high yields could therefore have been due to increased mineralization during mid-season, which was synchronous with critical maize growth stages of flowering/grain filling.

148 124 Addition of mineral N fertilizer may have offset the prolonged N immobilization normally associated with the first season of manure application (Mugwira and Mukurumbira, 1984; Probert et al., 2005). Because of variability often arising from differences in quality of livestock feed and handling (Delve et al., 2001; Kimani and Lekasi, 2004), potential amounts of N released from manure cannot be predetermined as is the case with green manures (Palm et al., 1997, 2001). However the high application rates of about t ha -1 used by farmers inevitably resulted in a large pool of available mineral N. Significantly high NH + 4 -N concentrations at cm depth (up to 17 kg N ha -1 ) measured at T5 (Figure 2d), suggests N mineralization in sub-surface horizons, as previous studies on similar soils have suggested limited chances of NH + 4 -N leaching (Chikowo et al., 2004b). 6.6 Conclusions The study showed that maize productivity, and most likely that of other cereals, on granitic sandy soils with <100 g clay kg-1, hinges primarily on within-season fluxes of soil mineral N. High quality organic resources release a significant proportion of their N within three weeks of incorporation into moist soil, but most of this N is highly susceptible to leaching losses as NO - 3 -N. Most of the NO - 3 -N leaching occurred within a week of a single rainfall event following its accumulation in soil. While use of high application rates significantly increase such losses, it is apparently necessary to maintain the high soil N fluxes required to attain high yields. This raises a critical question for improving nutrient use efficiency on such soils in the wake of increasing efforts to promote utilization of high quality organic inputs on smallholder farms. High maize grain yields >3 t ha-1 were only attainable with huge amounts of organic N inputs applied in combination with mineral N fertilizer. While findings from this study justify the high organic matter loading

149 125 strategy employed by smallholder farmers in Zimbabwe to achieve relatively high yields on coarse sandy soils, questions arise about optimal production scales and economic viability of such practice.

150 126 CHAPTER 7 Organic matter quality and management effects on enrichment of soil organic matter fractions on contrasting soils in Zimbabwe 7.1 Abstract The chapter addresses the interactive effects of organic resource quality and management on SOM formation and subsequent influence on maize yields under contrasting soil types. Maintenance of SOM at levels that sustain optimal supply of soil nutrients and enhance efficiency of externally added fertilizers is a major challenge for smallholder farming systems. Crotalaria juncea, Calliandra calothyrsus, cattle manure, maize (Zea mays L.) stover and Pinus patula sawdust were applied at 2.5 t C ha -1 and 7.5 t C ha -1 in season 1 and 1.2 t C ha -1 and 4 t C ha -1 (season 2) at Domboshawa and Makoholi Experimental stations while soil amendments commonly available on smallholder farms (e.g. manure, crop residues and woodland litter) were applied on-farm at variable rates (1-12 t C ha -1 ) determined by farmers. Soils at Domboshawa are sandyclay loams with 220 g clay kg -1 while the sandy soils at Makoholi were similar to those for the communal areas of Zimuto and Chikwaka with <100 g clay kg -1. About weeks after incorporation, organic resource quality effects on POM C enrichment were most significant (p<0.01) in the macro-pom ( µm diameter) fraction of both soil types constituting 15-30% of total soil C on coarse sand soil and between 5-10% of total soil C on sandy clay loam soils. The highest increases were under C. calothyrsus, manure and sawdust treatments. Evidence of subsoil enrichment was only apparent on sandy soils under C. calothyrsus and manure treatments. Under smallholder farmer management in Chikwaka and Zimuto, C enrichment was highest under manure and composted litter treatments, accounting for >30% more soil C against the nonamended control. Fractionation of the different soils reflected changes in both the macro- POM and the meso-pom ( µm diameter) fractions under organic resource management. While there were no significant treatment effects on the size of organo- This chapter has been modified and submitted as: Mtambanengwe,F., Mapfumo, P. and Vanlauwe, B Organic matter quality and management effects on enrichment of soil organic matter fractions on contrasting soils in Zimbabwe. (submitted to Plant and Soil).

151 mineral fractions, there was a significant (p<0.05) separation of treatments in terms of potential mineralizable N from the same fraction. 127 On coarse sands, medium to high quality materials such as manure and C. juncea released ~50 mg N kg -1 compared to between 8-18 mg N kg -1 from low quality sawdust and maize stover, suggesting that high quality material enhanced the N-supply capacity of the organo-mineral fraction without necessarily increasing the size. The same trends were observed under sandy clay loams although in contrast to coarse sands, the high quality materials released no more than 25 mg N kg -1, suggesting that the added C may be protected against immediate mineralization in short-term under the clayey soils. These contrasting properties were also reflected in maize yield patterns between the two soil types. On sandy clay loams, maize yields were significantly related to the amount of mineralizable N in the macro-pom fraction (R 2 = 0.50; p < 0.01), while the best predictor for maize yields on coarse sands was the mineralizable N from the organo-mineral fraction (R 2 = 0.86 for Makoholi and R 2 = 0.70 for Chikwaka). It was concluded that maize productivity on contrasting soil types hinges on different soil organic fractions and therefore require different management strategies. Sustainability of cropping on sandy soils is likely o depend on a regular supply of high quality C materials which enhance the nutrient supply capacity of a small organo-mineral fraction while maintenance of a large macro-pom fraction under the relatively C protective sandy clay loams promotes high crop yields in short-term. 7.2 Introduction The maintenance and improvement of soil organic C is an important factor in the sustenance of overall farm productivity because of its influence on soil productivity and nutrient cycling processes (Duxbury et al., 1989; Swift, 1998). Soil organic matter (SOM) largely originates from aboveground organic inputs, root residues and exudates, all of which differ widely in their decomposition and mineralization processes. It is this differential turnover times, coupled with inherent soil properties particularly texture and ph, and land management that resource quality can affect the formation of SOM and subsequent nutrient availability. Decomposition and synthesis of many different SOM fractions, which can range from the biological active to the passive pools (Elliot and Cambardella, 1991), is influenced by prevailing management processes operative under a series of contrasting physicochemical, biological and socio-economic environments (Swift et al., 1994). Soils under the majority of smallholder farming in Zimbabwe have low inherent fertility characterized by a significant small fraction of low-activity clays (<100 g kg -1 ) with

152 128 predominantly kaolinite (Nyamapfene, 1991). Since most of these soils have characteristically low CEC, the SOM fraction plays an important role in nutrient retention and its maintenance is crucial in sustaining productivity. There is a general widespread use of organic soil ameliorants to improve the nutrient supply capacity particularly on the predominantly sandy soils under smallholder farming in Zimbabwe (Mapfumo and Giller, 2001). However, the organic resources incorporated into soil are often of medium- to poor quality and are likely to have a differential impact on the soil organic (SOM) fractions prompting the need to improve our understanding of organic resource quality- SOM-management interactions. Numerous SOM experiments dedicated to study the responses of in situ SOM have been carried out (Anderson et al, 1981; Ladd et al., 1985; Cambardella and Elliot, 1994; Six et al., 1998; Six et al., 1999), leading to an improved understanding of the different functions of fractions isolated through soil particle size fractionation. Both physical and chemical fractionation methods have been used to separate particulate organic matter (POM) sometimes referred to as the light fraction SOM, in coarse-textured soils. In cases where soils lack the protective capacity to store C (e.g. sandy soils), direct measurements of new POM resulting from variations in management have been known to approximate reality (Feller, 1993). However, the relative influence of continuous application of different quality organic and mineral nutrient sources on the enrichments and behaviour of the POM and organomineral fraction under tropical smallholder cropping systems still remains largely unknown. Characterization of this POM fraction (particle size ranging between µm diameter) has been linked to short-term nutrient availability since it is

153 129 thought to incorporate much of the organic fertilizer property of SOM (Swift and Woomer, 1993). There has however been little qualitative data to support this argument. This study was carried out to quantify the interactive effects of organic resource quality and quantity on SOM functional pools essential for maintenance of maize productivity under different management systems and soil types. The specific objectives of the study were to: i. quantify the relative contribution of different quality organic nutrient resources to SOM fractions under soils with contrasting textures ii. determine the relative distribution of POM down sandy soil profiles in relation to organic matter management iii. determine the relationship between N release from the different fractions and maize grain yields 7.3 Materials and Methods Study sites The study was conducted between 2002 and 2004 in Chikwaka and Zimuto smallholder farming areas and at Domboshawa and Makoholi (Chapter 3). The field experiments at Domboshawa and Makoholi were established in November 2002 as part of a long-term trial aimed at investigating the influence of continuous and repeated application of different quality and quantities of organic resources on soil organic matter dynamics (Mapfumo et al., 2001a). Five different quality organic resources ranging from high to low (Table 7.1) were hand-incorporated to a depth of 0.15 m using hoes in experimental plots measuring 6 x 6 m 2 in gross area at the beginning of the 2002/03 and 2003/04 growing seasons.

154 130 Table 7.1 Quality of organic resources used under two contrasting soil types at Domboshawa and Makoholi field experiments Treatment Nitrogen Lignin Polyphenol C:N (%) Crotalaria juncea 3.3 (0.05) 6.5 (0.02) 1.8 (0.01) 13 Calliandra calothyrsus 2.8 (0.07) 14.0 (0.1) 4.6 (0.08) 16 Manure 1.2 (0.03) 2.9 (0.02) 0.2 (0.01) 18 Maize stover 0.8 (0.01) 2.9 (0.02) 1.0 (0.03) 55 Pinus patula sawdust 0.3 (0.03) 28.0 (0.03) 0.6 (0.02) 156 Numbers in parentheses indicate standard error of the mean The organic resources were applied at two carbon rates of 2.5 and 7.5 t C ha -1 in season 1 but this was later revised to 1.2 and 4.0 t C ha -1 respectively in season 2 due to bulking problems. Farmer-managed experiments in Chikwaka and Zimuto communal smallholder were established during 2003/04 season using different quality organic resources identified by farmers during participatory workshops as earlier described in Chapter 6. The organic resources (Table 7.2) were also broadcast and incorporated by hand-hoes to a depth of 0.15 m on plots measuring 4.5 m x 8 m, two weeks prior to planting of a maize test crop. A non-amended control and mineral N treatments were included at each experimental site. A randomised complete block design with three replicates was used. At Chikwaka, planting was delayed to about five weeks after organic resource incorporation as the farmers prioritised their own fields relative to experimental sites.

155 131 Table 7.2 Organic and mineral nutrient sources used by smallholder farmers in Chikwaka and Zimuto communal areas Treatment *Application Amount of N Amount of C rate used applied in resource applied in resource (t ha -1 ) (kg ha -1 ) (t ha -1 ) Chikwaka (> 750 mm yr -1 ) Fresh woodland litter Cattle manure Maize stover Crotalaria juncea Ammonium nitrate Control n/a Zimuto (<650 mm yr -1 ) Fresh woodland litter Composted litter Composted maize stover Cattle manure Crotalaria juncea Termitaria Ammonium nitrate Control n/a * - Dry weight basis; n/a not applicable

156 Soil sampling and fractionation Soil samples for total C analysis and particulate organic matter (POM) fractionation were collected from all the four sites during the mid-season period (early to mid-february), about weeks after organic resource incorporation. The samples were collected from 0-15, 15-30, 30-45, 45-60, and cm depths at Domboshawa and Makoholi, and to a depth of 100 cm at 20 cm intervals at Chikwaka and Zimuto. For each sampling, soil was collected from five replicate points within a plot before a composite sample was drawn for analysis. Bulk density measurements were also taken at the respective depths from representative soil profile pits through undisturbed samples collected in cores measuring 72 mm in diameter and 50 mm in height. Total organic C from the topsoil only was determined using a modified Walkley-Black procedure without external heating (Anderson and Ingram, 1993). Particulate organic matter was quantified by wet-sieving and floatation (Okalebo et al., 2002). Soil samples were sieved to pass through a 2 mm sieve inorder to remove coarse fragments including plant roots, stones and large debris, after which two sets of 100 g sub-samples each were transferred into a 250 ml container and dispersed with 100 ml of 10% sodium hexametaphosphate on an end-over-end shaker for 18 hours. After shaking, the soil mixture in each flask was decanted onto an assemblage of wet sieving apparatus with mesh sizes of 250 and 53 µm (Figure 7.1). All POM between the µm sieves (macro-pom) and between the µm (meso-pom) sieves were separated from the mineral fraction by floatation and collected. The POM and mineral fractions were oven dried at 60 Cfor 48 hours and their weights recorded.

157 133 Composite field fresh soil Whole sample: dry sieving at 2000 µm mesh Fraction > 2000 µm discarded 100 g sub-sample dispersed in 10% Na hexametaphosphate Wet sieving & floatation of dispersed soil using 250 µm mesh MACRO-POM fraction ( µm Wet sieving and floatation at 53 µm mesh sieve MESO-POM fraction ( µm diameter) Sedimentation of clay + silt organomineral fraction Micro-POM <53 µm diameter + mineral associated matter (ORGANO-MINERAL fraction) Figure 7.1 Schematic diagram showing procedure used to separate particulate organic matter and organo-mineral fractions in soil

158 134 The fraction <53 µm, (organo-mineral) was allowed to settle for hours after which excess water was siphoned and the fraction dried at 60 C before quantification. For one set of samples, the fractionated macro-pom and meso- POM fractions were added back to their respective mineral fractions before a twoweek incubation for potential mineralizable N estimates. A 20 g sub-sample of the organo-mineral fraction was also incubated for mineral N estimates. The second set was used to determine their respective C concentrations Mineral N analysis The µm (POM + mineral) fraction, the (POM + mineral) fraction and the organo-mineral fraction were anaerobically incubated for 14 days at 28 C for potential mineralizable N after submerging the fractions with deionised water. After 14 days, the fractions were shaken on an end-over-end shaker for one hour, centrifuged and a clear supernatant transferred into a set of 100 ml plastic containers. Ammonium-N concentration in the different fractions was determined by the phenate method as described by Keeney and Nelson (1982) and colorimetrically quantified at 640 nm using a UV-visible spectrophotometer, Shimadzu BioSpec Model 1601 against a set of blank standards Quantifying the N mineralization potential and C contributions in fractions Respective bulk densities for the different soil depths were used to quantify the different fraction sizes and their potential N mineralization on a hectare basis. The amount of C in each fraction was calculated as the product of the size of fraction and corresponding C concentration in the fraction e.g. Macro-POM C = POM x %C The amount of mineralizable N per fraction was also calculated in a similar way. Relative C contributions of each fraction to total soil C was

159 135 calculated as a fraction of the %C in the size fraction expressed as a percentage of total soil C while total mineralizable N was calculated as the sum of N mineralized from each of the three fractions Data analyses Analysis of variance (ANOVA) was used to determine the effects of different organic resource management regimes on the POM and organo-mineral fractions using Genstat statistical package (Genstat for Windows Discovery Edition 1, 2003). The ANOVA was was also used to determine the effect of resource quality and soil depth on potentially mineralizable N. Mean separation was tested using Tukey s at p<0.05. Regression analyses were carried out to determine relationships between maize grain yields and the different size fractions, as well as between overall maize grain yield and potentially mineralizable N in the different fractions. 7.4 Results Effect of organic resource quality on the size of POM fractions Incorporation of different quality organic materials significantly increased topsoil organic C contents of both a sandy clay loam soil at Domboshawa and a coarse sandy soil at Makoholi. On sandy clay loams, organic C contents increased by as much as 18% following application of 4.0 t C ha -1 of Calliandra, manure and sawdust in comparison with a non-amended soil, which had total C contents of 6.2 g C kg -1 soil (Figure 7.2).

160 Domboshawa - sandy clay loam 0-15 cm 10 8 Makoholi - coarse sand 0-15 cm µm µm Organo-mineral Relative organic C contribution (g kg -1 soil) cm SED Total C = µm = µm =ns Organo-mineral = cm SED Total C = µm = µm =ns Organo-mineral = ns Crotalaria juncea Calliandra calothyrsus Manure Maize stover Sawdust Control 0 Crotalaria juncea Calliandra calothyrsus Manure Maize stover Sawdust Control Figure 7.2 Relative C distribution in separated POM- and organo-mineral fractions following two seasons application of 4 t C ha -1 of different quality organic resources on (i) a sandy clay loam at Domboshawa and (ii) a coarse sand at Makoholi

161 137 Under coarse sands at Makoholi, the same quality resources increased soil C contents by >50% against 3.8 g C kg -1 soil for the non-amended control. The same trends were observed under low biomass application (data not shown), although the magnitude of impact was lower. Analysis of variance showed a significant twoway interaction between organic resource quality and soil depth (p<0.05). However no significant interaction could be attested for organic resource quality and rate of application of the different resources on soil C under both soil types. Fractionation of the different organic matter fractions showed that overall topsoil C contribution of the macro-pom ( µm diameter) fraction to total soil was <10% under sandy clay loams (Figure 7.2). Manure application apparently increased the relative C concentration of the organo-mineral fraction compared to other treatments. For the other treatments, there was an equal contribution to total C from both the meso-pom and the organo-mineral fraction in the top 15 cm, and these were not significantly different. In the sub-soil (15-30 cm depth) of the sandy clay loams, both the organo-mineral and macro-pom fractions were significantly affected by organic resource management (Table 7.2). While manure, Calliandra and Crotalaria contributed 40% to the total C pool (~2 g C kg -1 ) to the meso-pom fraction in the subsoil, against <1 g C kg -1 under maize stover, sawdust and control treatments, the observed variations were not significant. In the subsoil, ~75% of total C was in the organo-mineral fraction for non-amended control (Figure 7.2), implying a likely short-term unavailability of nutrients due the protective nature of this fraction. On coarse sands under low rainfall Makoholi, there was a 15-30% increase of the macro-pom fraction under Calliandra, sawdust and manure treatments in the top

162 cm. Evidence of sub-soil enrichment of macro-pom under these three treatments was apparent (Figure 7.2). Although the relative size of the meso-pom fraction accounted for between 30% of total C under Calliandra and 60% under Crotalaria, maize stover and control treatments, treatment differences were not significant. Organic C concentration in the organo-mineral fraction did not show any significant treatment effects averaging ~2 g C kg -1, a figure translating to between 30-50% of total C under the different organic management regimes POM size fractions on sandy soils under smallholder farmer management Under smallholder management in Chikwaka and Zimuto, incorporation of varying amounts of different quality organic resources to soil also significantly increased topsoil organic C contents. When measured against an amended soil, increases of between 3% under maize stover treatment and 46% under manure treatment were observed in Chikwaka. Under semi-arid conditions in Zimuto, increases in soil C contents were of the magnitude of between 11 and 62% for composted litter stover and manure respectively. Application of mineral N fertilizer and maize stover (both sites) and termitaria soil (Zimuto) did not significantly change soil C contents (Figure 7.3) in the short-term. In Chikwaka, fractionation for the different POM size fractions revealed significant treatment differences in the macro-pom and the organo-mineral fractions. However, contribution of macro-pom to total C under the different organic resources was <15%. Mineral fertilizer apparently decreased the size of the macro-pom by about 30%, compared to the control treatment, accounting for only 5% of total C.

163 139 Relative organic C contribution (g kg -1 soil) Chikwaka - coarse sand (>750 mm yr -1 ) SED Total C = µm = µm =ns Organomineral = Zimuto coarse sand ( mm yr -1 ) µm µm organo-mineral SED Total C = µm = µm = 0.3 Organomineral = Fresh litter Crotalaria juncea Maize stover Manure Mineral N fertilizer Control 0 Composted litter Composted maize stover Crotalaria juncea Fresh litter Manure Mineral N fertilizer Termitaria Control Figure 7.3 Relative C distribution in the different POM- and organo-mineral fraction following application of different quality organic resources on a coarse sands under (i) high rainfall area at Chikwaka and (ii) semi-arid conditions at Zimuto during the season Statistical differences in the organo-mineral fraction were apparently due to increases of this fraction under the manure treatment (Figure 7.3), contributing 25% more C compared to the rest treatments which averaged ~1.6g C kg -1 soil. The meso-pom fraction was apparently not affected by the different management regimes when tested at p<0.05, contributing about 35% to the organic C pool. Under low rainfall in Zimuto, the different inputs significantly affected the size of all three isolated organic matter fractions (Figure 7.3). Soils under composted litter, manure and fresh litter had between 100 and 400% more macro-pom compared to the control. Except for soils under the composted litter treatment, >50% of soil C

164 140 was contributed by the meso-pom fraction under organic resource treatments in contrast with an equal contribution by the meso- and the organo-mineral fraction under mineral N fertilizer, termitaria and unamended control (Figure 7.3) Distribution of POM down contrasting soil profiles Analysis of soil profiles for the relative distribution of the different POM size fractions showed significant differences in the fate of the same quality organic resources on contrasting soil types at Makoholi and Domboshawa. On coarse sands at Makoholi, the size of the macro-pom fraction ranged between 0.3 kg ha -1 under maize stover and 2.8 kg ha -1 under Calliandra treatments compared to between 0.1 and 0.6 kg ha -1 for the same quality resources on sandy clay loams in Domboshawa (Figure 7.4). Treatment separation in the size of macro-pom was significant only up to a 30 cm depth, and below that no significant differences could be ascertained. While the behaviour of manure in the meso-pom ( µm diameter) was not significantly different from other organic resources at on sandy clay loams, manure movement down the profile was evident down to a depth of 60 cm on coarse sands (Figure 7.4). Total cumulative values under this treatment were as much as 5 kg ha -1 compared to <2 kg ha -1 for the other treatments. The different quality organic resources resulted in significant differences in the organo-mineral fraction in the top 45 cm on sandy clay loams but not on coarse sands. At depths lower than 45 cm, no significant treatments differences were apparent. Worth noting was the abrupt increase in the size of the organo-mineral fraction below a depth of 45 cm for both soil types (Figure 7.4).

165 POM fraction (kg ha -1 ) Soil depth (cm) Sandy clay loam POM size: µm Sandy clay loam POM size: µm Sandy clay loam Organomineral fraction: <53 µm Crotalaria Calliandra Maize stover Sawdust Manure Control Coarse sand POM size: µm Coarse sand POM size: µm Coarse sand Organomineral fraction: <53 µm 120 Figure 7.4 Size and distribution of two POM fractions and an organo-mineral fraction following incorporation of different quality organic resources at 4 t C ha -1 on a sandy clay loam soil under high rainfall conditions at Domboshawa, and coarse sands under semiarid conditions at Makoholi There was no evidence to align this sudden increase to organic resource management suggesting that this increase was probably an inherent property of these granitic soils. Application of the different quality organic resources at 1.2 t C ha -1 showed similar trends in POM distribution as those observed under higher rates (4.0 t C ha -1 ) in the different soil profiles although the magnitude of impact was lower for the same quality organic resources (data not shown).

166 Potential mineral N contributions from different POM fractions At Domboshawa, there was a significant interaction between organic resource quality and soil depth for mineralizable N from the three isolated POM fractions. However, rate of application of the different quality organic resources did not significantly affect the amount of mineralizable N from the macro-pom, while the meso-pom and the organo-mineral fractions were significantly affected (Figure 7.5). Relative amounts in the topsoil ranged between 1 mg N kg -1 and 18 mg N kg - 1 soil (meso-pom) and between 5 mg N kg -1 and 22 mg N kg -1 (organo-mineral) for sawdust and Crotalaria treatments respectively. On coarse sands, the organo-mineral fraction consistently released more mineralizable N than either the macro-pom or the meso-pom fractions. There was a clear separation in potential N mineralized by the organo-mineral fraction between medium-to high quality resources (manure, Calliandra and Crotalaria) and poor quality resources (maize stover and sawdust). This was particularly evident in the top 60 cm of the profile regardless of soil type (Figure 7.5). At Makoholi, the organo-mineral fraction under manure, Calliandra and Crotalaria treatments mineralized up to 50, 42 and 28 mg N kg -1 soil (0-15 cm) respectively, a clear separation from amounts of between 8-18 mg N kg -1 under lower quality resources. Meanwhile at Domboshawa, maximum amounts of mineralizable N of ~24 mg N kg -1 soil were from the manure treatment (Figure 7.5), but this was not significantly different from amounts mineralized under Calliandra and Crotalaria.

167 143 Potential mineralizable N (mg N kg -1 soil) Sandy clay loam POM size: µm Sandy clay loam POM size: µm Sandy clay loam Organomineral fraction: <53 µm 60 Soil depth (cm) Crotalaria Calliandra Maize stover Sawdust Manure Control Coarse sand POM size: µm Coarse sand POM size: µm Coarse sand Organomineral fraction: <53 µm 120 Figure 7.5 Potential mineralizable N from the macro-, meso-pom and organo-mineral fractions following incorporation of 4 t C ha -1 of different quality organic resources on (i) a sandy clay loam soil at Domboshawa and (ii) coarse sand at Makoholi Relationships between POM fraction size and maize productivity Total soil organic C contents generally did not significantly influence maize productivity. The only exception was in Zimuto, where a significant linear relationship between maize yields and total C with an R 2 value of 0.76 (p<0.01) was obtained (Table 7.3). Separation of the organic C pool into three different size-fractions improved the correlation, particularly on farmers fields in Chikwaka, probably due to a previous history of organic management.

168 144 Table 7.3 R 2 values of relationship between maize yields and total C, POM- and organo-mineral- size fractions (0-30 cm depth) under different organic matter management at four sites in Zimbabwe Site and texture Total C µm diameter µm diameter Organomineral Domboshawa (sandy clay loam) 0.19 ns 0.10 ns 0.46 * 0.67 *** Makoholi (coarse sand) 0.13 ns 0.02 ns 0.43 * 0.04 ns Chikwaka (coarse sand) 0.44 ns 0.68 * 0.66 * 0.31 ns Zimuto (coarse sand) 0.76 ** 0.60 * 0.66 ** 0.23 ns * = p < 0.05; ** = p < 0.01; *** = p < 0.001; ns = not significant On sandy clay loams at Domboshawa, the level of significance increased with decreasing POM size (Table 7.3) with the size of the organo-mineral fraction best predicting yield estimates (R 2 = 0.67; p < 0.001). In contrast, the size of the organo-mineral fraction in the coarse sands showed no significant relationships with maize yields in all the three sites. Overall, it was the size of the meso-pom fraction that could uniquely predict maize yields estimates across the different sites (Table 7.3). The amount of potentially mineralizable N from the different sizefractions also had significant effect on maize grain yield although the degree of impact varied with soil type and area (Table 7.4). Although the size of the organomineral fraction best predicted maize yields on sandy clay loams in Domboshawa, mineralizable N from this fraction was weakly correlated (R 2 = 0.37; p<0.05) to maize yields. The best predictor was the fraction of mineralizable N from the macro-pom fraction, which gave an R 2 value of 0.50 (p < 0.01) (Figure 7.6).

169 145 Table 7.4 R 2 values and level of significance for relationships between maize yields and particulate organic matter size fractions at different depths from two onfarm sites (Chikwaka and Zimuto) and two on-station sites (Domboshawa and Makoholi) Site and mineralizable N from fraction Domboshawa (sandy clay loam) (> 750 mm yr -1 ) µm N µm N <53 µm (organo-mineral) N ( µm N) + ( µm N) + (<53 µm N) ( µm N) + ( µm N) + (<53 µm N) Chikwaka (coarse sand) (> 750 mm yr -1 ) µm N µm N <53 µm (organo-mineral) N ( µm N) + ( µm N) + (<53 µm N) ( µm N) + ( µm N) + (<53 µm N) Makoholi (coarse sand) ( mm yr -1 ) µm N µm N <53 µm (organo-mineral) N ( µm N) + ( µm N) + (<53 µm N) ( µm N) + ( µm N) + (<53 µm N) Zimuto (coarse sand) ( mm yr -1 ) µm N µm N <53 µm (organo-mineral) N ( µm N) + ( µm N) + <53 µm N ( µm N) + ( µm N) + <53 µm N Sampling depth (cm) R 2 - value and significance level 0.50 ** 0.21 ns 0.37 * 0.40 * 0.43 * 0.13 ns 0.74 * 0.69 * 0.49 ns 0.66 * 0.04 ns 0.63 ** 0.86 *** 0.71 *** 0.53 ** 0.37 ns 0.54 * 0.60 * 0.33 ns 0.86 *** * = p < 0.05; ** = p < 0.01; *** = p < 0.001; ns = not significant

170 a) POM size: µm y = 0.2x R 2 = 0.50 Maize grain yield (kg ha -1 ) Potential mineralizable N (mg N kg -1 soil) Crotalaria juncea 1.2 t C ha-1 Crotalaria juncea 4.0 t C ha -1 Calliandra calothyrsus 1.2 t C ha -1 Calliandra calothyrsus 4.0 t C ha -1 Maize stover 1.2 t C ha -1 Maize stover 4.0 t C ha -1 Sawdust 1.2 t C ha -1 Sawdust 4.0 t C ha -1 Manure 1.2 t C ha -1 Manure 4.0 t C ha -1 Control Figure 7.6 Relationship between maize yield and potential mineralizable N from the macro-pom fraction in the top 30 cm of a sandy clay loam soil at Domboshawa. This macro-pom N probably influenced the significant relationship between maize yields and total mineralizable N from the three isolated fractions in the top 60 cm of the profile (Table 7.4). Under the similar management at Makoholi, regression analysis showed that mineralizable N from the organo-mineral fraction drives maize productivity (R 2 = 0.86; p < 0.001) (Figure 7.7). This could probably explain the high level of significance (p<0.001) also observed after regressing maize yields with sum of total mineralizable N in the different fractions (0-30 cm). However, under smallholder farmer management in Chikwaka and Zimuto, total mineralizable-n from a 60-cm profile gave the best yield estimates (Table 7.4; Figure 7.8), suggesting the need for regular N charge of the soil profile through organic matter management to improve maize productivity.

171 Makoholi Organomineral fraction: <53 µm Maize grain yield (kg ha -1 ) Y = 13.5x R 2 = Potential mineralizable N (mg kg -1 soil) Crotalaria juncea 1.2 t C ha -1 Crotalaria juncea 4.0 t C ha -1 Calliandra calothyrsus 1.2 t C ha -1 Calliandra calothyrsus 4.0 t C ha -1 Maize stover 1.2 t C ha -1 Maize stover 4.0 t C ha -1 Sawdust 1.2 t C ha -1 Sawdust 4.0 t C ha -1 Manure 1.2 t C ha -1 Manure 4.0 t C ha -1 Control Figure 7.7 Relationship between maize yield and potential mineralizable N from the organo-mineral fraction in the top 30 cm of a coarse sandy soil at Makoholi

172 Maize grain yield (kg ha -1 ) y = 2 5x R 2 = M ine raliza ble N in 6 0 cm p rofile (m g N kg -1 so il) C om posted litter C o m p osted m aize sto ve r C rotalaria juncea F resh litter M anure M ineral N fertilizer T erm itaria C on tro l Figure 7.8 Relationship between maize yield and the sum of potential mineralizable N from the macro- meso-pom and organo-mineral fractions in the top 60 cm of a coarse sandy soil at Zimuto 7.5 Discussion Build-up of POM fractions in soil The results indicate that the fate of newly added C and its distribution within different organic matter fractions in arable soils was a function of organic resource quality, soil texture and rainfall among other things. Application of the different quality organic and nutrient resources resulted in significant differential enrichment of the different POM fractions in soils. The rate of decomposition of organic materials in soil, including roots and root residues, has been known to vary widely due to organic resource quality (Heal et al., 1997; Iritani and Arnold, 1960), thus influencing SOM composition (Oorts et al., 2000; Palm et al., 2001).

173 149 With the exception of Crotalaria, the majority of organic resources used as nutrient sources were of poor to medium quality with either low tissue N concentration and/ or high lignin contents which could have resulted in low turnover due to chemical recalcitrance and microbial immobilization. This could explain the significantly higher proportion of macro-pom ( µm diameter) under sawdust and Calliandra treatments at Makoholi, and for litter materials and manure under smallholder farmer management in Chikwaka and Zimuto. Furthermore, high application rates of particulate materials Calliandra, manure and sawdust appeared to enrich the lower soil depths (below 20 cm), more than low application rates. This implies that high biomass application has the potential to improve to subsoil soil C status due to possible saturation of an already low protective capacity defined by the clay + silt content (Hassink, 1996) of the topsoil layers. This was more apparent in the macro-pom fraction of soils with >88% sand. An apparent decrease in the macro-pom size fraction under Crotalaria treatment may mean that application of high N resources are likely to stimulate mineralization of inherent SOM. Under minimum organic matter management in high rainfall Chikwaka, the organo-mineral fraction under mineral N fertilizer treatment appeared to reduce the relative contribution of organo-mineral C to the total soil C pool, suggesting that high N loading reduces the size of the otherwise stable and recalcitrant fraction (Tiessen and Stewart, 1983) Effect of organic resource quality on POM enrichment The data showed a similarity in the behaviour of POM under Crotalaria and maize stover treatments across the different sites despite their wide differences in quality.

174 150 Despite application of up to 9 t ha -1 of Crotalaria or maize stover biomass, there was no evidence of such biomass loading in the either the macro- ( µm) or the meso-pom ( µm) fraction both materials only accounting for no more than 0.8 kg ha -1 in the topsoil. A possible explanation could have been that at sampling, some weeks after incorporation, a large proportion of the Crotalaria biomass may have decomposed while the period was not long enough for the breakdown of maize stover. Studies on organic matter decomposition have shown that more than 75% of the residue C added to soil was lost as CO 2 through mineralization as in a season (Gregorich et al., 1995), with high quality leguminous materials loosing up to 50% within 10 weeks of incorporation (Chikowo, 2004). The implied high turnover rate of Crotalaria was further substantiated by enrichment of mineralizable N at lower depths under this treatment. The N enrichment in the organo-mineral fraction suggest a more physical rather than chemical interaction with N forms released from high quality materials like Crotalaria since it did not result in significant enrichments of the fraction. The clay fraction has been known to interact with organic substances to form more stable organo-mineral complexes (Ladd et al., 1993). While there is no physical evidence to support this, the results suggest that the chemical quality of the organo-mineral fraction was enriched in terms of N-release. On the other hand, under maize stover management, lack of significant increase in the macro-pom fraction compared to the control was attributed to the low quality and nature of the organic resource. While both maize stover and sawdust had wide C:N ratios, sawdust was already of a particulate nature when it was incorporated into soil while stover material was >2 mm, too large to be integrated in SOM.

175 151 Significant differences observed only in the top 30 cm of the sandy clay loam profile suggest that enrichment to POM in lower depths takes longer than 2 years of consistent organic matter application, except for particulate materials such as manure, which exhibited differences in the meso-fraction up to 45 cm depth. Lack of treatment differences below 45 cm implied that the recovered POM below this depth was not from the different quality organic resources, but were probably due root residues and exudates from a previous maize crop. Further more, soil aggregates below 45 cm are likely to be protected from disruption during tillage (Six et al., 1999) and possibly from forces of erosion given the clear demarcation of size of the organo-mineral fraction between the top 45 cm and the lower horizons (Figure 7.4) Effect of soil texture on POM enrichment In addition to organic resource quality, the nature and extent of managementinduced changes on POM content were controlled by inherent soil textural properties. It was established that the dynamics of SOM and its influence on maize productivity between coarse sands and sandy clay loam soils at Makoholi and Domboshawa, was different. On coarse sands, through its mineralization, the organo-mineral fraction (<53 µm diameter) largely determined crop productivity across different rainfall regimes. On sandy clay loams, it was the amount of mineralizable N from the macro-pom ( µm diameter) fraction that was more important and this was in agreement with findings by Gaiser et al. (1998), which affirmed the lability of this macro-pom fraction. However, at Domboshawa, macro-pom only contributed between 5 and 12% of total soil C pool compared with ~45% for the meso-pom fraction, and thus raises a question on the

176 152 magnitude of influence on crop productivity. Total C contribution for the whole POM fraction was however more than double those reported by Barrios et al. (1996) who concluded that the POM fraction >53 µm diameter (both macro- and meso-pom) contained ~28% of whole soil C. Although the breakdown of both added and native organic matter cannot be elucidated directly from these data, turnover of fresh organic matter has been found to be fastest in the light fraction ( µm diameter) of the SOM pool and 70% of light fraction C was derived from recently added corn residues (Gregorich et al., 1995). Soil organic matter stabilization has been generally attributed to physical protection from decomposition by soil microorganisms (Adu and Oades, 1978; Christensen, 1987; Hassink, 1992; Pulleman et al., 2005), and the protective action by clays (Paul and van Veen, 1978; Dene and Six, 2005). Ladd et al., (1985) found a significant linear relationship between residual labelled C in topsoil and clay contents ranging between 5 and 42%. However, this data showed that the sandy soils either lacked the protective capacity or that application of high loads of organic materials may have resulted in saturation of the protective capacity of the soil since soil C contents increased significantly. There is however a possibility that this increase in soil C could be transitory, since much of the increases were in the macro- and meso-pom fraction implying that the new organic matter was biologically available. This means that the build-up of the different POM fractions on sandy soils is for the major part, dependent on newly added C inputs. Differences in potential mineralizable N under sandy soils suggested that with particulate materials like manure, enrichment of the organo-mineral fraction may

177 153 be possible within one season. Studies with stubble mulch on arable soils showed that the total contribution of POM-C (>53 µm diameter) was reduced by half to 19% of total C compared to native grassland soils (Elliott et al., 1993) followed by an enrichment in the organo-mineral fraction. The sandy clay loams had significantly higher clay + silt contents (topsoil mean of >270 g kg -1 soil compared to < 180 g kg -1 for other sites), which might explain the relationship between the coarser macro-pom and maize grain yields. Microbial inaccessibility rather than composition would explain the significantly smaller proportion of N mineralized from the organo-mineral fraction of the sandy clay loams compared to the sandy soils (Mtambanengwe et al., 2004). Under sandy environments, the organo-mineral fraction significantly impacted on maize yields probably due to enrichment of following decomposition and mineralization of new organic matter. This suggested that the organo-mineral fraction represented a sink for the products of microbial decomposition. Using 14 C- labeled materials, the clay and silt fractions (<100 µm diameter) were found to contain both old and young (new) organic matter after 25 days of incubation (Magid et al., 1996), suggesting that the active fractions of SOM are probably distributed among particles of various size fractions. 7.6 Conclusions Although the macro- and meso-pom fractions are enriched in short-term, it is the quality of the organo-mineral fraction as influenced by the added materials that largely determines observed yield differences on sandy soils. Productivity of sandy soils is therefore dependent on regular/ annual inputs of high quality organic

178 154 matter, as the total amount of C stored in these soils is small. Conversely, on sandy clay loams with >200 g clay kg -1, the macro-pom fraction was a robust index for maize productivity, most likely because this fraction has a relatively long resident time due to better physical protection of this macro-pom against decomposition. Since the macro-pom fraction is the least protected of the three SOM fractions in relatively clayey soils, it is thus more likely to be influenced by short-term organic matter management. There was no added advantage in applying high quality biomass at high rates on coarse sandy soils since the maximum amount of mineralizable N contained within the organo-mineral fraction was limited by the relatively small size of this fraction. High quality organic materials have a distinct role in increasing the quality of SOM in the organomineral fraction while low quality organic inputs have a positive influence in increasing the size of the fractions.

179 155 CHAPTER 8 Particulate and labile C fractions as influenced by organic matter management practices on smallholder farms 8.1 Abstract This chapter focuses on short- and long-term impacts of preferential organic resource allocations to fields contrasting in productivity on sizes and C quality of SOM fractions. An understanding of relationships between maize productivity and labile C fractions in soils under such different organic matter regimes was also sought. Characterization of arable soils into biologically meaningful fractions could provide the necessary understanding to enable smallholder farmers producing crops under constrained soil environments to optimally manage available organic nutrient resources. Options for management of different quality organic materials are required for the predominantly maize-based farming systems of southern Africa. The study was conducted on sandy soil (Arenosols) with and average of 6% clay and 88% sand in Zimuto, Chinyika and Chikwaka smallholder areas of Zimbabwe. Fields perceived by farmers to the most productive (rich) received between t C ha -1 compared to between t C ha -1 in the least productive (poor) fields for two consecutive cropping cycles. The intensity of use of external nutrient sources was apparently dictated by resource endowment. Differences in C inputs were reflected more in meso-pom ( µm diameter) fraction at 13 kg meso-pom kg -1 (rich field) and 5 kg meso-pom kg -1 (poor field), compared to the macro-pom ( µm diameter) and organo-mineral fractions. While there was 100% more macro-pom in rich fields compared to poor fields, the size of the organo-mineral fraction did not differ significantly regardless of differences in C inputs and time over which they had been applied. Organic inputs with an N content of between 10 and 25 mg N kg -1 contribute significantly to the soil POM and A modified version of this chapter is to be submitted as: Mtambanengwe, F. and Mapfumo, P. Particulate and labile C fractions as influenced by organic matter management practices on smallholder farms.

180 156 labile C fractions. In contrast, high quality materials such as Crotalaria juncea (>25 mg N kg -1 ) had more biologically available C and resulted in C enrichment of lower horizons. Application of 1.6 t C ha -1 of C. juncea resulted in similar amounts of total available C as with 6 t C ha -1 in manure (4 g C kg -1 ) within the top 60 cm of the profile in Chikwaka and ~ 1.5 g C kg -1 in semi-arid Zimuto. Labile C under mineral N fertilizer and termitaria soil was low and not significantly different from the control treatments. Under low rainfall in Zimuto, the amount of readily available C was linearly related to maize yields while under high rainfall conditions in Chikwaka, total available C was best related to maize yield (p<0.01). It was concluded that the organic matter management trends segregated against the lessendowment farmers while a preferential allocation of resources to more productive fields resulted in enrichment of labile SOM fractions at the expense of the non-productive fields. 8.2 Introduction Knowledge of transformations occurring within the organic component of the soil matrix is necessary to enable beneficial manipulation of soil organic matter (SOM) by smallholder farmers. In Zimbabwe and many parts of sub-saharan Africa most rural households derive their livelihoods from cultivating depleted soils that are low in SOM. Interest in the characterization of SOM arises from its purported role in nutrient supply and its possible use as an index for soil productivity (Woomer et al., 1994). It has since been concluded that SOM can be separated into several different fractions, the dividing line among the different fractions being their relative responsiveness to land-use and management practices (Parton et al, 1987; Elliot and Cambardella, 1991). Release of nutrients from SOM is dependant on the size of readily usable organic C pool required by microorganisms for energy. Introduction of fresh organic matter provides such energy source if moisture and temperature are favourable. Much of the current understanding on SOM dynamics emanates from detailed studies under controlled and processes driving the transformation of nutrients are now generally understood (Wander et al., 1994; Magid et al., 1996; Gaiser et al., 1998). However, little qualitative information on long-term organic matter

181 157 management on smallholder farmers fields has been undertaken (Mtambanengwe and Mapfumo, 2005). Such long-term management effects among farmers differing in resource-endowment are likely to result in differential enrichment of active SOM fractions. Proper management of critical SOM components should make it possible to increase the efficiency of use of mineral fertilizer. Particle size fractionation has enhanced the understanding of the differential roles of major SOM fractions in nutrient supply. The active microbial biomass pool, nonbiomass active particulate organic matter (POM) components, stabilized constituents and resistant C and N pools have all been successfully isolated (Jenkinson and Rayner, 1977; Feller, 1993). However, challenges still remain in their characterization and quantification of their potential roles in soil productivity. The active fraction, which comprises of a heterogeneous mix of living and dead organic materials that are readily cycled through biological pools, is believed to act as a transformation matrix for organic matter as well as reservoir of plant-labile nutrients (Boone, 1994; Jenkinson and Ladd, 1981). In addition, changes in lability of soil C has been proposed as a measure of sustainability because of its association with the biologically active pool which in turn drives short term (e.g. one season) nutrient cycling. However, the use of the microbial biomass pool as an indicator for C turnover has received criticism because of its susceptibility to stresses in the environment (Mazzarino et al., 1991). Chemical oxidation of labile C (Blair et al., 1995) has been useful as a qualitative index of postulating how the quality of applied organic resource is likely to influence the turnover rates of active SOM fractions. It can therefore be regarded as an index for soil quality in terms of its nutrient supply potential. Because low

182 158 input systems characterizing many smallholder farming systems rely on nutrient cycling from SOM, it is critical to understand the relationships among C inputs, active SOM and nutrient supply characteristics under smallholder farmer management. The aims at establishing the relative influence of annual organic inputs by different farmer resource groups on the size of soil available C pool and how this C accounts for observed maize yield. Specific objectives were to: i. determine patterns of organic resource allocation by smallholder farmers to fields of contrasting productivity potential ii. determine the short- and long-term effects of organic resource application and farmer management factors on enrichment of active SOM fractions in farmers fields iii. quantify the relationship between maize productivity and labile C fractions as influenced by organic matter management factors 8.3 Materials and Methods Selection and monitoring of farm and field sites The study was carried out in three smallholder farming areas of Chikwaka Communal Area, Chinyika Resettlement Area and Zimuto Communal Area (Chapter 3). The soils in Chinyika had an average of 5.4 g C kg -1, 0.7 g N kg -1, approximately 820 g sand kg -1, 80 g clay kg -1 and a ph of 5.2 (H 2 O). Corresponding soil characteristics for Zimuto were 5.6 g C kg -1, 0.6 g N kg -1, 850 g sand kg -1, 84 g clay kg -1 and a ph of 5.3 (H 2 O). Chikwaka soils had similar textural properties to those of Zimuto, and had an average of 5.9 g C kg -1, 0.6 g N kg -1 and a ph of 4.8 (H 2 O).

183 159 Farmer participatory research (FPR) approaches were used to determine soil fertility management practices in each study area. The range of organic inputs available for soil fertility management was established using focus group discussions (see Chapter 6). Based on history of organic matter management practices, at least 20 farms were selected in each of the three study areas. Using local soil fertility indices (Mtambanengwe and Mapfumo, 2005), each host farmer was asked to identify the most productive (rich) and least productive (poor) field or field sections on their farm. This gave a total of 40 field sites per study area. The identified fields were monitored from field preparation to post-harvest land management for two consecutive cropping seasons (2002/03 and 2003/04). Monitoring included type and quantity of organic inputs and their mode of application; time of planting; crop type; weeding regimes; dates of mineral fertilizer application and harvesting. All fields under monitoring were planted to maize, the staple food crop. Organic nutrient sources used by farmers on the monitored rich and poor fields were quantified and analysed for C and N, while mineral fertilizer was quantified in terms of area covered per 50 kg bag or part thereof (Table 8.1). Maize grain yields were quantified from a net-plot measuring 5.4 m x 10 m (54 m 2 in total). In addition to the monitored field sites, one nutrient depleted field site was selected in each study area to test the short-term effects of commonly used organic resources on SOM size fractions and maize productivity. Each of the identified field sites had not received any organic inputs in >7 yrs and had <4.6 g C kg -1, <0.5 g N kg -1, <5 mg P kg -1, < 70 clay kg -1 and ph (H 2 O)<5. The experiments were set-up during the 2003/04 season using resources identified and bulked by farmers (Table 8.2). Crotalaria juncea green manure was included in each of the experiments as a high quality resource at the advice of the researchers.

184 160 Table 8.1 Mean quantities (ranges in parentheses) of organic and mineral nutrient sources used by smallholder farmers on rich and poor fields during the 2002/03 and 2003/04 seasons in Chikwaka, Chinyika and Zimuto Nutrient source Chikwaka (>750 mm yr -1 ) Chinyika ( mm yr -1 ) Zimuto ( mm yr -1 ) Rich field Poor field Rich field Poor field Rich field Poor field Ammonium nitrate (kg ha -1 ) 137 (41-325) 102 (25-243) 120 (15-284) 96 (12-250) 102 (19-237) 93 (21-294) Ash (t ha -1 ) not used not used not used not used 16 (2-53) 0.8 (0.5-1) Compost (t ha -1 ) not used not used not used not used 7 (2-13) not used Compound D* (kg ha -1 ) 158 (62-288) 133 (62-206) 113 (17-227) 72 (9-152) 135 (15-371) 122 (5-321) Manure (t ha -1 ) 17 (6-51) 11 (0.5-31) 3 (0.9-9) 9 (1.5-14) 20 (2-47) 9 (1-19) Termitaria (t ha -1 ) not used not used not used not used 4 (0.4-13) 4 (0.5-13) Woodland litter (t ha -1 ) not used 0.2 (0.1-1) not used not used 22 (11-31) 4 (1-8) Urea (kg ha -1 ) not used not used not used not used 84 (74-94) 67 (55-90) * = Basal compound fertilizer (7%N:6%P:6%K:7%S)

185 161 Table 8.2 Quantity and quality of different organic and mineral nutrient sources used in farmer-managed field experiments in Chikwaka, Chinyika and Zimuto Treatment Application rate N concentration C:N (t ha -1 ) (mg 100 g -1 ) Chikwaka (>750 mm yr -1 )) Crotalaria juncea (0.09) 12 Fresh litter (0.04) 20 Maize stover (0.20) 54 Cattle manure* (0.06) 16 Mineral fertilizer (0.00) n/a Unamended control n/a n/a n/a Chinyika ( mm yr -1 ) Crotalaria juncea (0.09) 12 Fresh litter (0.04) 33 Maize stover (0.02) 56 Cattle manure* (0.08) 21 Termitaria (0.01) 5 Compound D** (0.00) n/a Mineral fertilizer (0.00) n/a Unamended control n/a n/a n/a Zimuto ( mm yr -1 ) Fresh woodland litter (0.09) 32 Composted litter (0.04) 20 Composted maize stover (0.06) 28 Cattle manure* (0.07) 17 Crotalaria juncea (0.09) 12 Termitaria (0.02) 7 Ammonium nitrate (0.00) n/a Unamended control n/a n/a n/a * - The cattle manure had been heap-stored for at least three months prior to incorporation; **- Compound fertilizer (7%N:6%P:6%K:7%S) applied two to four weeks after crop emergence; n/a not applicable; Figures in parentheses indicate standard error of the means

186 162 The organic resources were broadcast and incorporated by hand-hoes to a depth of 0.15 m on plots measuring 4.5 m x 8 m, two weeks prior to planting of a maize test crop at start of the rainy season. A mineral N fertilizer treatment and a nonamended control were also included. In each of the three experimental field sites, a randomised complete block design with three replicates was used Soil sampling and fractionation Because of the general similarity in soil textural properties in the three study sites, detailed measurements to determine the effect of history of organic matter management were only taken from 20 farm sites in Zimuto Communal Area. However, short-term effects of organic matter application on maize yields and SOM enrichment were conducted through farmer-managed experiments in all the three study sites of Chikwaka, Chinyika and Zimuto. Soil samples were collected during the mid-season (early to mid February, 2004) from each of the farmerdesignated rich and poor fields. During the same period, samples were also collected from the three farmermanaged organic matter experiments for analyses. The soils were from 0-20, 20-40, 40-60, and cm depths. Out of the 20 farms in Zimuto, only 12 field sites from six farms were monitored to a depth of 100 cm from fields belonging to three different resource groups namely Resource-endowed, Intermediate and Resource-constrained farmers (Chapter 6). The six paired fields (one rich and one poor) represented three distinct groups of high (>5 t ha -1 ), medium (1-4 t ha -1 ) and low <1 t ha -1 organic matter usage and approximately reflected the farmer s position in resource endowment. For each sampling, soil from three replicate points within a plot was bulked before a composite sample

187 163 was drawn for analysis. Topsoil (0-20 cm) textural properties were analysed using the Bouyoucos hydrometer method while total organic C was analysed using a modified Walkley-Black procedure without external heating following wet oxidation by acidified potassium dichromate (Anderson and Ingram, 1993). Particulate organic matter (POM) was quantified by wet-sieving and floatation (Okalebo et al., 2002) as described in Chapter Measurement of labile C fractions Labile C fractions in soils from 40 field sites from Zimuto and from the three farmer-managed organic matter experiments in Chikwaka, Chinyika and Zimuto was quantified using the potassium permanganate (KMnO 4 ) procedure described by Blair et al. (1995). Using results from organic C analyses, paired soil samples containing an equivalent of 15 mg C were weighed into centrifuge tubes. Standardizing at 15 mg C was found to significantly reduce errors (Blair et al., 1995). One set was extracted using 25 ml of a dilute concentration (33 mm) of KMnO 4, while the other set received 25 ml of 333 mm KMnO 4. The 33 mm KMnO 4 oxidizes the readily labile C compounds while the stronger 333 mm KMnO 4 oxidizes total labile compounds in the soil. The samples were put on rotational shaker for 60 minutes before being centrifuged at 2000 rpm for 5 min. Blank samples (7) set up using decreasing volumes of the two KMnO 4 concentrations starting from 100 to 94 µl and used as standards. For each of the test samples and standards, 100 µl was transferred from just below the surface into a new set of 50 ml glass vials to which 24.9 ml distilled water was added and thoroughly mixed. The amount of C oxidized by the two KMnO 4 was estimated colorimetrically using a UV- visible spectrophotometer, Shimadzu

188 164 BioSpec Model 1601 against the assumption that 1 mm MnO 4 is consumed in the oxidation of 9 mg of C (Blair et al., 1995). The top standard (100 µl) for each set was used as the zero reference Data analyses Data on potential C and N inputs by smallholder farmers in the different sites were analyzed using boxplots. An analysis of variance (ANOVA) was performed for the two-pom and organo-mineral fractions under the different management, and labile C fractions using Genstat statistical package (Genstat for Windows Discovery Edition 1, 2003). Mean separation was tested using Tukey s at p <0.05. Relationships between maize yield and POM size fractions, and labile C fractions were tested by simple and multiple linear regressions. 8.4 Results C and N in inputs allocated to different field types Overall, there was high and diverse use of organic nutrient sources in Zimuto compared to Chikwaka and Chinyika. At least three-quarters of the experimenting farmers using organic amendments in Zimuto applied between t C ha -1 to rich fields compared to between t C ha -1 to poor fields (Figure 8.1). In some cases, farmers applied as much as 14 t C ha -1 to their rich fields in Zimuto. In addition to organic N applied in the different resources, both rich and poor fields also received variable doses of mineral N fertilizer (Table 8.1), resulting in an overall N input of between 25 and 550 kg N ha -1 for rich fields and 25 and 300 kg N ha -1 for poor fields. In Chikwaka, over 80% of the monitored rich fields received

189 165 between 0.5 and 9 Mg C ha -1, while the majority of poor fields benefited largely from mineral fertilizers. Use of organic nutrient sources was not widespread in Chinyika. Only eight out of the 40 monitored field sites received manure inputs and more than half of these fields were designated poor field sites. Farmers in Chinyika largely depended on mineral N fertilizers for crop nutrient supply (Table 8.1; Figure 8.1) Impact of short-term organic matter management on POM size fractions Targeted application of known quantities of different quality nutrient resources showed apparent increases in the macro-pom fraction under organic resources treatments. Incorporation of manure and composted litter increased this fraction by six-fold compared to the unamended control (1.6 g kg -1 soil) under low rainfall area of Zimuto (Figure 8.2). Only composted maize stover failed to significantly improve the macro-pom status of the soil, probably due to its slow breakdown into particles <2000 µm in diameter. Mineral N fertilizer and termitaria treatments in Zimuto did not change the macro-pom status. The same trend was observed in the medium rainfall area of Chinyika where enrichment under manure and fresh litter treatment was significantly higher than the other treatments (Figure 8.2). Under high rainfall area in Chikwaka, the different organic resources exhibited similar increases in macro-pom which ranged between 2 and 3 g kg -1 soil. Mineral N fertilizer application appeared to depress the size of the macro-pom across all sites although this was more apparent under high rainfall conditions in Chikwaka.

190 166 Total C input (kg C ha -1 ) a) C hikwaka (>750 m m yr -1 ) b) Chinyika ( m m yr -1 ) c) Zim uto ( m m yr -1 ) ---- M ean M edian Total N input (kg N ha -1 ) Poor field R ich field Poor field Rich field Poor field R ich field Figure 8.1 C and N inputs from different quality nutrient sources applied to most productive (rich) and least productive (poor) field types under different rainfall regimes of Chikwaka, Chinyika and Zimuto smallholder farming areas (n = 20)

191 167 Enrichment of the meso-pom fraction was particularly significant under manure treatment in Chikwaka (12 g kg -1 compared to < 5 g kg -1 for the other treatments), and Chinyika (9 g kg -1 versus <6 g kg -1 for the rest of the treatments) but not in Zimuto. Soils in Chinyika had the largest size of the organo-mineral fraction in the topsoil, averaging 180 g kg -1. This fraction was apparently not affected by shortterm management changes (Figure 8.2) Effect of organic matter management history on POM enrichment in farmers fields Soils from the 40 field sites in Zimuto showed that POM amounts were significantly higher in fields identified as rich than in corresponding poor fields. Particulate organic matter size fractionation of the soils from farmers fields showed significantly higher amounts of POM in rich compared to poor fields (Figure 8.3). The meso-pom ( µm diameter) fraction in the topsoil averaged 12 g kg -1 soil in rich fields, more than double the amount in poor fields. Despite relative differences in organic matter inputs in the previous cropping seasons, the size of the macro-pom in both rich and poor fields was >10 g kg -1. This implies that the two field types could not be readily differentiated on the basis of the size of the macro-pom fraction contrary to the apparent changes in the meso-pom fraction. The organo-mineral fractions of the two field types did not show any significant differences (Figure 8.3), suggesting that this fraction was not likely to be influenced by short-term management.

192 168 a) CHIKWAKA (>750 mm yr -1 ) b) CHINYIKA ( mm yr -1 ) c) ZIMUTO ( mm yr -1 ) 10 8 POM = µm POM = µm POM = µm Fraction size (g kg -1 soil) POM = µm POM = µm POM = µm 200 organo-mineral (<53 µm) organo-mineral (<53 µm) organo-mineral (<53 µm) Crotalaria juncea Fresh litter Maize stover Manure Mineral N fertilizer Crotalaria juncea Compound D fertilizer Fresh litter Maize stover Manure Mineral N fertilizer Control Composted litter Composted maize stover Crotalaria juncea Fresh litter Manure Mineral N fertilizer Termitaria Control Termitaria Control Figure 8.2 Enrichment of different POM-size fractions following field application of different quality nutrient sources in three smallholder farming areas of Zimbabwe

193 a) POM size ( µm) Fraction size (g 100 g -1 soil) b) POM size ( µm) 40 c) Organo-mineral (< 53 µm) Mean Median Poor field Rich field Figure 8.3 Topsoil (0-20 cm) enrichment of different POM-size fractions for the most productive (rich) and least productive (poor) fields under smallholder management in semi-arid Zimuto Communal Area (n = 20)

194 Soil fertility management strategies by smallholder farmers: The Zimuto case study Soil fertility maintenance involved the use of both organic and mineral fertilizers. However, the intensity of use of the two nutrient sources was apparently dictated by resource endowment. The relatively wealthier Resource-endowed farmers such as Mr Mazarire had access to both manure and mineral fertilizers (Box 8.1). To enhance the productivity of their fields, the less endowed farmers use a variety of organic nutrient sources such as woodland litter and household waste. Mrs Mbokochena represented the Intermediate-farmer group with limited access to manure and used preapplication treatments such as Box 8.1 Soil fertility management strategies at Mr Mazarire s farm using cattle manure Mr Mazarire a very successful Resource-endowed farmer in the Mazambara area of Zimuto. He is a holder of the national Master farmer certificate having successfully undergone training offered by AREX, a national research and extension agency. Mr Mazarire owns 14 head of cattle and has 3 ha of arable land. Most of his children stay away from the farm and labour requirements are met through hiring. Every night, his cattle are penned close to the homestead. Crop residues and grass collected from the veld are added to the cattle pen to provide bedding and extra feed to the cattle, at the same time boosting manure stocks. The manure is applied in sections of the fields rotationally every three-to four years and annually there is usually enough for more than one field. The most productive field on his farm (rich field) lies at the bottom of the catena and usually has enough moisture to allow for winterploughing after harvesting. In this way, he is able to capture and incorporate much of the residues and other non-crop biomass on field surface as a means of boosting the productive capacity of his land. In addition, Mr Mazarire has access to mineral fertilizer which he applies at recommended rates of 51 kg N ha -1 for top-dressing fertilizer and 200 kg ha -1 basal compound D fertilizer (7%N:6%P:6%K:7%S). Apart from proceeds from crop sales, Mr Mazarire receives annual remittances from his sons to buy fertilizer. Because Mr Mazarire has enough draught power, his arable land is usually ploughed twice. Maize yields range between 3-5 t ha -1 for the most productive fields and between t ha -1 for the least productive fields depending on the season. composting to improve the quality of their organic fertilizers (Box 8.2). In some extreme cases, some Resource-constrained farmers do not apply anything to their fields if the Government does not give fertilizer handouts. Such farmers therefore concentrate on selling their labour services to the more resource-endowed groups (Box 8.3). Reducing the area under cultivation and only concentrating on small pieces

195 171 around their homesteads appeared to be the only way of sustaining household food security. Analysis of soils from the six farm reflecting the three identified organic matter use categories (high:>5 t ha -1, medium: 1-4 t ha -1 ) and low: <1 t ha -1 ) had similar textural properties with high sand contents averaging 910 g kg -1 and low clay not exceeding 80 g kg -1 (Table 8.3). Organic C contents of the designated rich fields had at least 24-57% more soil Box 8.2 Soil fertility management strategies at Mrs Mbokochena farm using woodland litter Mrs Mbokochena is a widow who lives with her five grandchildren in the Mazambara area of Zimuto. She falls into the Intermediate farmer group and owns 4 cattle. The cattle do not supply her with adequate manure for her cropping activities on her <2 ha arable land. All her fields are in the top to middle catenary position. Every year during the dry season, her grandchildren assist in the collection of litter from nearby woodland. This, together with cowdung collected from the communal grazing lands, is piled in a pit and composted for use as a soil fertility amendment in the next growing season. Biodegradable household waste and ash are also added to the pit and watered occasionally to get the best product. Before the onset of the rains, the composted materials is collected in wheelbarrows and heaped as wheelbarrow heaps on target areas in the fields. Each season, the composted material is broadcast and incorporated systematically in rotations, with the most productive field sections getting priority. Depending on availability, mineral fertilizer is applied as top-dressing at 25 kg AN acre -1 (~ 21 kg N ha -1 ) Yields range between t ha -1 for the most productive field and between t ha-1 for the least productive field. C than poor fields at the different farm sites (Table 8.3). There was no apparent Box 8.3 Soil fertility management strategies at Mrs Chirakata s farm Mrs Chirakata and her husband are Resourceconstrained farmers who stay with their seven grandchildren on their farm. They have no formal employment and live off hiring out labour to those requiring it, mostly during the cropping season. They do not own any cattle, and if the Zimbabwe government does not give fertilizer handouts, they do all their arable farming with no addition of external inputs. They cultivate their only field of <0.25 ha, which is situated at the top of the catena around their homestead. Higher maize yields are obtained from the area closest to the dwelling (rich section) within a five- metre radius. The portion >15 m from the homestead produces significantly less (poor field). In good years, they are able to harvest about 0.8 t ha -1 of maize grain, insufficient for home consumption. relationship between total soil C and the amount of organic C applied to the different field types in the previous 2 years prior to sampling. However, quantification of macro-pom fraction of the different soils reflected the three identified groups of organic matter management among farmers. This was more apparent in the top 20 cm for the

196 172 designated rich fields (Figure 8.4). A cumulative total of ~40 kg macro-pom ha -1 were estimated in the top 60 cm of profiles of field receiving >5 t organic biomass ha -1 compared to about 24 kg macro-pom ha -1 for fields receiving between 1-4 t organic biomass ha -1. Fields that received no inputs in the previous 2 seasons, the majority of which were poor fields (Table 8.3), had no more than 8 kg macro-pom ha -1 down a 60 cm profile. Macro-POM enrichments in the sub-soil were particularly evident at Mbokochena farm where amounts of ~5 g macro-pom kg -1 soil could be found between cm, compared to <1.5 g kg -1 for the same depth in the other five rich fields (Figure 8.4). Chirakata farm, had received no quantifiable organic C inputs in the preceding two years (Box 8.3), and had ~2 g macro-pom kg -1 soil, probably emanating from root residues and weed biomass from the previous season. Similar trends of organic resource usage observed for the macro-pom fraction were also reflected in meso-pom fraction. For all the tested soils, the size of the meso-pom fraction was more than twice the macro-pom ranging from 8 to 20 g kg -1 soil in the top 20 cm of the profile for rich fields and between 2-16 g kg -1 soil for poor fields. The poor fields at Mbokochena and Mazarire farms had significantly higher amounts of the meso-pom fraction in the sub-soil, below the plough layer, >6 g kg -1 soil. This gave a reflection of at least 3-6 times more meso-pom compared to fields that received <1 t ha -1 organic matter in the preceding 2 years (Figure 8.4). As was the case with topsoil analysis from the all the 40 field sites in Zimuto, the organo-mineral fraction did not show influence of organic resource management in both rich and poor fields.

197 173 Table 8.3 Soil properties and total C applied on the most productive (rich) and least productive (poor) fields on selected farms in Zimuto Communal Area Farmer name Resource group Rich field Poor field C applied Sand Clay C C applied Sand Clay C in 2 yrs in 2 yrs (t ha -1 ) (g kg -1 ) (g kg -1 ) (g kg -1 ) (t ha -1 ) (g kg -1 ) (g kg -1 ) (g kg -1 ) Chirakata Resource-constrained Tauya (H) Resource-endowed Tauya (M) Resource-constrained Mazarire Resource-endowed Mbokochena Intermediate Zivhave Intermediate SED nd nd Nd 0.07 nd nd nd 0.04 nd not determined; SED Standard error of the difference of means

198 174 a) Chikwaka b) Zimuto mM oxidizable C 33mM oxidizable C 0-20 cm depth 0-60 cm depth 1.5 Labile C fraction (mg g -1 soil) mM oxidizable C 333mM oxidizable C Crotalaria juncea Fresh litter Maize stover Manure Mineral N fertilizer Control Composted litter Composted maize stover Crotalaria juncea Fresh litter Manure Mineral N fertilizer Termitaria Control Figure 8.4 Mid-season (February) cumulative labile C fractions from the 0-20 cm and 0-60 cm soil depths following deliberate application of known quantities of different quality nutrient sources in Chikwaka (a) and Zimuto (b) Communal Areas Observed separation of the organo-mineral fraction on different farms was attributed to inherent textural properties e.g. the poor field at H. Tauya farm had 80 g clay kg -1 soil in the top 20 cm, about 160% more clay than at Chirakata farm

199 (Table 8.3). Common to the organo-mineral fraction of both field types was a distinct sudden increase from a depth of about 60 cm (Figure 8.4) C lability and maize productivity Under high rainfall conditions in Chikwaka, short-term organic matter management effect on the readily oxidizable C pool (33mM KMnO 4 - oxidizable C) was no more than 0.4 g kg -1 soil in the top 20 cm. Significantly more readily oxidizable C under the different treatments was apparent in the deeper soil profile of 0-60 cm, ranging between 0.4 and 0.8 g kg -1 soil (Figure 8.5). Despite low application rates for Crotalaria juncea which was about four times less than that of manure and fresh litter (see Table 8.2), results indicated no significant differences among the three resources with respect to readily available C in a 60-cm profile (Figure 8.5) suggesting that C. juncea had high amounts of available C. Total oxidizable C (333mM KMnO 4 oxidizable C) was highest under manure treatment at 5 g kg -1, about 10-times more than amount from the readily oxidizable C fraction. This fraction accounted for at least 80% of observed maize yields in one season of organic resource incorporation (Table 8.4). In semi-arid Zimuto, at least two-thirds of the readily available C in the top 60 cm of the profile was accounted for in the top 20 cm under all treatments except C. juncea where a reverse trend was observed (Figure 8.5). However, although absolute amounts were no more than 0.8 g kg -1, there was a significant linear relationship (R 2 = 0.91; p<0.001) between maize yields and the combined effect of total soil C + readily available C + potential mineralizable N in the macro-pom fraction (Table 8.4).

200 176 POM fraction size (g 100 g -1 soil) Soil depth (cm) D Graph 8 Rich field POM > µm 2D Graph 8 2D Graph 9 Rich field POM > µm Rich field Organo-mineral (<53 µm ) Poor field POM > µm Chirakata H. Tauya M. Tauya Poor field POM > µm Mazarire Mbokochena Zivhave Poor field Organo-mineral (<53 µm ) Figure 8.5 Relative distribution of three different POM fractions under smallholder management on selected farms in semi-arid Zimuto

201 177 Table 8.4 Relationships between maize grain yield and different soil C and N fractions under different organic and nutrient resource management in sub-humid Chikwaka and semi-arid Zimuto Predictor Chikwaka (>750 mm yr -1 ) Total C Readily oxidizable C Total oxidizable C Readily oxidizable C + Min N ( µm) Readily oxidizable C + Min N ( µm) Total oxidizable C + Min N ( µm) Total oxidizable C + Min N ( µm) Total C + Readily oxidizable C + Min N ( µm) Zimuto ( mm yr -1 ) Total C Readily oxidizable C Total oxidizable C Readily oxidizable C + Min N ( µm) Readily oxidizable C + Min N ( µm) Total oxidizable C + Min N ( µm) Total oxidizable C + Min N ( µm) Total C + Readily oxidizable C + Min N ( µm) R 2 -value (0-20 cm) 0.44 ns 0.60 * 0.81 ** 0.35 ns 0.75 * 0.52 ns 0.79 * 0.63 ns 0.76 ** 0.62 ** 0.40 * 0.59 ** 0.55 * 0.44 ns 0.31 ns 0.71 * R 2 -value (0-60 cm) 0.20 ns 0.56 * 0.82 ** 0.46 ns 0.64 ns 0.77 * 0.76 * 0.52 ns 0.66 ** 0.73 ** 0.29 ns 0.86 ** 0.85 ** 0.33 ns 0.65 * 0.91 *** Trends for total oxidizable C were similar to those observed for readily oxidizable C, although absolute amounts under manure the two litter types, composted maize stover and C.juncea, were not significantly different from each other. Mineral N fertilizer, termitaria and the control treatments had no more than 1 g kg -1 soil in the 60 cm profile (Figure 8.5). On the 40 monitored farmers fields, significant differences among the readily available C were apparent between fields that had recently received organic C inputs and those that had received no inputs. Values

202 178 ranged from g C kg -1 in poor fields and from g C kg -1 for rich fields. Regression analysis showed that the readily available C fraction was a better predictor for maize yields than total oxidizable C in the top soil, accounting for at least 18% of observed yield under farmers fields (Figure 8.6). This readily available labile C fraction was also significantly (p<0.001) related to mineralizable N from the macro-pom fraction (Figure 8.6), implying a fast-turn over of the macro-pom fraction Maize grain yield (kg ha -1 ) D Graph 19 y = 1430x R 2 = 0.22; p = Potential mineralizable N (mg kg -1 soil) y = x R 2 = 0.42; p <0.001 Poor field Rich field Readily oxidizable C (mg kg -1 soil) Figure 8.6 Relationship between maize grain yield, mineralizable N and readily available C in the top 20 cm of most productive (rich) and least productive (poor) fields under smallholder farmer management in Zimuto

203 Discussion Implications of organic matter management on fertility gradients on smallholder farms Between 2002 and 2004, an estimated total of 3.0 and 0.5 t C ha -1 was incorporated into the most productive (rich) and least productive (poor) fields in high rainfall Chikwaka. Corresponding values for medium rainfall Chinyika were 0.25 and 0.3 t C ha -1 and 4 and 2.5 t C ha -1 for semi-arid Zimuto. This targeted application of resources to the more productive fields/ field sections resulted in the size of POM (macro- + meso-) of about 14 kg ha -1 for rich fields compared to <7 kg ha -1 for poor fields. Use of organic resources was more widespread under semi-arid conditions in Zimuto where farmers used other organic materials in addition to manure. Farmers are aware of the mulching effects of organic materials in cropping systems in addition to supplying nutrients to growing crops (Chuma et al., 2000). The added organic matter increased the overall size of the POM fraction, suggesting that the productivity potential of this fraction may be dependent on recent addition of C (Gregorich et al., 1995). Moreover, the size of both macro- and meso-pom fractions reflected the farmer s capacity to apply organic nutrient resources. While resource-endowment dictated use of mineral N fertilizers and manure, compost, termitaria and crop residues were among the list of nutrient sources used the less endowed farmers (Elias, 2000; Mapfumo and Giller, 2001). Overall, access to resources and the labour demands associated with organic matter application widened the fertility gradients between the designated rich and poor fields within

204 and between the different farmer-resource groups (Chapter 4; Mtambanengwe and Mapfumo, 2005) Enrichment of POM fractions in farmers fields There was apparently a rapid transformation of added C into macro- and meso- POM under the different organic matter management regimes. Organic resources incorporated into soil are broken into smaller particles and gradually enter the soil matrix through the macro-pom fraction, into the meso-pom fraction and finally the organo-mineral fraction. The final transition into the organo-mineral phase could not be ascertained on the basis of results from this study. Given the consistency in organic matter management by different farmer-resource groups each season, impacts on the size of the organo-mineral fraction was minimal and inconclusive. This could either be a result of stabilization of this fraction through chemical recalcitrance and perhaps physical occlusion (Ladd et al., 1985) or that, farmers do not have access to the type and amounts of organic resources required to enrich this fraction. Such work might warrant the use of 14 C isotopic tracer methods (Amato and Ladd, 1992; Magid et al., 1996), to ascertain the spatial and temporal distribution of organic matter in these porous soils. However, recent work has shown that the type of organic matter used can influence the quality of the organo-mineral fraction in terms of N supply capacity (Chapter 6). The majority of rich fields undoubtedly benefited from annual additions of organic matter. Even in fields with no recent organic matter additions, the meso-pom fraction of designated rich fields was high suggesting that the shift from macro- to meso-pom was a short-term process in these coarse sands, and probably takes

205 181 place within 1-3 years, depending on the quality of the organic resource (Heal et al., 1997). For example, impact to macro-pom fraction following application of <2 t manure-c ha -1 was not significant but the meso-pom fractions under such low organic matter management were more than two-fold within the same season. This may have management implications on both the quality and quantity of organic resources used by farmers. Significant amounts of POM lower soil horizons could not be adequately accounted for in terms of root contributions suggesting that recent additions of organic matter such as manure were probably responsible for C enrichment to a depth of about 60 cm. Such managementinduced sub-soil enrichments were likely due inherent coarse nature of soil in the different smallholder farming systems (Thompson and Purves, 1981; Mapfumo, 1995) Significance of annual organic inputs on labile C fractions The organic matter application threshold for coarse sands was ~10 t ha -1 since application rates higher than that apparently did not change lability of C in the plough layer. This could be attributed a possible attainment of saturation of the protective capacity (Amato and Ladd, 1992; Hassink, 1996) of the coarse sands since only a finite amount of organic matter was likely to be protected from biological attack. Oades (1988) concluded that stabilization of soil organic C was a function the initial C quality of the resource and textural properties that offer various mechanisms of protection offered by soil minerals. It was thus, likely that continuous use of high amounts organic matter inputs enhanced the enrichment of sub-soil layers making them more labile compared to low input rates of <10 t ha -1.

206 182 A strong linear relationship between maize grain yields and both macro-pom potential mineralizable N and a readily labile C fraction suggests that these two parameters may be better determinants of biological lability of process driving nutrient availability. Several studies have shown that nutrient cycling and SOM were closely related through the microbially driven mineralization/ immobilization turnover processes (Duxbury et al., 1989). The KMnO 4 oxidizable C appears to be a promising measure of the active component of soil following suggestions that the previously used highly dynamic microbial biomass pool may be a poor indicator of lability (Mazzarino et al., 1991). Measurements from the organo-mineral fraction indicated that this fraction was less sensitive to short-term management interventions than were the other POM and labile C fractions Quality of applied organic resource and C lability Observed changes in lability of soil C and POM size-fractions at different depths on farmers fields were related to the history of management, the quality of resource incorporated and the amounts at which these were added. The smallholder farming systems are subjected to high N loads (up to >500 kg N ha -1 season -1 ). Results from this study showed that a large proportion of the added N was from organic materials with mineral N fertilizers contributing <30% of the total mineral N. Nitrogen release capacity of most organic resources available on-farm is poor because of the quality of resources from which it is derived and the N is usually not available to benefit crop productivity within the season of application (Chapter 4; Mtambanengwe and Mapfumo, 2005). However, mineral N fertilizer appeared to deplete inherent POM fractions by as much as 30% compared to a

207 non-amended control, raising the question of sustainability of its use under already depleted soils. 183 High C turnover rates and lack of protective capacity (Monreal et al, 1995; Six et al, 1998) of the communal soils were implied when enrichment of the meso-pom fraction was apparent within three months of organic resource incorporation. This was clearly demonstrated under manure and woodland litter treatments. Under C. juncea treatment, lack of quantifiable amounts of topsoil POM and labile C fractions indicated that the C quality in this organic resource was more readily available and prone to rapid mineralization by soil microbes (Palm et al, 2001). This could probably explain the enrichment of labile C at lower depths under this treatment despite its low application rate, suggesting that C charge of the whole profile may be a better predictor of crop yields than the top 20 cm of the soil profile. The implied rapid turnover of high quality materials has implication on the applicability of the carbon management index (Blair et al., 1995; Blair et al., 1997), which has previously been used to estimate declines in soil C under different management systems. Comparatively, manure application rates under the different smallholder systems are high (>18 t ha -1 ) and are likely to impact significantly on the POM and labile C fractions. Furthermore, the quality of manure under most smallholder farming systems is generally poor and may not be readily decomposable (Delve, 2001; Probert et al., 2005). In most cases, the widespread practice of adding lignified materials such as cereal stover, woodland litters and grass to cattle pens to provide both animal bedding and to boost manure

208 quantities (Mugwira and Murwira, 1997) is likely to impact on C availability of the final product Conclusions Regular inputs of organic nutrient resources are a prerequisite in stimulating biological activity and productivity potential of sandy soils in farmers fields since the systems are already C limited. The macro-pom fraction is the most labile of the three isolated SOM fractions, and therefore needs regular replenishment of organic inputs to have a meaningful contribution in N release because of its overall small size. High quality organic resources play an insignificant role in the build-up of POM size fractions, but are more important in influencing the quality of the organo-mineral fractions. While indications are that farmers with access to organic resources prefer to apply it to the more productive portions on their farms to ensure they produce enough maize grain, high C application may serve to boost the biologically available fraction under the different rainfall regimes, is likely to lead to unprecedented nutrient losses. There is therefore potential for better nutrient management through repeated and systematic application of not so large doses of organic nutrient sources, not exceeding 5 t C ha -1 season -1, to improve soil productivity.

209 185 CHAPTER 9 Overall discussion, conclusions and recommendations 9.1 Introduction Soil fertility research over the last decade has provided scientific evidence that improving soil productivity on smallholder farms is fundamental in the attainment of the UN s MDG 1 (United Nations, 2000), which seeks to improve household food security. The state of arable soils, in terms of their productive potential, dictates management strategies within a given socio-economic environment. It is these management decisions that lead to an improved or degraded status of soils under smallholder farming systems through both space and time (Kumwenda et al., 1995). Nutrient loss pathways include nutrient exports through field harvest and residue removal, leaching, erosion and gaseous fluxes operative at different scales from a field scale, through farm-scale to landscape levels (de Jager et al., 1998; Haileslassie et al., 2005). This study provided information on arable field management practices under typical smallholder farming systems in three different agro-ecological regions of Zimbabwe. The data presented here may apply to other farming systems in the high, medium and low rainfall areas of Zimbabwe and other similar environments in sub-saharan Africa. 9.2 Matching farmers perception of soil productivity with conventional science to enhance sustainability Farmers exhibited clear knowledge of soil fertility gradients within and between their farms. Use of descriptors defining soil productivity was consistent regardless of farmer s geographical location or social status. Farmers criteria for separating

210 186 productive from non-productive fields was inclusive of the major physico-chemical and biological factors influencing crop growth at field-level and this was substantiated by results from conventional science (Mtambanengwe and Mapfumo, 2005). Indicators of soil productivity centred on crop performance, soil colour and texture (Chapter 4). Apart from colour differences inherent in the parent material, the major reason why farmers often link soil colour to fertility, is apparently due to the influence of soil organic carbon (SOC). The mean SOC content for rich fields were >6.0 g kg -1 compared with <4.6 g kg -1 for the designated poor fields. Farmer designated rich fields typically had high concentrations of essential nutrients such as N ranging from mg N kg -1 soil and exchangeable Ca and Mg ranging between and cmol (+) kg -1 soil respectively. This was indicative of improved nutrient cycling following cumulative effects of years of preferential resource allocation to rich fields. The congruency between field-level characterization of soil fertility by farmers and researchers suggest that in principle, farmer indicators can reliably be used to target soil fertility technologies at farm scale. Tapping into the indigenous knowledge base can thus be used to complement process research to aid management decisions. 9.3 Resource endowment as an organic matter management factor Both cattle and land ownership were ranked highly as indicators of resource endowment and this was consistent in the different communal areas (Chapter 3). Resource-endowed farmers had more than 10 cattle and >3 hectares of arable land while Resource-constrained farmers had variable farm sizes of between 0.5-3

211 187 hectares and mostly no cattle. It was evident that those Resource-constrained farmers with large landholdings only utilized small portions of total arable land. A third group, the Intermediate farmers, was more diverse comprising of farmers of varying but limited resource ownership. Under the different smallholder farming systems, the size and variability of the Intermediate farmer group that may indicative of the dynamism of technology usage across different production systems. Resource endowment was important in management and allocation of resources to different field types. Three different organic matter management strategies contributing to improved soil C status of arable fields were apparent: 1. Efficient capture of available organic resources: involving capturing in situ organic materials on field surfaces during the post-harvest period. Resourceendowed farmers have the capacity to capture nutrients associated with this management through winterploughing after crop harvest. At least 1.5 t C, 25 kg N and 5 kg P ha -1 can potentially be captured in situ with a likelihood of more nutrients being accounted for under high rainfall environments (>750 mm yr -1 ). Although availability of nutrients from this form of management remains largely unknown, such small inputs could make a difference in raising the productivity of nutrient-depleted soils characterizing most of the smallholder farms. It is recommended that the merits of practice be extended to all farmer groups particularly the Resource-constrained farmers who have no access to external nutrient supplementation. 2. Targeted and sequential application of nutrients from external sources: involving allocation of resources to particular field portions, also known as

212 188 Muforo, due to insufficient acquisition of the required amounts. The wealthier farmers typically allocate resources along different Muforos within the same field using either cattle manure, woodland litter or composted materials. This form of management is carried out on different fields over seasons until the whole field benefits before the cycle starts again. For the Resource-constrained farmers, generating enough biomass quantities to cover a meaningful hectarage remains a major constraint. There is need for both researchers and extension staff to assist farmers broaden the range of nutrient sources available to them, and enrich their knowledge in processes at work in soils. 3. Targeted and repeated application of resources: This is a concentration strategy which involves application of high quantities of acquired resources to identified field portions. This management strategy may not necessarily follow a particular Muforo, but usually targets areas of favourable productivity (rich fields/ field sections). This strategy implies that farmers prefer to invest their labour inputs where returns are already favourable. For the Resource-endowed farmers, amounts can be as high as 50 t ha -1 for manure (Chapter 6 and 8), and in the majority of cases, the same field benefits regularly at the expense of the less productive fields, further deepening the fertility gradients within farms. It was however noted that on Resource-constrained farmers fields, fertility gradients are relatively small due to limited amounts of available resources (Mapfumo and Giller, 2001). The majority of these farmers usually opt to reduce area under cultivation and exploiting the relatively fertile homestead surroundings. Cropping of poor outfields by this farmer group brings a sense of ownership to the land despite losses in investment through seed and labour. The challenge is

213 189 making resources available that could assist farmers manage these differences in land productivity. Strategies that address the efficient use of available resources and increase productivity and profitability of significant proportions of land under cropping should be formulated and promoted. 9.4 Fate of different quality organic resources in cropping systems Organic nutrient sources available for soil amelioration in the different agroecosystems are highly heterogenous and vary in quality and quantity. In addition to the macro-environment, the fate of the different organic materials in soil is governed by their rate of turnover and soil texture. Organic C build-up, N release and productivity potential of the different field types were all a function of differential organic matter management practices by the different farmer resource groups through space and time (Figure 9.1; Chapters 7 and 8). Organic inputs with a high C:N ratios >30 (e.g. woodland litter, manure, sawdust) contributed significantly to the particulate organic matter (POM) fraction of SOM. Separation of POM into macro-pom ( µm diameter) and meso-pom ( µm diameter) revealed that apart from differences in aggregate size, nutrient availability from these two fractions was different. While the macro-pom fraction is the most labile, indications are that the available N pool from this fraction is small (Figure 9.1). Significant impact of this fraction on crop productivity is likely only through regular and timely C inputs of not more than 10 t biomass ha -1 (~6 t C ha -1 for most organic materials). Any additional biomass loads above 10 t ha -1 apparently gave no added yield benefits regardless of biomass type and quality suggesting low thresholds for attaining maximum saturation for sandy soils.

214 190 >6 t C ha -1 C input <1 t C ha -1 Rich field Soil C: >6 g kg -1 Readily available C: 0.5 g kg -1 soil Total available C: 3 g kg -1 soil Maize grain yield: 3-5 t ha -1 Poor field Soil C: >4.6 g kg -1 Readily available C: 0.1 g kg -1 soil Total available C = <1 g kg -1 soil Maize grain yield = t ha mg kg -1 soil 30 mg N kg -1 soil 15 mg N kg -1 soil 20-30% of total C Macro-POM ( µm diameter) 40-50% of total C Meso-POM ( µm diameter) 5-15% of total C 40-50% of total C 5 mg N kg -1 soil 10 mg N kg -1 soil 17.5 mg N kg -1 soil 20-40% of total C 35-55% of total C Organo-mineral (<53 µm diameter) Figure 9.1 Possible enrichment of measurable organic matter fractions in fields differing in their productivity potential. Arrow size shows the magnitude of either C entering the pool (block arrows) or the amount of potential mineralizable N released from the fraction (simple solid arrows) Two seasons of monitoring showed that rich fields received between t C and kg N ha -1 compared with t C and kg N ha -1 allocated to poor fields (Chapter 8). Although the figures appear high and impractical, grain

215 191 yields from under these systems did not reflect any of the high organic matter loads barely exceeding 4 t ha -1. This implies that the majority of soils do not have the capacity to store and protect C. The meso-pom fraction contributes significantly to soil total C contents, ~50%, and its enrichment on sandy profiles occurred within a single cropping season. However, a build-up of both macro- and meso-pom fractions is likely with the inclusion of slowly decomposing organic materials such as woodland litter, maize stover and cattle manure. While the build-up of the organo-mineral fraction is known to be a long-term process beyond the scope of this study, short-term organic matter management practices can enhance the quality and N-release capacity of the this fraction (Chapter 7). Despite it relatively small size, the organomineral fraction is apparently the one that drives crop productivity on coarse sands across different rainfall regimes. 9.5 Optimizing organic nutrient sources for improved maize productivity Evaluation of efficiencies of the different nutrient sources under farmer management revealed that use of mineral fertilizer alone was more profitable since this was a ready source of N. Under organic matter management on farmers fields, grain yields were highest under manure> woodland litter> termitaria> maize stover. It was however noted that on their own these materials might not be enough to enhance crop productivity. It was necessary to include mineral N fertilizer to increase their use efficiency. On sandy soils with < 70 g clay kg -1 soil, crop productivity is dependent on regular/ annual inputs of organic materials to

216 enrich the relatively stable organo-mineral fraction, as the total amount of C potentially stored in these soils is small. 192 Application of high quality resources to such soils enhances the quality, lability and N release capacity of the small but otherwise stable organo-mineral fraction. This possible enrichment from different quality organic resources could account for observed differences in maize biomass as early as two weeks. On heavier soils (<100 g clay kg -1 soil), the larger POM fraction ( µm diameter) correlates better with maize yields. This fraction has a relatively longer resident time due to improved physical protection from degradation. In this instance, maize productivity at two weeks might not be the best tool for estimating grain yields since soil N availability is already high at the beginning of season. Farmers on such soils need to manage N fluxes throughout the vegetative period of maize as this ultimately determines grain yield. Increasing N availability from most organic resources available on-farm is critical since the net-n release from low- to medium- quality resources is around mid- to late growing season (Chapter 6) when the growing maize crop has little use for it. However, the nutrient benefits from such resources are likely to be realized over time. Use of high quality materials increased grain yields, but due the scarcity of high N-containing organic nutrient sources, low quality materials can be manipulated to improve efficiency. Available options include organic/mineral N combinations (Palm et al., 1997) and pre-application treatment methods as opposed to direct application. While the majority of these farmers have a low purchasing power, efforts should be made to promote mineral N fertilizer use. For farmers with access to manure, anaerobic composting of manure in pits has been

217 193 known to improve the quality of manure (Nzuma, 2004). Such technological innovations have been known to reduce N losses before manure is applied to fields, and therefore improve use efficiency. Under high quality organic matter management (e.g. leguminous green manure) between 40-50% of added N was released during the first half of the season and this benefited the maize crop. However, profile N dynamics of sandy soils showed leaching losses maybe as high as 40 kg NO - 3 -N ha -1 within the first three weeks of crop emergence, a period within which the maize crop will not have established efficient rooting systems to capture much of the N (Chikowo et al., 2003). While use of high N loads significantly increased N losses, their use is apparently necessary to maintain the high soil N fluxes required to attain optimum yields. The challenge is to minimize the leaching losses and increase the magnitude of these fluxes. 9.6 Options for improving soil productivity for resource-poor farmers Current available options for soil amelioration are skewed towards the more resource-endowed farmers. It is the Resource-endowed farmers who (i) have access to manure; (ii) have the capacity to transport woodland litter and crop residues; (iii) have access to credit facilities; (iv) own cattle that feed on crop residues on fields belonging to their less endowed counterparts; (v) own draught power to capture off-season in situ biomass. Some of the designated unproductive fields are not poor as perceived by farmers, but simply failure to bring the soil into production through lack of the necessary resources. The major challenge is that of strengthening the capacity Resource constrained farmers to manage their soils

218 194 and ensure food security since most of the sandy soils are unlikely to sustain productivity without external nutrient inputs. These may include: For the few farmers with access to manure, efficient management of this resource including mixing it with crop residues and woodland litter to boost manure quantity before field application (Mugwira and Murwira, 1997). Methods of application of could include spot application to each maize stand as a form of nutrient concentration strategy (Hilhorst et al., 2000). This will maximize use efficiency given that quantity is the major constraint to this farmer group. For the non-cattle owners, available resources cross-cutting across all farmer groups include crop residues, woodland litter and dung collected from the veld. Nutrient release from such resources can be boosted through pre-application treatment methods including pit storage, composting or heaping. This form of management will serve not only to boost farm-level productivity, but also protect their meagre resources. Organic matter management options must therefore aim at regulating the N losses during early crop establishment and regulate N availability within and across seasons. The farmer friendly decision support system for organic N management (Giller, 2000) could be a useful tool in assisting both farmers extension to classify and manage different quality organic resources. Exploring other options such as self- generating indigenous legumes (indifallows) (Mapfumo et al., 2005), which are available across all the dominant agroecozones of Zimbabwe. These provide a ready source of N through biological nitrogen fixation, and would benefit the Resourceconstrained farmers by virtue of their being a non labour-intensive technology.

219 Areas of further research Available information from this study could be used to target technologies aimed at addressing field variability across different levels from field, through farm to landscape taking into account the different farmer resource groups. Knowledge gaps include: Information on production scales and optimum size land required to meet household food security under the different smallholder systems. While organic/inorganic combinations have been found to improve productivity in integrated soil fertility management, more work is still required on: (i) how to generate sufficient OM under poor fertility conditions; (ii) managing the variability in quality and quantity of available resources; (iii) timing of their relative application (iv) the proportions at which the two should be combined and (v) the economics of the combinations. The challenge is to optimise use nutrient use efficiency and minimize individual household requirements for cash and labour. Any possible interactions between nitrate leaching and cation dynamics over long term and their subsequent effect on acidification Policy implications on successful technologies and how these can be promoted for adoption by various farmer typologies. Soil quality measurements within individual farms could be replaced by reflectance measurements including geographical information systems (GIS) to scale-up soil fertility gradients work. Near infra-red reflectance spectroscopy (NIRS) (Shepherd and Walsh, 2002), is a rapid methodological approach which gives indirect integrated estimates of quality parameters for a large number of farm sites in a relatively short space of time compared to conventional methods.

220 196 Validation of generated data through simulation models (Giller and van Keulen, 2001) to simulate the impact of present and past practices, and the effect of alternative future practices including the effects of climatic change. This could help define thresholds the critical for crop productivity on depleted soils and mitigate negative impacts in the quality of both surface and groundwater. A combination of these together with participatory action research will be required to further arrest declines in soil fertility and improve food security at household level.

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237 213 APPENDICES Appendix 1. Monthly rainfall during 2002/03 and 2003/04 seasons at Makoholi and Domboshawa Experimental Stations a) Makoholi = 732 mm = 647 mm 2002/ / Monthly rainfall (mm) b) Domboshawa = 911 mm = 643 mm July Aug Sept Oct Nov Dec Jan Feb March April May June

238 214 Appendix 2. Rainfall distribution during the 2003/04 season in Chikwaka (total = 765 mm), Chinyika (total = 631 mm) and Zimuto (total = 659 mm) C h ik w a k a Daily rainfall (mm) C h in y ik a Z im u t o O c to b e r N o v e m b e r D e c e m b e r J a n u a r y F e b r u a r y M a r c h A p r il M a y

239 Appendix 3: Publications from this thesis 215