Evaluation of the reproductive performance and effectiveness of artificial insemination on smallholder dairy farms in Zambia

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1 Scholarly Journal of Agricultural Science Vol. 3(10), pp October, 2013 Available online at ISSN Scholarly-Journals Full Length Research Paper Evaluation of the reproductive performance and effectiveness of artificial insemination on smallholder dairy farms in Zambia Kabemba MWAMBILWA, Kavwanga E. YAMBAYAMBA and Joseph SIMBAYA Department of Animal Science, University of Zambia, Lusaka. Accepted 13 October, 2013 A study was conducted at eight (8) smallholder dairy cooperatives involving 1037 cows aged between three and eight years. The main objective of the study was to investigate the effectiveness of artificial insemination and the reproductive performance of dairy cows managed under smallholder farms in Zambia. The cooperatives were Kalomo (n=217), Choma (n=262), Magoye (n=132) and Monze (n=214) in Southern Province; Palabana (n=112) in Lusaka Province; Chingola (n=32), Kitwe (n=48) and Mufulira (n=20) on the Copperbelt. Eight year data (2000 to 2007) was used to estimate the number of services required to obtain a pregnancy (NIRP), calving interval (CI) and first service conception rate (FSCR). The data were analysed using the General Linear Model of SAS. The overall mean for NIRP, CI and FSCR were 1.720±0.056, 458±5.4 days and 48%, respectively. Seasons of conception had no effect on the parameters studied. About 25% of the heats detected required two or more services. About 58% of the CI had a length of at least 450 days. Poor heat detection, diseases, nutrition, and lack of record keeping were the major husbandry factors identified which contributed to poor performance. Level of farmers education seemed to be associated with the poor performance in the smallholder dairy sector. Key words: Artificial insemination, records, reproductive performance, Calving interval, Zambia INTRODUCTION There is a general shortage of improved dairy cattle for the farmers under dairy schemes. AI facilities in most dairy schemes are also inadequate and, as a result, most participant farmers are dependent on natural service and those who do not own bulls depend on their neighbours. This situation has contributed to the inability to expand the smallholder dairy sector. To alleviate the shortage of dairy stock in the schemes, in 1979 the Zambian government established a cross-breeding scheme at Batoka with the assistance from the European Economic Commission (EEC). The function of the ranch is to supply in-calf crossbred heifers to small-scale farmers in dairy settlements and smallholder dairy projects. However, production so far has not met the rising demand as more farmers join the dairy industry. In Zambia, AI was introduced by World War II veterans who came to settle in various parts of the country along *Corresponding author. keyambayamba@unza.zm the line of rail. The post-independence government took keen interest in developing AI in the country in the early 1970s using improved semen with technical assistance from FAO and some developed countries. Farmers who required this service were expected to be attended to by a stationed inseminator and in return pay a normal fee for each insemination service (NAIS, 2006). The government, however, withdrew the service within five years following the severe economic recession and the end of the technical assistance. Emphasis is now placed on farmers who are interested in AI and are able to pay for the training. Such farmers are expected to carry out what is termed do it by yourself artificial insemination. However, the effectiveness of this strategy has not fully been evaluated. Currently, there is an upswing increase in smallholder dairy farming in Zambia due to the availing of dairy cows to farmers by Non Governmental Organizations and other stakeholders. Since bulls are not supplied as part of the package, AI is increasingly being used under smallholder dairy management; the effectiveness of this technique, however, is not known.

2 Percentage (%) Scholarly J. Agric. Sci zero mixed extensive supplement(dry) Grazing system Figure1. Summary of the grazing systems among smallholder dairy farmers in Zambia. The main objective of the present study was, therefore, to investigate the reproductive performance and the effectiveness of AI in dairy cows managed under smallholder farms in Zambia. MATERIALS AND METHODS Location of Study A survey was conducted from Eight (8) smallholder dairy cooperatives involving 1037 cows aged between three and eight years. These were Kalomo (n=217), Choma (n=262), Magoye (n=132) and Monze (n=214) in Southern province, Palabana (n=112) in Lusaka province, Chingola (n=32), Kitwe (n=48) and Mufulira (n=20) on the Copperbelt province. Data collection and analysis Data was collected using a structured questionnaire which was administered to individual farmers. A random sample of 30% of the farmers using the AI service in each cooperative was selected. Retrospective data collected from 2000 to 2007 were used to assess number of services per conception (NIRP), calving interval (CI) and first service conception rate (FSCR). After deleting incomplete records, a total of 1037 were used to estimate

3 Percentage (%) Mwambilwa et al Easily Moderately Difficult Accessibility Figure 2. Accessibility of AI service. NIRP, CI and FSCR respectively. Preliminary analysis showed that interaction effects of the fixed factors such as efficacy of insemination, timing, semen quality and breed were not significant hence not included in the model. Data were analysed using the following General Linear Model (GLM) procedures of the Statistical Analysis System (SAS 1998). Y ijkl =m+a j +S k +R l + +e ijkl, Where: Y ijkl= dependent variables (NIRP, CI, and FSCR); m = overall mean; Aj = the effect of the j th area of the i th cow; S k = effect of the k th season of conception, calving or birth; R l = effect of the l th year of birth, conception or calving; and, e ijkl = random error associated with Y ijkl observation. Differences between means were determined when the analysis of variance detected significant effects.

4 Percentage of cows % Scholarly J. Agric. Sci Jer Frei FreiXZeb Local Type of animal Figure 3. Types of Animals kept by small scale dairy farmers RESULTS AND DISCUSSION Grazing Systems The study revealed that 68.8% of the cows under the smallholder dairy system were managed through the extensive grazing management system, 12.02% were supplemented only during the dry season, 11.02% were managed under the mixed grazing system and only 8.16% were managed under the zero grazing system (Figure 1). Under the extensive grazing management systems where cows are given very little supplementary feeding, if any, there is bound to be a negative effect on the reproductive performance of cows subjected to artificial insemination. With these systems, there is generally no guarantee for enough feed for the cows unless a comprehensive supplementary programme supports it, and, the mixing of cows from different herds and different disease status promotes spreading of diseases. As reported by Obese et al. (1999), and Domecq et al. (1997), lack of supplementary feeding in extensively grazed dairy cows affect their reproductive

5 Mwambilwa et al. 395 performance. Frequently, extensively grazed cows are exposed to heat stress, which suppresses estrus activity in cows (Jordan 2003; Rensis et al. 2003; Windig et al. 2005), making heat detection difficult. In addition, exposure to heat stress 1-3 days after insemination induces embryonic death (Ealy et al. 1995), leading to poor conception rate and repeat breeding. Accessibility of AI services The study revealed that 87% of the farmers found it difficult to access AI services such as semen supplies, liquid Nitrogen, AI equipment such as flasks for liquid nitrogen and access to AI technicians (Figure 2). Only 2% of the farmers had easy access to these services. Where these were available, they were usually expensive and beyond the reach of most of the smallholder dairy farmers. Currently liquid nitrogen is only commercially supplied by Afrox Zambia Limited. Farmers have to travel to either Ndola or Lusaka to access it; however, since it is a by-product in the production process, its availability at all times cannot easily be assured. Another important aspect is the supply of semen. Currently the country depends entirely on imported semen stocks from the developed countries; this makes it expensive and prohibitive to most smallholder farmers. Further, the quality of the semen is not verified by independent government bodies at the point of entry into the country. Type of animals kept by smallholder dairy farmers. The study revealed that 65% of the cows kept by smallholder farmers were Freisian-Zebu cross breed, 14% Freisian, 10% Jersey and 11% Local breed (Figure 3). Education Levels of Farmers The majority of farmers interviewed (82.8% of the respondents) had not gone beyond primary school education while only 4.2% had gone up to graduate level. While it is debatable, such a high illiteracy level among farmers is a potential hindrance in breeding of animals through AI because it creates an imbalance between technical demands of the AI technology and the skills of the existing farm laborers. More than 95 % of the farmers in the study did not keep records, while the few records kept were incomplete, inaccurate or not updated. Poor record keeping affects performance of artificial insemination in several ways. Any attempt to improve the efficiency of AI has to be based on an understanding of the most important causes for failure under each specific production system. Traditionally, methods used to gain this understanding rely on accurate recording and analysis of reproductive events such as estrus, services, pregnancies and calvings. However, farmers in the study rarely kept records, and even when available, they did not allow an assessment of the importance of factors such as efficiency and precision of estrus detection by the farmers or incorrect timing of insemination. Without proper records, elements used when reproductive performance is evaluated such as conception rate, number of services per conception, pregnancy rate, day s open, calving interval and many others cannot be measured. Simple, complete and accurate records about the entire reproductive life of the dairy cow are required to monitor components contributing to reproductive management. This aspect of management needs to be improved. Poor record keeping has been reported to be one of the major management attributes affecting AI in dairy cows (Heersche and Nebel, 1994; Abeygunawardena, 1998). Incidence of diseases Figure 5 shows the incidences of reproductive disorder among smallholder dairy farmers in Zambia. In all the cooperatives under study, farmers in the study used nonreturn to heat days after service as a sign of pregnancy. However, while this may be considered the easiest and cheapest method of pregnancy diagnosis, it requires keen and timely observation superimposed on heat detection skills for it to be accurate. As reported by Senger (1994), the efficiency of non-return rate is further confounded by embryonic mortality, which results in lower calving rates. This method further suffers the disadvantage that farmers are generally not keen to follow up on heat detection on the same cow after insemination. Because of these shortfalls, rectal palpation remains the most reliable, efficient method of pregnancy diagnosis. However, its requirement for skilled labour may explain why it is not a favorite with the farmers. Regardless of when and how pregnancy diagnosis is carried out, the identified reproductive problems affect performance of AI through poor conception, embryo mortality, and abortion, hence farmers might be justified in their complaints on poor pregnancy rate in dairy cows subjected to artificial insemination. However, it must be noted that problems such as dystocia, retained placenta, and abortion, are under the direct influence of the reproductive system of the cow. In this study the incidences of dystocia cases was estimated at 17%. This is a high rate which could be a direct effect of poor bull selection by technicians as well as poor nutrition leading to loss of condition in most cows. For that reason, these factors are somewhat difficult to manage and control because the cow s reproductive system is the primary component influencing the outcome. Nevertheless, reduction in the incidence of dystocia can almost always occur when sires used in AI are selected for a high

6 Percentage (%) Scholarly J. Agric. Sci N.S PS Cl GrL Educational Level Figure 4 Educational levels among smallholder farmers in Zambia (NS= Never attended School, PS= Primary School level, CL= College level and GrL= Graduate level) degree of calving ease especially in heifers. Further, calvings should be supervised by attendants with the appropriate obstetrical skills. Thus, management can exert a strong preventive influence by keeping records and selecting calving-ease bulls for use in heifers and employing proper heifer management and maternity pen care. Further, a good reproductive health program, which provides for checking normal uterine involution and return of ovarian cyclicity, is required. Apart from specific reproductive disorders, a high prevalence of general systemic diseases in most of the cooperatives visited such as East Coast Fever (ECF), black leg and lumpy skin (to mention but a few) were mentioned. These diseases result in sickness and/or

7 Percentage (%) Mwambilwa et al None Abort RP Dystokia Type of Disorder Figure 5 Incidence of reproductive disorder among smallholder farmers in Zambia. (RP= Retained Placenta) death of cows. In particular, ECF can have severe impacts on exotic cattle. Diseases, whether associated with the reproductive system or other systems of the body, have deleterious effects on fertility of dairy cows (Kinsel and Etherington 1998). The high prevalence of diseases for which disease control technology such as effective vaccines, and acaricides is available may be taken to reflect failure of veterinary extension. Number of Inseminations Required in Obtaining a Pregnancy Table 1 shows the number of services required per conception. The number of services required to obtain a pregnancy ranged from 1.41 to 2.56 straws with an average of 1.81 straws. The NIRP for Choma and Magoye did not differ significantly. Kalomo recorded the

8 Scholarly J. Agric. Sci. 398 Table 1. Number of services required to obtain a pregnancy Cooperative NIRP Choma 1.41±0.213 a Kalomo 2.56±0.121 c Magoye 1.45±0.203 a Kitwe 1.93±0.056 b Palabana 1.91±0.307 b Monze 1.84±0.387 b Chingola 1.72±0.176 b Mufulira 1.80±0.056 b Overall 1.81±0.056 a,b,c, Means within the same column differ at P<0.05 highest number of services per conception. The rest of the cooperatives did not differ significantly. However, it is important to note that at least 25% of the cows required two or more inseminations to conceive. The number of services (1.81±0.056) reported for the cooperatives under the study is closer to the range given for well managed herd (McDowell 1985) and similar to the estimates for different breed groups at Abernosa Ranch (1.7) (Mekonnen et al. 1993), Holeta Research Centre (1.72) (Gifawosen et al. 2003) and smallholder dairy farms (1.6) (Lobago et al. 2006) but lower than the estimates obtained for crosses in Asela farm (2.15) (Yohannes et al. 2001) and commercial farms (2.0) (Asseged and Birhanu 2004). Calving Interval Table 2 outlines the calving intervals determined for the different cooperatives under the study. Palabana had the highest number of days open and calving interval. This was also reflected in the number of inseminations required to obtain a pregnancy in this area. This could be attributed to a number of factors. The area could have a high number of repeat breeders possibly due to poor semen handling practices, poor heat detection by the farmers and poor insemination techniques by the operator. As can be observed in Figure1, 68% of the cows were managed under the extensive grazing system; as a result they tended to severely lose weight and body condition score (BCS). This is associated with anovulation and anestrus in dairy cattle leading to prolonged calving intervals. The population mean of 458 days is in agreement with the estimates documented in Ethiopia for F 1 crosses ( Teferi 1994), upgraded dairy cows (Goshu and Hegde 2003) and Friesian cows (Melaku 1994). The long CI observed could be due to the higher NIRP and DO among the the cooperatives. Yoseph et al. (2000) reported even longer CI in the urban and peri-urban dairy production systems due to extended lactation length. This could be due to unnoticed cycles, early loss of embryo and late resumption of ovarian activity. Proportion of Cows Conceiving at First Service Table 3 shows the distribution of first service conception rates in the cooperatives in the study. The first service conception rate in the smallholder cooperatives under review ranged from 38% in Choma to 58% in Magoye with the overall conception rate estimated at 48%. While overall average was low, it is worth noting that 50% of the cooperatives have conception rates below average. This could be directly associated with the difficulty of accessibility of AI services by most of the farmers in the study. Different authors have reported variable figures regarding the conception rates at first service to AI. Geleto (1991), found a pregnancy rate of 62% and 68% for Boran cows at ILRI Derbe Zeit Research Station in Ethiopia. Even much higher rates were reported by Galal et al. (1981) of 70%, 75% and 85% for local cows in wet, dry and humid research stations respectively. Compared to 48% found in this study, their cows were all managed under a controlled environment with proper management. Secondly, while most of our farmers used Freisian-Zebu cross breeds, the animals in the experiments referred to above were all pure breeds. This could certainly have contributed to the higher conception rates recorded. The most limiting factor in AI programs is the proper detection of cows or heifers in estrus. Where AI is the means of breeding the females, the herdsman must recognize and interpret a cow s heat signs. Proper timing of the AI is necessary to accomplish a high percentage of conceptions in the cows that are bred artificially. However, under the extensive management system, cows are left under the care of children who usually do not understand heat signs and its importance. CONCLUSIONS Artificial insemination is a comparatively sophisticated technology of animal breeding whose impact on cattle development is closely associated with the simultaneous introduction of reasonable standards of animal husbandry. In the present study, the major basic animal husbandry practices were below expected standards. Poor heat detection, diseases, nutrition, and lack of record keeping were the major husbandry factors identified that needed further investigation. The education level of most farmers seemed to be a major factor. Training is needed to uplift management capacity of most of the farmers because most, if not all, of the factors identified fall directly or indirectly under the control of the individuals performing the task or making a decision about the task. It is a fact that fertility factors controlled by human, can be improved significantly with the appropriate management decisions and implementation of well-

9 Mwambilwa et al. 399 Table 2. Calving intervals and open days Cooperative No. of cows Recorded Calving intervals (days) Days open Choma ±23.4 b 133±21 b Kalomo ±9.9 b 161±11 ab Magoye ±12.9 c 145±13 ab Kitwe ±27.9 b 137±20 b Palabana ±10.8 a 212±11 a Monze ±25.4 b 152±25 ab Chingola ±11.9 a 194±10 ab Mufulira ±18.6 c 156±17 ab Overall ± ±5.4 a,b,c Means within the same column differ at P<0.05 Table 3. Percentage of cows conceiving at first service Cooperative Number Recorded Conception Rate (%) Choma Kalomo Magoye Kitwe Palabana Monze Chingola Mufulira Overall focused herd health, production and reproduction management programmes. For example, greatest improvement in reproductive performance can be made by improving estrous detection efficiency, estrous detection accuracy, nutritional management, and record keeping, among others. The probability of successfully implementing and controlling most of the factors identified in this study is much higher than attempting to control other factors, which cannot be totally controlled by the management team. ACKNOWLEDGEMENT We wish to profoundly acknowledge the financial assistance from the Ministry of Livestock and Fisheries, particularly the office of the Deputy Director, Livestock, Dr. Benson Mwenya. Without his commitment and support to the study, it would have been very difficult to collect data. Also appreciated is Mr Makabaniso Njhovu of World Vision Zambia for his material and moral support. REFERENCES Abeygunawardena, H. (1998). A review of cattle and buffalo breeding activities in Sri Lanka, Sri Lanka Vet. J. 45: Asseged, B. and Birhanu, M. (2004). Survival analysis of calves and reproductive performance of cows in commercial dairy farms in and around Addis Ababa, Ethiopia. Trop. Animal Health and Prod. 36: Domecq, J.J., Skidmore, A.L., Lloyd, J.W. and Kaneene, J.B. (1997). Relationship between body condition scores and conception at first artificial insemination in a large dairy herd of high yielding Holstein cows. J. Dairy Sci. 80: Ealy, A.D., Howell, J.L., Monterroso, V.H., Aréchiga, C.H. and Hansen, P.T. (1995). Developmental changes in sensitivity of bovine embryos to heat shock and use of antioxidants as thermoprotectants. J. Animal Sci. 73: Galal, E.S.E., Beyene, K. and Azage, T. (1981). A study on the reproduction of local zebu and F 1 crossbreed cows. II. Age at first calving and calf production. Ethiopian J. Agric. Sci. 3: Goshu, G. and Hegde, B.P. (2003). Age at first calving, calving interval and milk yield performance of Friesian-Boran crossbred cattle at Cheffa state farm, Wollo, Ethiopia. Bulletin of Health and Production in Africa. 51: Geleto, A. (1991). Effects of nutrition and partial suckling on lactation and reproductive performance of primiparous Boran cows and on growth of their progeny. DVM Thesis. Faculty of Veterinary Medicine, Addis Ababa University, Ethiopia Gifawosen, T., Alemu, G., Azage, T., Diediou, M.L. and Hegde, B.P. (2003). Study on reproductive efficiency of Boran and its crosses at Holetta research farm: Effect of genotype, management and environment. Ethiopian J. Animal Prod. 3: Heersche, G.J. and Nebel, R.L. (1994). Measuring efficiency and accuracy of detection of estrus. J. Dairy Sci. 77: Jordan, E.R. (2003). Effects of heat stress on reproduction. J. Dairy Sci. p. 86. Kinsel, E. and Etherington, W.G. (1998). Factors affecting reproductive performance in Ontario dairy herds. Theriogenol. 50: Lobago, F., Bekana, M. and Gustafsson, H. (2006). Reproductive performances of dairy cows in smallholder production system in Selalle, central Ethiopia. Trop. Animal Health and Prod. 38: McDowell, R.E. (1985). Crossbreeding in tropical areas with emphasis on milk, health and fitness. J. Dairy Sci. 68: Mekonnen, T., Bekana, M. and Abayneh, T. (2009). Reproductive performance and efficiency of artificial insemination smallholder dairy

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