Influence of Cotton Breeding on Yield and Fiber Quality Problems

Transcription

1 Influence of Cotton Breeding on Yield and Fiber Quality Problems W. R. Meredith, Jr. USDA-ARS-CGP Stoneville, MS Over the years, we ve heard of various states or areas having specific fiber quality problems. Some examples are sticky cotton, high micronaire, poor grades (color and leaf), staple length, uniformity and seed coat fragments. The cause or causes of these problems may be due to crop management, pests, weather, harvesting, ginning, and of course, varieties. All major cotton producing areas have had these problems and now it has become Georgia s time. My interest, as a geneticist, is to design studies to determine the affect varieties may have on a specific fiber quality problem. My approach will be to first use historical data with yield as a reference point and then fiber quality. Yield does impact fiber quality. This will be followed with a few examples of how weather can impact yield and fiber quality. Finally, I ll review some of the latest results from the 2004 Regional High Quality study. The average Mississippi lint yield for the years 1981 through 2004 are shown in Figure 1. For the past 24 years, yield has increased at an average of six pounds/acre (Prob. = 0.08) per year. My interpretation is that the increase in yield is due to the sum total effects of new technology; pest control, crop management, harvesting, and improved varieties. The individual years deviate considerably from each other, varying as much as a half bale per acre acreage from one year to the next. These large year to year deviations are mainly due to uncontrolled effects such as weather and pest control and not grower inputs

2 The Mississippi historical data for fiber length and micronaire are given in Figures 2 and 3, respectively. Average fiber length has changed little in 24 years and micronaire has increased mostly because of the use of high micronaire varieties. While variety tests show little average improvement in fiber strength and uniformity, regression analyses over the past 24 years show significant increases in these traits (Figures 4 and 5, respectively). Both growers and ginners pay more attention now to fiber quality than they did 10 to 15 years ago. The average percent change in these traits is given in Table 1. All increases in technology progress are not due to varieties. The average effect of maximum July August temperature (national Weather Service, 2005) on yield, staple, length, and micronaire are shown in Figures 6, 7, and 8, respectively. The total variation among years due to high July August temperatures are compared with the influence of technology progress in Table 1. Temperature has had a major effect on yield, staple length, and micronaire and to a lesser degree on fiber strength and uniformity. The variability analysis from many years of variety testing across the US was presented at this Conference in 2001 (Meredith, 2001). A brief summary of that table is presented in Table 2. The location influence on yield and fiber colorimeter Rd and +b is high, accounting for 80, 81, and 74%, respectively of the total variance across years of testing. The location effect for length, strength, and micronaire was 31, 51, and 61%, respectively. Short fiber content has been discussed as a factor in Georgia s 2003 problem. The AFIS instrument allows an estimate of short fiber content that seems to be correlated with textile mill performance. It allows an estimate of short fiber content that was previously not practical to obtain. The short fiber content (SFC (w)) comparison of three varieties or strains is given in

3 Figure 9. The data reported is from two replications at six locations involved in the 2004 Regional High Quality Study. The data show consistent differences due to genetics and also that the location effect is large. The impact of short fiber content is known to increase waste and reduced spinning efficiency at the textile mill. Variety short fiber content ranged from 2.9 to 5.7% across multiple environments. This points to a need to reinforce varietal improvement in short fiber content. The large variation across locations, ranging from 3.5 to 5.2%, also indicates that the multiple effects of locations, weather, crop culture, harvesting, and ginning also needs further investigation. The future improvements in yield and fiber strength combinations are not only possible but probable as shown in Figure 10. The yield and fiber strength data are from six locations in the 2004 Regional High Quality Study. One entry, MD 9ne, shows a significant deviation above the usually strong negative association of yield and fiber strength. A summary of other comparisons of yield, and fiber traits for DPL 555BG/RR and MD 9ne are given in Table 3. While at this time the F2:5 entry, MD 9ne, is only a promising strain, its potential usefulness is limited because of its yield. The breeding focus on Mid South cotton varieties has been to increase yield as the marketing system s rewards for improving fiber quality are not equal to the rewards for increasing yield. In the future will this marketing system need modification in order for the US cotton industry to adjust to changing textile industry and world competition needs? In each instance, the US cotton industry has identified a specific fiber quality problem, such as sticky cotton, high micronaire, poor grades, and seed coat fragments, there has always been a positive response to that problem.

4 REFERENCES Meredith, W. R., Jr Changes in Yield and Quality Due to Genetics and Climatic Factors EFS System Conference Proceedings. Appendix 1. Greenville, SC June 9 11, Mississippi Agricultural Statistical Service. Weekly Weather Crop Report. Last Updated 05/12/05. National Weather Service, Cooperative Observing Station, Stoneville, MS.

5 Table 1. Percent change per year (regression coefficient) for Mississippi average yield and fiber traits and percentage of total variation among years that can be accounted for by technology progress (regression equation on years) and on July August maximum temperature. All data for years. Percent of total variation (R 2 ) due to: Trait Regression coefficient % change/yr Relative to mean Technology f (P, %) July Aug. temp. Yield, lbs/ac (0.77) 21.3 (0.023) Length, 1/32s (0.356) 34.6 (0.003) Uniformity (0.05) 0.9 (0.713) Strength, HVI (<0.001) 0.2 (0.825) Micronaire (0.002) 17.8 (0.040) f Technology progress effect is measured by regression of year on the specific trait. Table 2. Average proportion of total variance components associated with locations, varieties, and their interaction for yield and fiber properties (Meredith, 2001). Characteristic Locations (E) Varieties (G) G X E Yield % Span Length Uniformity Strength (T1) Micronaire Colorimeter, Rd Colorimeter, +b Table 3. Comparison of DPL 555BG/RR and MD 9ne from six 2004 Regional High Quality Studies.. Genetic type Characteristic DPL 555BG/RR MD 9ne Yield, lint/lbs./ac Staple length Stelometer strength (T1) Micronaire Short Fiber content (w) %

6 YIELD PROGRESS = X R 2 = 13.5 % (PROB = 0.077) MEAN = 758 LBS/AC LINT PER ACRE X = YEARS AFTER 1900 Data source: Mississippi Agricultural Statistical Service. Weekly Weather Crop Report. Figure 1. Average Mississippi lint yield (lbs./ac) FIBER LENGTH 1/32 INCHES LENGTH = X R 2 = 3.9 % (PROB = 0.356) MEAN = X = YEARS AFTER 1900 Data source: Mississippi Agricultural Statistical Service. Weekly Weather Crop Report. Figure 2. Average Mississippi length (1/32 in.)

7 48 47 MICRONAIRE = X R 2 = 36.6 % (PROB = ) MEAN = 44.2 MICROANIRE X = YEARS AFTER 1900 Data source: Mississippi Agricultural Statistical Service. Weekly Weather Crop Report. Figure 3. Average Mississippi micronaire STRENGTH = X R 2 = 70.2 % (PROB = < ) MEAN = STRENGTH X = YEARS AFTER 1900 Data source: Mississippi Agricultural Statistical Service. Weekly Weather Crop Report. Figure 4. Average Mississippi strength

8 UNIFORMITY UNIFORMITY = X R 2 = 23.5 % (PROB = ) MEAN = X = YEARS AFTER 1900 Data source: Mississippi Agricultural Statistical Service. Weekly Weather Crop Report. Figure 5. Average Mississippi HVI uniformity index

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