Breeding soybean (Glycine max. L. Merr) varieties for single- versus double-crop production systems

Soybeans [Glycine max. (L.) Merr.] are grown throughout the southeastern United States as both a single crop and as a second crop following small grains. Varieties currently grown in both systems were developed under conventional, mono-crop conditions. Concern over the development of current varieties has prompted researchers to question if these varieties are best suited for double-crop production or if new varieties should be developed which are specifically adapted for double-cropping. Twenty-five determinate and 25 indeterminate F^-derived breeding lines were evaluated for seed yield in conventional (tilled seedbed, optimum planting date, wide rows) and double-crop (wheat stubble seedbed, mid-June planting date, narrow rows) nursery environments to determine: 1) if relative yield of lines was similar in the two systems, and 2) if indeterminate lines were higher yielding than determinate lines under double-crop conditions. The tests were conducted at 26 location/year combinations in 1982-1986. The 50 lines were separated into two groups based on overall means from the 26 combinations: 1) a superior group consisting of 17 lines which yielded above the overall mean in both conventional and double-crop nursery environments, and 2) a non-superior group consisting of all other lines. Genotype X nursery environment interactions were significant for both the superior and non-superior groups, but the magnitude of interaction was twice as great for the non-superior group. Stability analysis showed that the superior group had significantly higher mean regression values than the non- superior group in conventional tests, but there was no difference in double-crop tests. Selection of the top lines based on means from combinations of one, two, three, and four conventional tests in 1985, and combinations of one, two, three, and four double-crop tests in 1985, each produced up to 65% of the superior lines. The best breeding line was selected in every case. Mean yield differences were not significant between growth types in conventional tests, but determinates were significantly higher yielding than indeterminates in double-crop tests. The results from this study indicate there is no immediate need to maintain separate selection nurseries to enhance the development of soybean varieties adapted for double-crop production systems

Using mixed linear models and best linear unbiased predictions to predict seed yield in soybeans

Best linear unbiased predictions (BLUP) from mixed linear models have been used to predict breeding values of dairy sires for milk yield based on information from their dams and daughters. One of the major advantages of BLUP is that predictions of individuals can be made when information on the individual per se is unavailable, but information from its relatives is available. Since BLUP methodology can utilize information from individuals per se and their relatives to predict the value of individuals, there is potential for its use in two important areas of plant breeding: i) predicting breeding values of parents from the performance of their relatives, and ii) ranking new genotypes when observed data for them are limited (e.g. early stages of performance testing). The objectives of this dissertation were to i) compare the efficiencies of BLUP and MPV in determining seed yield performances of future soybean (Glycine max (L.) Merr.) crosses from historical information about parents, ii) determine the effects of progeny and grand-progeny yield performance information on breeding values of their parents, iii) compare seed yield predictions from BLUP to a traditional approach of estimation, best linear unbiased estimations (BLUE), for ranking new genotypes from a limited number of yield tests, and iv) develop a computing strategy for utilizing BLUP in plant breeding applications. The F4-F6 bulks and F5:6, lines from 24 crosses and four parents were evaluated in replicated yield trials in 11 environments to establish their relative seed yield performances. A summary of the results was; i) predictions of the 24 crosses from BLUP using only historical parental data were better indicators of performance than estimates from MPV, ii) BLUP breeding values of parents were more precise using small amounts of progeny information than when using large amounts of grand-progeny information, iii) BLUP was superior to BLUE for ranking new genotypes evaluated in a limited number of performance trials, and iv) computer software was developed using SAS/IML™ for computing BLUP values in plant breeding applications. The BLUP methodology should be considered a superior alternative to traditional approaches to genotypic performance estimation