REPEATABILITY OF STABILITY ESTIMATORS FOR GRAIN-YIELD IN WHEAT

Stability statistics that are used to explain genotypic response to environments are not useful to plant breeders unless they are repeatable across sets of environments. The purpose of this study was to examine the repeatability of the stability estimators: regression coefficient (b(i)), regression coefficient away from mean regression (\b(i) - 1 \), mean squares for deviation from regression (Sd(i)2), Shukla's stability variance (sigma(i)2), variance of genotypic means (S(i)2), and genotypic coefficient of variation (CV(i)), in addition to coefficient of determination (r(i)2) and mean yield (X(i)BAR). These statistics were calculated from three sets of yield data of the Louisiana Agricultural Experiment Station winter wheat (Triticum aestivum L.) performance trials grown in 36 environments. Repeatability was estimated by Spearman's rank-correlation coefficient and Kendall's coefficient of concordance. The \b(i) - 1\, sigma(i)2, and Sd(i)2 were not repeatable between any two subsets of environments, and repeatability of S(i)2 and r(i)2 s were low. Among the stability estimators, only b(i) and CV(i) were repeatable across subsets of environments. The CV(i) was not a reliable statistic to describe genotypic stability because the rank order of CV(i) was induced by the rank order of X(i)BAR. Mean yield was the most repeatable genotypic character. Gain in selection for yield stability can be expected from the combined use of b(i) and X(i)BAR. If data do not fit the linear regression model, then low values of S(i)2 (Type 1) or Type-4-variance (variance of genotypic means across unpredictable environments averaged across predictable environments) may be used as an alternative criterion for yield stability.