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There are many statistics to assess cultivar yield stability: some deal with genotype × environment interaction (GEI) patterns ( b i , and interaction principal component scores), some with GEI noise ( s 2 di ), some with total GEI sum of squares ( ), and others with rank changes S (1). Our objective was to assess the repeatability in soybean Glycine max (L.) Merr. of different yield stability statistics. We evaluated nine statistics derived from additive main effects and mnitiplicative interaction (AMMI) analyses, regression coefficients from analyses using either yield‐based or plant height‐based environmental indices, as well as , S (1). Yield data were from Arkansas trials of maturity group V cultivars from 1987 to 1994. Stability analyses were warranted because GEI was significant, partitioning of GEl sum of squares by AMMI or regression techniques was generally significant, and all stability statistics found significant differences among the cultivars. The AMMI‐derived stability statistics produced information on cultivar stability that was similar to that produced by s 2 di and . The repeatability of cultivar rankings for s 2 di , , S (1), and most AMMI statistics, estimated in different single‐ or two‐year periods were low, indicating that these statistics would not be useful to breeders or growers selecting for stability. The repeatability of two regression coeffacient statistics and one AMMI‐derived statistic were moderate, particularly when estimated over environments from 2 yr. Each of the three statistics relates to a different concept of stability and may be useful to growers and breeders attempting to select cultivars with predictable yield across environments.
Sneller et al. (Sat,) studied this question.