Regression analysis of yield stability is strongly affected by companion test varieties and locations - examples from a study of Nordic barley lines.

The suitability of regression analysis for studying the phenotypic stability of grain yield was investigated using a collection of 220 Nordic barley lines. Linear regression explained 26-52% of the genotype x environment (GE) interactions in different groupings of the material. The regression coefficient, b i , measures the yield response of the i-th genotype to improved environmental conditions. Deviations from regression, S di (2) , have been used to estimate Tai's stability parameter, λ i , which is a measure of the phenotypic yield stability in the agronomic sense. Repeatability of b i , λ i , and grain yield was studied by means of correlations between estimates obtained in each experimental year. Yield had the highest repeatability, with correlations between years ranging from 0.57 to 0.85. In this study, regression coefficients and λ i -values were not repeatable, i.e. genotypes reacted differentially to the yearly climatic variations. Six-rowed (6r) barleys had higher responsiveness, but lower mean yields, than two-rowed (2r) barleys. This is partly due to the history of selection of 6r-barleys, which mainly originate from regions with low potential yield levels, i.e. Finland and Norway. In general, responsiveness and stability were not correlated with yield. The highest-yielding lines had b i ≈1. The response pattern of the different types of barleys used in this study show that responsiveness can be changed by recombination.