The use of parametric and non-parametric measures for selecting stable and adapted barley lines

Abstract

ABSTRACTThis research was carried out to estimate yield stability of 18 barley breeding lines using different parametric and non-parametric statistics across 15 environments during 2012–2015 growing seasons. The results of combined analysis of variance (ANOVA) and additive main effect and multiplicative interaction (AMMI) analysis showed that environments (E), genotypes (G), GE interaction, as well as the first four interaction principal component axes were highly significant, suggesting that the lines interacted differentially with environments, so further general adaptability and stability analysis across environments should be followed before being introduced for cultivation. Based on correlation coefficient and principal components analysis (PCA), most of the non-parametric statistics were significantly inter-correlated with parametric statistics, hence seem to be suitable alternatives to complement parametric statistics. Furthermore, according to the static and dynamic concepts of stability, the results revealed that stability statistics can be clustered into three groups. The overall stability analysis following different stability methods concluded that four lines (G5, G7, G17 and G20) were highly stable for grain yield in rain-fed conditions of subtropical regions of Iran. Thus, these lines can be recognized as the most stable lines for cultivation in diverse environments of semi-warm regions of Iran.