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Yield Stability Parameters of Barley under Finnish Conditions
Authors:Ero Nissilä
Affiliation:Agricultural Research Centre of Finland , Institute of Plant Breeding , SF-31600, Jokioinen, Finland
Abstract:Abstract

The objective of this study was to evaluate whether it is possible to obtain reliable estimates of yield stability of barley on the basis of single year trials. The stability was analysed by using some of the most common stability parameters. The other objective was to study the influence of variation between locations and years on the yield stability of barley under growing conditions in Finland. Barley breeder's trials of the Agricultural Research Centre of Finland from the years 1987-89 were used as material in this study. In each of these years six trials from different parts of Finland and six genotypes were analysed. Four parameters were used in analysis of yield stability: b i (Finlay & Wilkinson, 1963), s 2 d i (Eberhart & Russell, 1966), r 2 i (Pinthus, 1973) and environmental variance s 2 i. Each parameter was calculated from single- and multi-year results. The multi-year results were considered as reliable data with which to estimate yield stability. The reliability of the stability parameters was tested by Spearman's rank correlation coefficient between single- and multi-year stability values of each parameter. Although the variation between years was highly significant, there was no interaction between genotypes and years. In two experimental years genotype × location interaction was highly significant, and on the basis of this study, the genotype × location interaction seems to be a more important factor than genotype × year interaction in barley breeding for Finnish conditions. However, a series of three years may not be sufficient for indicating genotypes × years interactions. In this study two stability parameters, b i and s 2 i, gave a reliable estimate of yield stability on the basis of single-year trials.
Keywords:Phenotypic stability  genotype × environment interaction  barley  repeatability  regression approach
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