Abstract
Lentil (Lens culinaris Medik.) is traditionally grown as a rain fed crop, particularly in the Middle East; its seed is a rich source of protein for human consumption in developing countries such as Iran and others. The stability of 11 different lentil genotypes was investigated using 19 univariate stability parameters. Field experiments were conducted in 20 rain-fed environments in Iran’s lentil producing areas to characterize genotype by environment (GE) interactions on seed yield of 11 lentil genotypes. Combined analysis of variance across environments indicated that both environment and GE interactions significantly influenced genotype yield. Several statistical methods and techniques were used to describe the GE interaction and to define stable genotypes in relation to their yield. The results of these different stability methods were variable. However, most showed genotype FLIP 92-12L was stable and genotype Gachsaran was unstable. Genotypes identified as superior differed significantly from local cultivars and can be recommended for use by farmers in semi-arid areas of Iran. Principal component analysis was used to obtain an understanding of relationships among stability techniques. It showed the parameters studied could be grouped in five distinct classes. Clustering of the genotypes indicated that there were two genotypic groups in this group of genotypes.
Highlights
Lentil (Lens culinaris Medik.) is the fourth most important pulse crop in the world after bean (Phaseolus vulgaris L.), pea (Pisum sativum L.), and chickpea (Cicer arietinum L.)
Effects of E and the genotype by environment (GE) interaction were significant at P < 0.01 and the genotype main effect was significant at P < 0.05
The significance (P < 0.01) of nonadditivity was an indication of a crossover GE interaction
Summary
Lentil (Lens culinaris Medik.) is the fourth most important pulse (legume) crop in the world after bean (Phaseolus vulgaris L.), pea (Pisum sativum L.), and chickpea (Cicer arietinum L.). In most lentil production regions yields seem to be no more than one-half of potential cultivar yields and are far below theoretical maximum yields (Sabaghpour et al, 2004). This difference reflects production constraints that prevent the realization of true genetic yield potential. Flores et al (1998) compared 22 univariate and multivariate methods to analyze genotype by environment (GE) interactions. These methods were classified into three main groups including univariate parametric, univariate non-parametric and multivariate methods. There are two possible strategies for interpreting GE interaction with univariate parametric methods including analysis of variance and simple linear regression analysis of cultivar yield. The use of regression analysis models in studying GE interactions was first proposed by Yates and Cochran (1938), but their ideas were not taken up until Finlay and Wilkinson (1963) rediscovered the same method
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