Stability of grain yield performance of winter wheat genotypes

Abstract

Bread wheat is one of the most represented field crops whose level and stability of yield is very important for the food security in Republic Serbia. In the paper was investigated stability of yield expression of 15 winter bread wheat genotypes in different agroecological conditions of Serbia, using the Additive main effects and multiplicative interaction (AMMI) model and GGE-biplot method of analysis. Aim of investigation was to determine which of applied analysis is superior in identification of the most desirable genotypes for cultivation in given environments. Analysis of variance showed that genotype and genotype-environment (G×E) interaction represent highly significant sources of variability in expression of grain yield. AMMI and GGE analyses were point out similar results and an indisputable conclusion is that multienvironment trials, besides routine usage of analysis of variance, must be analized with one of this two models, which combine analysis of variance and PCA analysis. AMMI analysis is simpler for interpretation and closer to the concept of view of the agronomical trial, while GGE analysis is more complex and gives more precise interpretation of "which-won-where", i .e. for defining of narrowly adapted genotypes in given environments. Thus, G11 as the genotype with highest average yield is narrow adapted to the environment Sombor and can be recommended, as well as in the environment 2 (Kruševac), while genotypes with modest requests (G2) rather can be recommended for cultivation in the environment 1 (Kragujevac), which is characterized by less fertile soil and a smaller amount and uneven distribution of precipitation.

Utilizing the Stability of Yield Parameters as a Technique to Select Salinity-Tolerant Wheat Genotypes

“…It is a widely used statistical method for analyzing the performance of different genotypes across multiple environments in crop breeding programs. By analyzing the performance of different genotypes across multiple environments, AMMI analysis can help plant breeders in identifying the genotypes that are best suited to specific environmental conditions, and also help in identifying stable genotypes that perform consistently well across different environments (Petrović et al, 2010;Mohammadi et al, 2018;Neisse et al, 2018;Luković et al, 2020;Banjac et al, 2022;Perišić et al, 2022). In order to identify additive and multiplicative variance, the AMMI method first performs an analysis of variance.…”