Genotype by Environment Interaction and Yield Stability of Barley Breeding Lines in Multi-Environment Trials

Abstract

In modern conditions it is necessary to create varieties of spring barley with combination of high grain yield and stability. For this purpose, multienvironment trials of nine advanced breeding lines and the standard variety Vzirets were carried out in three different ecological zones in Ukraine: Central Forest-Steppe, Polissia and Northern Steppe. High yield variability of spring barley breeding lines has been established. The ANOVA revealed reliable contributions from all three source of the variation: genotype, environment and genotype-environment interaction. The part of influence for environment was the highest -90.42 %. A set of statistical indices (regression coefficient (b i ), deviation mean squares (S 2 d i ), variety superiority measure (P i ), nonparametric stability indices (S i (1) and S i (2) ), homeostaticity (Hom i ), breeding value (Sc i )) and GGE biplot were used to interpret the multi-environment trial data. The applied statistical indices in different ways characterized the investigated barley breeding lines. Some indices estimated the stability only, without considering yield level (S 2 d i, S i (2) ). Other indices were related with the mean yield (P i ), with the maximum (b i ) or minimum (S i (1) , Hom i , Sc i ) its value. The combination of statistical indices and graphic model was effective for comprehensive evaluation of the genotype-environment data from multi-environment trials. This approach allows identify the best of the best breeding lines at the final stage of breeding work. The breeding lines Deficiens 5005, Nutans 4855, Nutans 4941 and Nutans 4890 have been submitted to the State Strain Testing of Ukraine as new varieties MIP Visnyk, MIP Ekspert, MIP Myroslav, MIP Vdiachnyi, respectively.

Evaluation of Breeding Improvement for Spring Barley Varieties in Terms of Yield and Yield-Related Traits

“…For accurate interpretation of the genotype by environment data it is necessary to use the most appropriate statistical models (van Eeuwijk et al, 2016). The genotype main effects plus genotype by environment interaction (GGE biplot) model has been the most widely used for this purpose in different countries (Kendal and Doğan, 2015;Meng et al, 2016;Bilgin et al, 2018;Kendal et al, 2019;Hudzenko et al, 2019). The first two principal components of the GGE biplot explained 97.57 % of genotype by environment interaction (Fig.…”

Evaluation of Winter Barley Cultivars for Resistance to Leaf Fungal Diseases and Yield in the Conditions of the Western Forest-Steppe of Ukraine

“…Extensive adaptation of the variety to radically different growing conditions is a relatively rare case. In the history of selection and production, such unique generally recognised varieties were: wheat -Myronivska 808, barley -Wiener (Vasylkivskyi & Gudzenko, 2017;Hudzenko et al, 2019). However, varieties with wide adaptability may be inferior to more locally adapted in specific conditions (Abessa et al, 1992;Ceccarelli, 1996).…”