Genotype by environment interaction using AMMI model and estimation of additive and epistasis gene effects for 1000-kernel weight in spring barley (Hordeum vulgare L.)

Abstract

The objective of this study was to assess genotype by environment interaction for 1000-kernel weight in spring barley lines grown in South Poland by the additive main effects and multiplicative interaction model. The study comprised of 32 spring barley ( Hordeum vulgare L.) genotypes (two parental genotypes—breeding line 1 N86 and doubled haploid (DH) line RK63/1, and 30 DH lines derived from F 1 hybrids), evaluated at six locations in a randomized complete block design, with three replicates. 1000-kernel weight ranged from 24.35 g (for R63N/42 in 2011) to 61.46 g (for R63N/18 in 2008), with an average of 44.80 g. AMMI analyses revealed significant genotype and environmental effects as well as GE interaction with respect to 1000-kernel weight. In the analysis of variance, 16.86% of the total 1000-kernel weight variation was explained by environment, 32.18% by differences between genotypes, and 24.50% by GE interaction. The lines R63N/61, R63N/22, and R63N/1 are recommended for further inclusion in the breeding program because their stability and the highest averages of 1000-kernel weight. The total additive effect of all genes controlling the trait and the total epistasis effect of 1000-kernel weight were estimated. Additive gene action effects based on DH lines were always larger that this parameter estimated on the basis of parental lines. Estimates of additive gene action effects based on the all DH lines were significantly larger than zero in each year of study. Epistasis effects based on all DH lines were statistically significant in 2011 and 2013.

Genetic Parameters and QTLs for Total Phenolic Content and Yield of Wheat Mapping Population of CSDH Lines under Drought Stress

“…All epistatic effects for BIO were positive (Table 3). Similar results have been obtained for a simulation study and in analyses of different plants [33,34,35,48]. The percentage variances attributed to additive and epistatic effects were in the range of 61.71–86.21% (yield), 62.45–80.16% (BIO), 60.25–89.54% (GN), and 62.91–82.23% (TGW).…”

Genotype by environment interaction for seeds yield in pea (Pisum sativum L.) using additive main effects and multiplicative interaction model

“…Multi-location experiments the AMMI biplot allows to visualize the main genotype effect in different environments (Bocianowski et al 2019a). The AMMI model was used to study many species (Abakemal et al 2016;Edwards 2016;Nowosad et al 2017Nowosad et al , 2018Bocianowski et al 2019d). Indicating GE's interaction and other interactions is possible using the AMMI model.…”

Assessment of ecological stability in yield for breeding of spring barley cultivars with increased adaptive potential

“…For interpretation of experimental data from multi-environment trials it is necessary to use the most appropriate statistical models (van Eeuwijk et al, 2016). AMMI (Mehari et al, 2014;Abtew et al, 2015;Bocianowski et al, 2019;Verma et al, 2019) and GGE biplots (Bilgin et al, 2018;Al-Ghzawi et al, 2019;Al-Sayaydeh et al, 2019;Gudzenko, 2019) have been the most widely used in recent years in order to interpret the experimental data from genotype by environmental trials. A number of researchers combine both of these statistical tools (Vaezi et al, 2017;Fana et al, 2018;Solonechnyi et al, 2018;Kendal et al, 2019).…”