Detection of additive and additive×environment interaction effects of QTLs for yield‐component traits of rice using single‐segment substitution lines (SSSLs)

Abstract

AbstractAdditive effects (A) and additive‐by‐environment interactions (A×E) for five rice yield components were analysed using 20 SSSLs under mixed linear model methodology. Thirty‐one QTLs were detected. Different yield components have different QTL‐by‐environment (Q×E) interaction patterns. No A×E interaction effects were detected for the four QTLs for panicle number (PN). Four QTLs detected for spikelets per panicle (SPP) had A×E interactions. Five of seven QTLs detected for grains per panicle (GPP), two of 10 QTLs detected for 1000‐grains weight (GWT) and three of six QTLs detected for seed set ratio (SSR) showed significant A×E interaction. Most of these QTLs were distributed in clusters across the genome. The complexity of linkage and pleiotropy of these QTLs plus environmental effect may result in the diversity of the yield phenotype in the SSSLs. Only S19 exhibited a significant increase in yield with a predicted gain by 281.58 kg ha−1. The results may be useful to design a better breeding strategy that takes advantage of QTL‐by‐environment interaction effects in each of the SSSLs.