Genotype × environment interaction on grain yield and yield components in bread wheat

M. Siddquie, M. Hoque
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Abstract

Genotype by environment (Location) interaction (GEI) is essential for identifying environment-specific and widely adapted genotypes of wheat. The experiment was carried out across five locations (Shyampur and Godagari under Rajshahi district, Nachole at Chapainawabganj, Sapahar at Naogaon and Lalpur at Natore district in north-west Bangladesh) to assess GEI effects on grain yield and its components and to identify high yielding and stable genotypes of wheat for grain yield in the year of 2020-21. Combined analyses of variance for G and GEI were significant for almost all traits. Significant GEI suggested that the performance of genotypes was not consistent across locations, revealing strong influence of environments on the expression of phenotype for all traits. Average over five locations, genotypes G84 (3647 kg ha-1) and G76 (3576 kg ha-1) exhibited maximum values for grain yield and also produced similar tillers m-2 (SPM) and grains spike-1 (GPS) where difference between them was statistically insignificant thus appeared as leading genotypes for yield and production traits. Again, the genotypes G84 and G76 produced statistically insignificant maximum yield in all locations indicating that they are high yielding and wide adapted genotypes. The genotype G80 produced insignificant yield and other yield traits with G76 and G84 across the locations indicating its wide adaptability. However, G26, G69 and G77 with higher grain yield in Shyampur, G53 and G59 in Godagari ,G20 in Lalpur, G3 in Nachole and G8 in Sapahar proved their specific adaptability in particular locations. Among locations, Shyampur and Godagari were identified as highly productive locations in terms of grain yield and positive environmental index. Correlation analysis showed that grain yield had strong positive association with spikes m-2 (r = 0.92**), grains spike-1 (r = 0.72**) and TGW (r = 0.89**). On the basis of mean grain yield and higher positive phenotypic index for SPM, GPS, TGW and GY, G76, the genotypes G84,G76 and G80 were found as high yielding genotypes and thus could be recommended as important breeding materials in upcoming specific breeding program for drought prone north-west part of Bangladesh.
基因型与环境互作对面包小麦产量及产量构成因素的影响
环境(位置)互作基因型(GEI)是鉴定小麦环境特异性和广泛适应基因型的基础。该试验在五个地点(Rajshahi地区的Shyampur和Godagari, Chapainawabganj的Nachole, Naogaon的Sapahar和Natore地区的Lalpur)进行,以评估GEI对粮食产量及其组成部分的影响,并确定用于2020-21年粮食产量的高产和稳定的小麦基因型。G和GEI的联合方差分析对几乎所有性状都具有显著性。显著的GEI表明基因型表现在不同地点并不一致,表明环境对所有性状的表型表达有很强的影响。平均而言,基因型G84 (3647 kg ha-1)和G76 (3576 kg ha-1)的产量最高,分蘖m-2 (SPM)和穗型1 (GPS)相似,差异无统计学意义,因此它们是产量和生产性状的主要基因型。同样,基因型G84和G76在所有地点的最大产量统计上不显著,表明它们是高产和广泛适应的基因型。G80基因型对G76和G84的产量和其他产量性状的影响不显著,表明其适应性广。然而,产量较高的G26、G69和G77在Shyampur, G53和G59在Godagari,G20在Lalpur, G3在Nachole, G8在Sapahar证明了它们在特定地点的适应性。其中,Shyampur和Godagari在粮食产量和积极环境指数方面被确定为高产地区。相关分析表明,籽粒产量与穗粒m-2 (r = 0.92**)、穗粒1 (r = 0.72**)和总重(r = 0.89**)呈极显著正相关。根据SPM、GPS、TGW和GY、G76的平均产量和较高的正表型指数,发现G84、G76和G80基因型为高产基因型,可作为未来孟加拉国西北部干旱易发地区特定育种计划的重要选育材料。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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