花生
最佳线性无偏预测
兽医学
基因型
数学
多样性(控制论)
统计
法医学
生物技术
生物
应用数学
医学
农学
计算机科学
遗传学
选择(遗传算法)
人工智能
基因
作者
Ramandeep Kaur Barsalia,Khushwinder Singh Brar,Pritpal Singh,Surinder Sandhu
出处
期刊:Agricultural Reviews
[Agricultural Research Communication Center]
日期:2024-04-05
卷期号: (Of)
摘要
Background: One of the major goals of plant breeding is the selection of high yielding superior cultivars having wide or specific adaptation. However, there is a fluctuation in the annual production due to the sensitive behaviour of the genotypes under different environmental conditions referred to as Genotype by Environment Interaction (GEI). The current study aimed to study the contribution of GEI for the adaptation of groundnut lines for spring and/or kharif season. Methods: To assess the contribution of GEI, Multi-Environment Trials (METs) were conducted for 40 confectionery purpose groundnut genotypes at F9 generation along with checks, across three locations for two seasons (spring and kharif). The contribution of environmental effects, genotypic values and genotype × environment interaction values were obtained from genotypic variance-covariance matrix Gi = Σg⨂A using mixed models (MM) in Best linear unbiased predictions (BLUPs).The pooled data was first partitioned into fixed effects of sites across the seasons and BLUP genotypic values (Ggge). The BLUP genotypic values are further partitioned into genetic value (Gg) and their interaction with the environment (Gge) for the adaptability of genotypes across seasons. Result: The results of MET revealed the presence of significant crossover interaction. The demarcation of advance breeding lines for adaptability across the environment as well as for season specific adaptation was done for variety testing. Genotypes having moderate to high Gge values along with high Gg values in spring than kharif, owing to their better performance during the spring season. CGL-11, CGL-23 and CGL-04 were the highest yielding genotypes, with quite high Gge values. This is due to the more favourable environmental conditions interacting positively with genotypes during the spring. Thus, the high Gg value(s) of genotype(s) alone is not a capable factor for commercialization as Gge value is the deciding factor for the adaptability for the targeted season.
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