Scholarlink

<p>Identifying the suitable production environment and understanding Genotype × Environment Interactions (GEI) is crucial for achieving optimal yield stability in field pea. A study was conducted to examine GEI for seed yield in 150 field pea (<i>Pisum sativum</i> L.) genotypes over two consecutive growing seasons at three different locations of Haryana in an alfa-lattice design. The study utilized several multivariate pattern analysis methods, including Eberhart and Russell (ER), AMMI, GGE biplot and WAAS. The analysis of variance showed that genotype, environment and their interaction had a significant impact on seed yield, as indicated by the ER model and identified five genotypes G84, G58, G20, G33 and G137 as high-yielding and hence well-suited to favourable environments. An ANOVA based on AMMI revealed highly significant GEI for seed yield per plant at <i>P</i> &lt; 0.001. The AMMI biplot analysis revealed that the genotypes G20, G121, G148, G81 and G17 were constant across environments, as they did not exhibit strong interactive forces. These genotypes were therefore identified as potential candidates for release in the study areas. Additionally, the GGE model (which-won-where) showed that genotypes G148, G121, G17, G11 and G20 were adapted to the first mega-environment, while genotypes G2, G10, G13, G7, G1, G92 and G33 were better suited to the second. The WAAS biplot identified G81, G20, G99, G142, G47, G138, and G148 as the most stable genotypes. Based on all models, G20 and G148 emerged as the most stable genotypes across all six environments. These genotypes can be used in crop breeding programs aimed at varietal development.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Evaluation of genotype × environment interactions for seed yield in field pea (Pisum sativum L.) genotypes using multivariate analysis model

  • 期刊论文

  • 发表日期：

    2025年4月14日

查看全文
  • Amit Sharma,
  • Rajesh Yadav,
  • Ravika Sheoran,
  • Pawan Kumar,
  • Deepak Kaushik,
  • Kavita Dhaka,
  • Nikhil Gangadharaiah,
  • Arpit Sharma

摘要

Identifying the suitable production environment and understanding Genotype × Environment Interactions (GEI) is crucial for achieving optimal yield stability in field pea. A study was conducted to examine GEI for seed yield in 150 field pea (Pisum sativum L.) genotypes over two consecutive growing seasons at three different locations of Haryana in an alfa-lattice design. The study utilized several multivariate pattern analysis methods, including Eberhart and Russell (ER), AMMI, GGE biplot and WAAS. The analysis of variance showed that genotype, environment and their interaction had a significant impact on seed yield, as indicated by the ER model and identified five genotypes G84, G58, G20, G33 and G137 as high-yielding and hence well-suited to favourable environments. An ANOVA based on AMMI revealed highly significant GEI for seed yield per plant at P < 0.001. The AMMI biplot analysis revealed that the genotypes G20, G121, G148, G81 and G17 were constant across environments, as they did not exhibit strong interactive forces. These genotypes were therefore identified as potential candidates for release in the study areas. Additionally, the GGE model (which-won-where) showed that genotypes G148, G121, G17, G11 and G20 were adapted to the first mega-environment, while genotypes G2, G10, G13, G7, G1, G92 and G33 were better suited to the second. The WAAS biplot identified G81, G20, G99, G142, G47, G138, and G148 as the most stable genotypes. Based on all models, G20 and G148 emerged as the most stable genotypes across all six environments. These genotypes can be used in crop breeding programs aimed at varietal development.