Bi-environmental evaluation of oat (Avena sativa L.) genotypes for yield and nutritional traits under cold stress conditions using multivariate analysis

Saika Nabi, Shamshir ul Hussan, Tawqeer Nabi, Asif B. Shikari, Zahoor Ahmad Dar, N. S. Khuroo, Ajaz Ahmad Lone, P. A. Sofi, Rahila Amin, M. Altaf Wani
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Abstract

Oat being a rabi/winter crop in Kashmir, experiences extremely low temperatures which has detrimental effects on its growth and development. Therefore, this study was designed to evaluate a set of 130 oat genotypes in multi-location trials across temperate conditions of Kashmir valley from 2018 to 2022. From the preliminary data of 56 genotypes, including five checks, were selected and evaluated for nutritional and yield attributing traits under cold stress conditions at two locations. The results demonstrated significant genetic variation and high heritability for majority of traits, except for days to 50% flowering, days to maturity and dry fodder. Positive correlations were observed between green fodder yield and other traits, indicating their potential for enhancing yield. Principal component analysis identified four principal components that accounted for 69.87% of the total variation. Cluster analysis categorized the genotypes into two main clusters and six sub-clusters. Frost damage assessment was conducted at tillering stage after the snow melted in late January 2021 and 2022 using cold tolerance rating scale and subsequently tested for chilling injury through an electrolyte leakage test. From field and lab data analysis, five most promising cold tolerant, nutritious and high-yielding genotypes were identified. These genotypes have significant potential for utilization in future breeding programmes to improve cold tolerance in cultivated oats within the Kashmir valley thus promoting agricultural productivity and sustainability. The outcomes also provide valuable insights into the genetic variation, heritability, genotype-by-environment interactions, correlations and cold tolerance of oat genotypes in Kashmir.

利用多元分析对燕麦(Avena sativa L.)基因型在冷胁迫条件下的产量和营养性状进行双环境评估
燕麦是克什米尔地区的一种冬季作物,由于气温极低,对其生长发育造成不利影响。因此,本研究旨在从 2018 年到 2022 年对克什米尔山谷温带条件下的 130 个燕麦基因型进行多地点试验评估。从初步数据中筛选出 56 个基因型,包括 5 个对照,并在两个地点对冷胁迫条件下的营养和产量性状进行了评估。结果表明,除50%开花天数、成熟天数和干饲料外,大多数性状都具有明显的遗传变异和较高的遗传率。青饲料产量与其他性状之间呈正相关,表明它们具有提高产量的潜力。主成分分析确定了四个主成分,占总变异的 69.87%。聚类分析将基因型分为两个主聚类和六个子聚类。在 2021 年和 2022 年 1 月底积雪融化后的分蘖期,使用耐寒等级表进行了冻害评估,随后通过电解质泄漏测试进行了冷害检测。通过田间和实验室数据分析,确定了五个最有潜力的耐寒、营养和高产基因型。这些基因型在未来的育种计划中具有很大的利用潜力,可提高克什米尔山谷栽培燕麦的耐寒性,从而提高农业生产力和可持续性。研究结果还对克什米尔地区燕麦基因型的遗传变异、遗传率、基因型与环境的相互作用、相关性和耐寒性提供了宝贵的见解。
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