The present study was undertaken to delineate genotype–environment interactions and stability status of 16 genotypes of ashwagandha (Withania somnifera (L.) Dunal) in context to the 12 characters, namely plant height, number of primary branches, number of secondary branches, days to flowering, days to maturity, number of berries, number of seeds/berry, root length, root diameter, root branches, dry root yield and total alkaloid content (%). Experiment was carried out in a randomized complete block design with three replications over three different locations (S. K. Nagar, Jagudan and Bhiloda) in north Gujarat for three years (2016–17, 2017–18 and 2018–19). Pooled analysis of variance revealed that the mean squares due to genotypes and genotype × environment interaction along with linear and nonlinear components were highly significant (P<0.01) for most of the traits under study. Stability parameters for component traits through Eberhart and Russell model showed that genotypes that can be used directly in breeding programme are SKA-4 for early flowering, SKA-21 for early maturity and SKA-1, SKA-4, SKA-6 and SKA-17 for shorter plant height. Further, SKA-21 could be used for improving number of primary branches per plant, SKA-11 and SKA-17 for number of secondary branches per plant, SKA-19 for number of berries per plant, SKA-6, SKA-21, SKA-27 and AWS-1 for root branches and SKA-17 for root length as these genotypes were found to be most stable across the environments for mentioned traits. The result revealed that some reliable predictions about genotype × environment interaction and its unpredictable components were involved significantly in determining the stability of genotypes. Hence, the present investigation can be exploited for the identification of more productive genotypes in specific environments, leading to significant increase in root productivity of ashwagandha.

中文翻译：

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阐明南非醉茄（Withania somnifera (L.) Dunal）产量、品质和农艺性状的基因型-环境相互作用和遗传稳定性参数

本研究旨在描述 ashwagandha (Withania somnifera (L.) Dunal) 的 16 个基因型的基因型 - 环境相互作用和稳定性状态，并结合 12 个特征，即株高、初级分枝数、次级分枝数、天数开花、成熟天数、浆果数、种子/浆果数、根长、根直径、根分枝、干根产量和总生物碱含量 (%)。实验以随机完整区组设计进行，在古吉拉特邦北部的三个不同地点（SK Nagar、Jagudan 和 Bhiloda）进行了三个重复，为期三年（2016-17、2017-18 和 2018-19）。方差合并分析显示，由于基因型和基因型×环境相互作用以及线性和非线性成分引起的均方非常显着（P < 0. 01）对于正在研究的大多数特征。通过Eberhart和Russell模型对组分性状的稳定性参数表明，可直接用于育种计划的基因型为早花SKA-4，早熟SKA-21和SKA-1、SKA-4、SKA-6和SKA- 17 用于较短的植物高度。此外，SKA-21 可用于提高每株植物的初级分枝数，SKA-11 和 SKA-17 用于提高每株植物的次级分枝数，SKA-19 用于提高每株植物的浆果数，SKA-6、SKA-21， SKA-27 和 AWS-1 用于根分支，SKA-17 用于根长度，因为发现这些基因型在上述特征的环境中最稳定。结果表明，一些关于基因型×环境相互作用及其不可预测成分的可靠预测显着影响了基因型的稳定性。