Cargando…

Evaluation of Indian ginseng [Withania somnifera (L.) Dunal] breeding lines and genotype-by-environment interaction across production environments in western India

In order to find location-specific and broadly adapted genotypes for total root alkaloid content and dry root yield along with additive main effects and multiplicative interactions (AMMI) and genotype (G) main effects plus genotype × environment (E) interaction in Indian ginseng (Withania somnifera...

Descripción completa

Detalles Bibliográficos
Autores principales: Kumar, Mithlesh, Patel, Manubhai, Solanki, Satyanarayan, Gami, Raman
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Nature Singapore 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10153036/
https://www.ncbi.nlm.nih.gov/pubmed/37359123
http://dx.doi.org/10.1007/s42535-023-00626-0
Descripción
Sumario:In order to find location-specific and broadly adapted genotypes for total root alkaloid content and dry root yield along with additive main effects and multiplicative interactions (AMMI) and genotype (G) main effects plus genotype × environment (E) interaction in Indian ginseng (Withania somnifera (L.) Dunal), (GGE) biplot analyses were used in the current study. Trials were carried out in a randomized complete block design (RCBD) over three succeeding years viz., 2016–2017, 2017–2018 and 2018–2019 at three different locations (S. K. Nagar, Bhiloda and Jagudan). Analysis of variance (ANOVA) for AMMI for dry root yield revealed that the environment, genotype, and GE interaction, respectively, accounted for significant sums of squares of 35.31%, 24.89%, and 32.96%. For total root alkaloid content, a significance of 27.59% of total sum of squares was justified by environment, 17.72% by genotype and 43.13% by GEI. Nine experimental trials in total were taken into consideration as contexts for the GEI analysis in 16 genotypes, including one check. AMMI analysis showed that genotypes, SKA-11, SKA-27, SKA-23 and SKA-10 were superior for mean dry root yield and SKA-11, SKA-27 and SKA-21 had better performance for total root alkaloid content across environment. The GGE biplot analysis showed genotypes SKA-11, SKA-27, SKA-10 desirable for dry root yield and SKA-26, SKA-27, SKA-11 for total root alkaloid content. As a result of the GGE and AMMI biplot techniques, SKA-11 and SKA-27 were determined to be the most desired genotypes for both total root alkaloid content and dry root yield. Further, simultaneous stability index or SSI statistics identified SKA-6, SKA-10, SKA-27, SKA-11 and AWS-1 for higher dry root yield, whilst SKA-25, SKA-6, SKA-11, SKA-12 and AWS-1 for total alkaloid content from root. Based on trait variation, GGE biplot analysis identified two mega-environments for dry root yield and a total of four for total root alkaloid content. Additionally, two representative and discriminating environments—one for dry root production and the other for total root alkaloid content were found. Location-specific and breeding for broad adaptation could be advocated for improvement and release of varieties for Indian ginseng.