Genetic variability, associations, and path analysis of chemical and morphological traits in Indian ginseng [Withania somnifera (L.) Dunal] for selection of higher yielding genotypes
Background: The study was carried out to assess the genetic variability present in ashwagandha and to examine the nature of associations of various traits to the root yield of the plant. Methods: Fifty-three diverse genetic stocks of ashwagandha (Withania somnifera) were evaluated for 14 quantitativ...
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Published in | Journal of ginseng research Vol. 42; no. 2; pp. 158 - 164 |
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Main Authors | , , , , , |
Format | Journal Article |
Language | Korean |
Published |
2018
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Subjects | |
Online Access | Get full text |
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Summary: | Background: The study was carried out to assess the genetic variability present in ashwagandha and to examine the nature of associations of various traits to the root yield of the plant. Methods: Fifty-three diverse genetic stocks of ashwagandha (Withania somnifera) were evaluated for 14 quantitative characteristics. Analysis of variance, correlation, and path coefficient analysis were performed using the mean data of 2 years. Results: Analysis of variance revealed that the genotypes differed significantly for all characteristics studied. High heritability in conjunction with high genetic advance was observed for fresh root weight, 12 deoxywithastramonolide in roots, and plant height, which indicated that selection could be effective for these traits. Dry root weight has a tight linkage with plant height and fresh root weight. Further, in path coefficient analysis, fresh root weight, total alkaloid (%) in leaves, and 12 deoxywithastramonolide (%) in roots had the highest positive direct effect on dry root weight. Conclusion: Therefore, these characteristics can be exploited to improve dry root weight in ashwagandha genotypes and there is also scope for the selection of promising and specific chemotypes (based on the alkaloid content) from the present germplasm. |
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Bibliography: | KISTI1.1003/JNL.JAKO201811041674547 |
ISSN: | 1226-8453 2093-4947 |