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  • 标题:Genetic Variations in fatty Acids and Oil Compositions among 188 Indian Mustard Brassica juncea (Linn.) Czern & Coss genotypes
  • 本地全文:下载
  • 作者:Chitralekha Shyam ; Manoj Kumar Tripathi ; Niraj Tripathi
  • 期刊名称:Current Journal of Applied Science and Technology
  • 印刷版ISSN:2457-1024
  • 出版年度:2021
  • 卷号:40
  • 期号:46
  • 页码:9-28
  • DOI:10.9734/cjast/2021/v40i4631629
  • 语种:English
  • 出版社:Sciencedomain International
  • 摘要:The experiment was conducted at Rajmata Vijayaraje Scindia Krishi Vishwa Vidyalaya, Gwalior, India to evaluate variability among 188 Indian mustard genotypes based on diverse biochemical parameters viz., palmitic, oleic, linoleic, linolenic and erucic acids along with oil content. Analysis of variance indicated the existence of substantial magnitude of variability among studied Indian mustard genotypes which suggest better possibilities for their improvement. Genotypic and phenotypic coefficient of variation was found to be higher for oleic acid tracked by erucic and palmitic acids. Erucic, oleic, palmitic, linoleic and linolenic acids had maximum heritability and genetic advance. Significant negative correlation of erucic acid was documented with palmitic, oleic, linoleic and linolenic acids. Genotypic and phenotypic path coefficient analysis had the higher positive direct effect of palmitic acid on erucic acid, whereas highest negative direct effect on erucic acid was evidenced by linoleic, oleic, linolenic acids and oil percentage. Genetic divergence using Euclidean distance cluster grouped the genotypes into eighteen different clusters. Among all studied biochemical parameters, erucic acid was found to be low in 9, moderate in 57 and higher in 122 genotypes. In cluster analysis of qualitative traits, maximum inter cluster distance was observed between cluster 18 (Karishma) and cluster 12 (Maya). Thus, these genotypes may be utilized as parents in Indian mustard breeding scheme for improvement of diverse qualitative traits.
  • 关键词:Indian mustard;biochemical traits;correlation coefficient;path coefficient;quantitative traits;principle component analysis
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