Elucidating genetic diversity and variability in Chickpea (Cicer arietinum L.) using yield attribution traits

A. Babbar, Monica Jyoti Kujur, Prachi Sharma, Balkishan Chaudhary, Monika Patel, Archana Shakya
{"title":"Elucidating genetic diversity and variability in Chickpea (Cicer arietinum L.) using yield attribution traits","authors":"A. Babbar, Monica Jyoti Kujur, Prachi Sharma, Balkishan Chaudhary, Monika Patel, Archana Shakya","doi":"10.36953/ecj.22362578","DOIUrl":null,"url":null,"abstract":"Fifty-six desi chickpea (Cicer arietinum L.) advance breeding lines were evaluated in order to explore the possibility of genetic divergence for yield and its contributing traits using Mahalanobis’s D2 Statistics and Principal Component Analysis. High estimates of heritability, genetic advance, GCV and PCV were recorded for seed yield per plant (92.2%, 12.4%, 37.1% and 38.7%), biological yield per plant (88.1%, 21.9%, 29.1% and 31.0%) and harvest index (87.3%, 25.0%, 22.7% and 24.3%). All the test genotypes were sort into five discrete clusters. Biological yield/plant (23.5%), days to maturity (17.3%), harvest index (14.6%), seed yield/plant (11.3%), total number of pods/plant (7.4%) and 100 seed weight (6.49%) were found to have highest percentage contributions to genetic diversity in the present research. The first six principal components (PC1 19.7%, PC 16.2%, PC3 11.2%, PC4 9.69%, PC5 7.2% and PC6 6.69%) could explain 70.68% of the total of the interaction variation and have Eigen value more than one.  Genotypes JG 2016-1411, JG 2016-9605, JG 2017-46, ICCV 16105, ICCV 16109, ICCV 16112 and ICCV 16116 were present in more than one PCs hence contributed maximum towards yield and can be used in various breeding programmes for yield improvement.","PeriodicalId":12035,"journal":{"name":"Environment Conservation Journal","volume":"49 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environment Conservation Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36953/ecj.22362578","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Fifty-six desi chickpea (Cicer arietinum L.) advance breeding lines were evaluated in order to explore the possibility of genetic divergence for yield and its contributing traits using Mahalanobis’s D2 Statistics and Principal Component Analysis. High estimates of heritability, genetic advance, GCV and PCV were recorded for seed yield per plant (92.2%, 12.4%, 37.1% and 38.7%), biological yield per plant (88.1%, 21.9%, 29.1% and 31.0%) and harvest index (87.3%, 25.0%, 22.7% and 24.3%). All the test genotypes were sort into five discrete clusters. Biological yield/plant (23.5%), days to maturity (17.3%), harvest index (14.6%), seed yield/plant (11.3%), total number of pods/plant (7.4%) and 100 seed weight (6.49%) were found to have highest percentage contributions to genetic diversity in the present research. The first six principal components (PC1 19.7%, PC 16.2%, PC3 11.2%, PC4 9.69%, PC5 7.2% and PC6 6.69%) could explain 70.68% of the total of the interaction variation and have Eigen value more than one.  Genotypes JG 2016-1411, JG 2016-9605, JG 2017-46, ICCV 16105, ICCV 16109, ICCV 16112 and ICCV 16116 were present in more than one PCs hence contributed maximum towards yield and can be used in various breeding programmes for yield improvement.
利用产量属性特征阐明鹰嘴豆(Cicer arietinum L.)的遗传多样性和变异性
对 56 个 desi鹰嘴豆(Cicer arietinum L.)先期育种品系进行了评估,以利用 Mahalanobis D2 统计法和主成分分析法探索产量及其贡献性状遗传差异的可能性。每株种子产量(92.2%、12.4%、37.1% 和 38.7%)、每株生物产量(88.1%、21.9%、29.1% 和 31.0%)和收获指数(87.3%、25.0%、22.7% 和 24.3%)的遗传率、遗传进展、GCV 和 PCV 的估计值都很高。所有受试基因型被分为五个离散群组。本研究发现,生物产量/株(23.5%)、成熟天数(17.3%)、收获指数(14.6%)、种子产量/株(11.3%)、荚果总数/株(7.4%)和百粒种子重量(6.49%)对遗传多样性的贡献率最高。前六个主成分(PC1 19.7%、PC 16.2%、PC3 11.2%、PC4 9.69%、PC5 7.2%和 PC6 6.69%)可解释 70.68%的互作变异,且特征值均大于 1。 基因型 JG 2016-1411、JG 2016-9605、JG 2017-46、ICCV 16105、ICCV 16109、ICCV 16112 和 ICCV 16116 出现在一个以上的 PC 中,因此对产量的贡献最大,可用于各种育种计划以提高产量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信