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Correlation and Path Coefficient Analysis Studies for Quantitative Traits in Okra [Abelmoschus esculentus (L.) Moench]

机译:秋葵中定量性状的相关路径系数分析研究[Abelmoschus Esculentus(L.)Moench]

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摘要

Investigation on correlation and path coefficient was carried out among 14 different yield attributing traits in 32 advanced breeding lines of okra during summer season, 2012-13. Genotypic and phenotypic correlation coefficient studies revealed that fruit yield per plant exhibited positive and significant correlation with number of pods per plant, number of nodes per plant, average pod weight, pod width, plant height and pod length. Whereas, days to 1 “ flowering and days to 50% flowering recorded significant negative correlation with pod yield per plant. Genotypic path coefficient analysis revealed that plant height and pod length recorded maximum positive direct effect on pod yield per plant. Whereas, phenotypic path coefficient analysis revealedthat number of pods per plant, average pod weight and plant height recorded maximum positive direct effect on pod yield per plant. Thus pod yield in okra can be improved by selection of traits with higher number of pods per plant, number of nodes per plant, average pod weight and pod length.
机译:在夏季秋季32次高级育种中的14种不同产量归因性状的相关性和路径系数进行了研究。基因型和表型相关系数研究表明,每株植物的果产量与每株植物的数量,每株植物数量,平均豆荚,荚宽度,植物高度和荚长度的阳性和显着相关性。然而,日期为1英寸开花和日落到50%开花记录了每株豆荚产量的显着负相关。基因型路径系数分析显示植物高度和荚长度记录了每株植物豆荚产量的最大阳性直接影响。然而,表型路径系数分析显示每个植物的豆荚数,平均豆荚和植物高度记录了每株植物荚产量的最大阳性直接影响。因此,通过选择每株植物数量较多的豆荚,每株植物数量,平均豆荚和荚长度,可以改善秋葵的豆荚产量。

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