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Research Article Open access CC BY 4.0

Principal Component Analysis of Yield and Yield-Contributing Traits in Okra (Abelmoschus esculentus (L.) Moench) Genotypes

Akhila Srinidhi Pendyala, S. J. Shinde, D. K. Zate, V. S. Khandare, A. T. Daunde, P. R. Zanwar, Syed Shabnam, Manisha Kharat, Shrikrishna Gatul

Journal of Advances in Biology & Biotechnology · pp. 337–346 · Published 24 Jul 2026

10.9734/jabb/2026/v29i84186

Abstract

Principal component analysis was used to summarise variation among 36 okra (Abelmoschus esculentus (L.) Moench) genotypes evaluated in a randomised block design with two replications at the Department of Horticulture, College of Agriculture, Vasantrao Naik Marathwada Krishi Vidyapeeth, Parbhani. Nineteen traits related to growth, flowering, fruit, seed, yield, disease, and pests were recorded. The data were standardised before PCA and analysed using OPSTAT software. Four principal components together accounted for 87.62% of the total variation. The first component explained 51.50% of the variation and was associated mainly with fruit yield per plant, followed by the number of seeds per fruit, number of fruits per plant, fruit length, fruit diameter, number of leaves per plant, and 100-seed weight. The second component explained 24.91% and was strongly influenced by fruit and shoot borer incidence, together with fruit- and virus-related traits. The third and fourth components explained 6.30% and 4.90%, respectively, and represented variation in fruit, seed, yield, and biotic stress traits. The first three components jointly explained 82.71% of the variation. The score plot indicated broad phenotypic dispersion among the genotypes, with EC-329370, IC-42460, Arka Anamika, and Parbhani Kranti appearing relatively separated from the main group. These results indicate that a limited number of principal components can summarise the observed multivariate variation. The identified traits and comparatively distinct genotypes may be considered for further evaluation in okra improvement programmes.

Okra principal component analysis genetic variability yield attributes genetic diversity.

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