Multivariate analysis for various agro-morphological traits of turmeric (Curcuma longa L.)

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DOI:

https://doi.org/10.24154/jhs.v18i2.2092

Keywords:

Clustering, multivariate analysis, principal component analysis, turmeric

Abstract

Turmeric is one of the potential spice crops having importance in culinary, colouring in textiles and therapeutic in pharmaceutical industries. The present investigation was carried out to estimate the genetic diversity of 21 turmeric genotypes representing different geographical locations of India. The principal component (PC) analysis indicated that the most of the variation among the genotypes was contributed by the first two principal components (61.38%), which were largely governed by plant height, number of leaves per plant, leaf lamina length, leaf area, total leaf area, collar girth and weight of the mother rhizomes per clump. These traits showed high positive correlation with first two PCs and influenced significantly for grouping. Based on PC correlation analysis, it is evident that morphological and yield attributing traits of PC1 and PC2 are influenced and contributed for most of the variation among the genotypes. The cluster analysis revealed that the 21 genotypes fall into five clusters, and among them most divergent with distinct genotypes were cluster I, III and cluster IV. However, IISR Pragati, Rajendra Sonali and NDH 8 were found superior for fresh rhizome yield and Acc. 849 was found unique with robust mother rhizome. The present study contributes to the knowledge of genetic diversity and defining strategies for yield improvement in turmeric.

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Published

2023-11-29

How to Cite

Silaru, R., Kotha Madduri, Y., Sounderarajan, A., & Prasath D. (2023). Multivariate analysis for various agro-morphological traits of turmeric (Curcuma longa L.). Journal of Horticultural Sciences, 18(2). https://doi.org/10.24154/jhs.v18i2.2092

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Original Research Papers

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