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Plant Science Today (PST)

Research Articles

Vol. 13 No. sp5 (2026): Recent Advances in Agriculture

Discrimination of mango (Mangifera indica L.) genotypes through multivariate analysis of physico-chemical characters

DOI
https://doi.org/10.14719/pst.14589
Submitted
18 March 2026
Published
04-08-2026

Abstract

Mango (Mangifera indica L.), the “king of fruits” native to India, exhibits wide variation in physical, chemical and nutritional properties, enabling trait-based classification and authentication of varieties. This study evaluated 15 mango genotypes from diverse agroecological zones of India based on bearing nature, quality traits and regional origin. Over 2 years, 27 traits were recorded from fully matured fruits and the data were analysed using principal component analysis (PCA) and linear discriminant analysis (LDA). Among the genotypes evaluated, Kalapad recorded the highest total soluble solids (TSS) (25.78°Brix), while Imampasand recorded the highest phenol content (35.25 mg gallic acid equivalents (GAE) / mL), reflecting superior nutritional quality. Principal component analysis indicated substantial variability among genotypes, with total carotenoids, TSS, fat, TSS : acid ratio, fruit weight and pulp weight identified as major contributors to the overall variability, with the major principal components, PC1 and PC2, together explaining 56.8 % of total variance. Linear discriminant analysis showed that Chinnarasam, Kalapad and Ratnagiri Alphonso clustered closely, showing superior quality traits and achieved a cross-validated classification accuracy of 82.22 % (k = 0.8095), confirming the strong discriminatory power of physico-chemical characters among 15 mango genotypes. Linear discriminant analysis also clearly distinguished the regular bearer and alternate bearer, such as Neelum, Bengalura and Imampasand, highlighting the influence of bearing habit on genotype differentiation. The overlap between export genotypes Kesar and Dashehari indicated a similar agroecological origin. These findings demonstrate the effectiveness of multivariate analysis in discriminating mango genotypes, aiding germplasm management, genotype authentication and crop improvement strategies.

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