Fruit and leaf diversity of selected Indian mangoes (Mangifera indica L.)

•Significant diversity was noted among 58 Indian mango genotypes basing on 70 pheno-biochemical characters.•Polymorphism was pronounced for several fruit features suitable for fresh consumption, industrially processed products.•Unique traits enabled identification of 23 different genotypes.•Twelve indigenous genotypes possessing desirable fruit quality are promising for genetic improvement through breeding programme. Genetic diversity was assessed of 58 mango genotypes obtained from different eco-geographical locations of India including 20 selections, 17 hybrids and 21 landraces (local genotypes) of Odisha State. A total of 70 pheno-biochemical features based on leaf morphology and fruits were considered for investigation through PCA, co-phenetic correlation and UPGMA cluster analysis, which revealed a significant extent of diversity among the studied mango genotypes. Correlations among quantitative and qualitative pomological traits not only enabled us to discriminate genotypes but, more importantly, helped us to select those specifically suitable for commercialization and selective breeding. Several pomological traits of economic significance displayed extreme variability based on the first three PCA components; these attributes might be used as breeding targets to enhance fruit production and quality. Unique or rare marker traits were identified which facilitated discrimination of 23 genotypes. Based on cluster analysis and outstanding ripe fruit quality characters (genotypes ‘Kancha Mitha’, ‘Karpura Bhog’, ‘Baldev’, ‘Aishwarya’, ‘Hamilton Sundari’), similarity coefficients (genotypes ‘Miskanta’, ‘Ganga’, ‘Kuanri’, ‘Baramasi’) as well as distribution in clusters and unique pomological attributes (genotypes ‘Hatimundi’, ‘Dophasal’, ‘Jehangir’, ‘Baldev’ and ‘Bileimundei’), new genotypes were found to be diverse and distinct for their desirable characteristics. They can be used as suitable candidates in breeding programs for mango improvement. The least similarity was observed between ‘Fazli’ vs ‘Manjeera’ followed by ‘Cherukrasam’ vs ‘Miskanta’, ‘Mallika’ vs ‘Ganga’ and ‘Lal Sundari’ vs ‘Ratna’, representing most diverse varieties. NJ tree based on pheno-biochemical data grouped 58 genotypes into five major clusters. The 2D and 3D PCA plots effectively clustered the genotypes based on their phenotypic resemblance and biochemical features. The information generated on genotypic diversity and interrelationships will certainly be helpful in sustainably expl