Volume Issue 1 DR-1776 [1-8] RESEARCH ARTICLE Asian Journal of Dairy and Food Research, Volume Issue : () Assessment of Genetic Divergence by Using Multivariate Analysis for Physico Chemical Characters of Mango Table and Juicy Cultivars Grown in Telangana Region B. Soujanya 1 , A. Kiran Kumar 2 , S. Vanisri 3 , M. Sreedhar 3 , P. Saidiah 4 , A. Bhagwan 2 , G. Sathish 4 10.18805/ajdfr.DR-1776 INTRODUCTION Mango (Mnagifera indica L.) is a major fruit crop which is widely grown in tropical and subtropical countries of the world. It’s related to Anacardiacea family in order Sapindales. India ranks first in production and consumption of mango in the world. In India, mango is cultivated in an area of 2.31 million ha with production of 22.35 million tonnes and 7.3 MT/ha productivity (NHB Data Base 2019-20). Major mango growing states are Uttar Pradesh, Andhra Pradesh, Odisha, Karnataka and Telangana. In India, 1000 cultivars are well known for its commercial importance, Telangana state also has richest source of mango germplasm. Mango is having the chromosome number 2n=40 and n=20 and the genome size is 4.39108 bp which is small in size but, morphologically distinguished among the cultivars of mango (Arumuganathan and Earle, 1991). Genetic diversity analysis is generally used to identify diverse genotypes for hybridization purpose. Analysis of divergence can be performed by many statistical tools such as D 2 Mahalanobis distance, Euclidean distance, average distance, etc. (Shirkhorshidi et al., 2015). Among the various methods identified to assess the genetic divergence in the varieties, the Mahalanobis D 2 (Mahalanobis, 1936) is reliable and most frequently used technique. D 2 analysis is a useful tool in quantifying the degree of divergence between biological population at genotypic level and to assess relative contribution of different components to the total divergence, both at the inter- and intra-cluster levels by using the concept of statistical distance employing multivariate measurements and Principal Component analysis is used to identify traits that explain the phenotype variability best. 1 College of Horticulture, Sri Konda Laxman Telangana State Horticultural University, Rajendranagar-500 030, Telangana, India. 2 Sri Konda Laxman Telangana State Horticultural University, Mulugu, Siddipet-502 279, Telangana, India. 3 Professor Jayashankar Telangana State Agricultural University, Rajendranagar-500 030, Telangana, India. 4 College of Horticulture, Sri Konda Laxman Telangana State Horticultural University, Mojerla-509 219, Telangana, India. Corresponding Author: B. Soujanya, College of Horticulture, Sri Konda Laxman Telangana State Horticultural University, Rajensranagar, Hyderabad-500 030, Telangana, India. Email: bsoujanya129@gmail.com How to cite this article: Soujanya, B., Kumar, A.K., Vanisri, S., Sreedhar, M., Saidiah, P., Bhagwan, A. and Sathish, G. (2022). Assessment of Genetic Divergence by Using Multivariate Analysis for Physico Chemical Characters of Mango Table and Juicy Cultivars Grown in Telangana Region. Asian Journal of Dairy and Food Research. DOI: 10.18805/ajdfr.DR-1776. Submitted: 29-06-2021 Accepted: 27-11-2021 Online: 17-01-2022 ABSTRACT Background: Mango (Mangifera indica L.) is well known for its diversity in Indian subcontinent and 1000 well known varieties are present all over the India among them 40 to 50 are having commercial importance. The present experiment was carried out at College of Horticulture, Rajendranagar during the year 2018-19 and 2019-20 to assess the genetic diversity in fifty mango cultivars using multivariate analysis over 25 physico-chemical characters. Methods: To assess the genetic diversity using D 2 analysis and principal component analysis over 50 mango cultivars during 2 consecutive years. Result: In the present investigation, the first seven principal components with eigen values more than one contributed 78.50 % of cumulative variance among fifty genotypes. Fifty genotypes were grouped into eight clusters among them cluster I was the largest comprising of twenty-six genotypes. Average inter cluster distance ranged from 218.93 between cluster V and VII to 1475.21 between cluster IV to VIII. Intra cluster distance ranged from 0.00 in cluster V, VI, VII and VIII to 280.69 in cluster III. The present results are most divergent for fruit weight, total phenols content, total flavonoid content, DA reading, fibre content, beta carotene, antioxidant activity, fruit length, fruit thickness. Selection of genotypes from clusters that are far genetically and had the maximum association of physico chemical characters to obtain superior segregants in the advanced generation to improve the quality of breeding in the future. Key words: Cluster distance, Genetic diversity, Hybridization programme, Mango varieties, Principal component analysis, Physico chemical traits.