Assessment of Genetic Diversity among Different Soybean Genotypes
A. S. Jadhav
Department of Genetics and Plant Breeding, College of Agriculture, Pune – 411005, India.
R. D. Nimbalkar
Agriculture Research Station, Karad – 415114, India.
C. S. Shinde *
Mahatma Phule Krishi Vidyapeeth, Rahuri – 413722, India.
H. J. Rajput
AICRP on Safflower, ZARS, Solapur – 413002, India.
M. P. Deshmukh
Agriculture Research Station, Kasbe Digraj, Sangali – 416305, India.
*Author to whom correspondence should be addressed.
Abstract
The present investigation was conducted at the Botany Research Farm, College of Agriculture, Pune, during kharif 2021 to assess genetic diversity among 31 soybean genotypes. The experiment was laid out in a randomised block design with three replications. Eleven characters were recorded: days to 50% flowering, days to maturity, plant height, branches per plant, pods per plant, seeds per pod, 100-seed weight, seed yield per plant, protein content, oil content and percent disease index for pod blight. Analysis of variance showed highly significant differences among genotypes for all characters, indicating adequate variability for evaluation. Genetic divergence was assessed using Mahalanobis D² statistics, and the genotypes were grouped into nine clusters. Cluster I contained the largest number of genotypes, whereas the remaining clusters were solitary. The highest inter-cluster distance was observed between Cluster II and Cluster IX, followed by Cluster VII and Cluster IX and Cluster II and Cluster VIII, indicating wider divergence. Cluster IX recorded higher mean values for pods per plant, seeds per pod and seed yield per plant, whereas other clusters showed superiority for oil content, protein content, 100-seed weight, plant height and days to maturity. Seed yield per plant contributed the most to total divergence, followed by days to maturity, oil content, protein content and 100-seed weight. Based on divergence class analysis and cluster performance, genotypes KDS-726, KDS-344, NRC-163, KDS-992, AMS-100-39, KDS-753, SKF-2036 and AMS-2016-1 were identified as useful breeding material for soybean improvement.
Keywords: Soybean, Glycine max (L.) Merrill, genetic diversity, Mahalanobis D² statistics, cluster analysis, genetic divergence, seed yield, protein content, oil content, pod blight, breeding material