Genetic Divergence and Principal Component Analysis for Yield and Yield Components of Lentil (Lens culinaris L. Medik.) Genotypes
Nitin Kumar
Department of Genetics and Plant Breeding, Banda University of Agriculture and Technology, Banda (U.P.), India.
Harsh Jainth
Department of Genetics and Plant Breeding, Banda University of Agriculture and Technology, Banda (U.P.), India.
Khushboo Devi
Department of Genetics and Plant Breeding, Banda University of Agriculture and Technology, Banda (U.P.), India.
Pragya Jee
Department of Genetics and Plant Breeding, Banda University of Agriculture and Technology, Banda (U.P.), India.
Anurag
Department of Genetics and Plant Breeding, Banda University of Agriculture and Technology, Banda (U.P.), India.
Mukul
Department of Genetics and Plant Breeding, Banda University of Agriculture and Technology, Banda (U.P.), India.
Chirag
Department of Genetics and Plant Breeding, Banda University of Agriculture and Technology, Banda (U.P.), India.
Divya Singh
Department of Genetics and Plant Breeding, Banda University of Agriculture and Technology, Banda (U.P.), India.
Arvind Patel
Department of Genetics and Plant Breeding, Banaras Hindu University, Varanasi, (U.P.), India.
Kamaluddin *
Department of Genetics and Plant Breeding, Banda University of Agriculture and Technology, Banda (U.P.), India.
*Author to whom correspondence should be addressed.
Abstract
Aims: The present study aimed to assess the genetic diversity among 25 lentil (Lens culinaris L. Medikus) genotypes, including three standard checks, with a focus on identifying high-yielding genotypes and those with elevated iron and zinc content, to support future breeding programs.
Study Design: The experiment was laid out in a randomized block design (RBD) with three replications.
Place and Duration of Study: The study was conducted at the Research Farm of Banda University of Agriculture and Technology, Banda, Uttar Pradesh, India, during the rabi season of 2023–2024.
Methodology: Analysis of variance (ANOVA) was performed to determine genotypic variation. Cluster analysis and principal component analysis (PCA) were used to study genetic diversity and relationships among the genotypes.
Results: Significant genotypic differences were observed for most traits, indicating ample genetic variability. Cluster analysis grouped genotypes into three distinct clusters, with Cluster II containing the most genotypes (15), followed by Clusters I and III (5 each). The highest inter-cluster distance was found between Clusters II and III, suggesting the potential for generating superior recombinants through inter-cluster hybridization. PCA revealed four principal components accounting for 72.30% of total variance. The highest seed yield was recorded in genotypes ILL-753/ILL-8461 (0.294 kg/plot), ILL-7537/ILL-800-S4 (0.280 kg/plot), and Black lentil (0.284 kg/plot). Genotypes IPL-316 (119.5 mg/kg) and PL-4 (106.3 mg/kg) had the highest iron content, while X20115-89-23-S4 (54.4 mg/kg) and ILL-10657 (52.1 mg/kg) had the highest zinc content.
Conclusion: The highest seed yield was recorded in genotypes ILL-753/ILL-8461 (0.294 kg/plot), ILL-7537/ILL-800-S4 (0.280 kg/plot), and Black Lentil (0.284 kg/plot). The highest iron content was observed in genotypes IPL-316 (119.5 mg/kg) and PL-4 (106.3 mg/kg), while the highest zinc content was found in genotypes X20115-89-23-S4 (54.4 mg/kg) and ILL-10657 (52.1 mg/kg)."
Keywords: Analysis of variance, cluster analysis, iron, lentil, principal components analysis (PCA), zinc