Multi-trait Analysis and Clustering of Forage Pearl Millet Genotypes in Semi-arid Conditions
Patel Supriya
S.V. Agricultural College, Acharya N.G. Ranga Agricultural University, Tirupati-517502, Andhra Pradesh, India.
Avinash Singode *
Indian Institute of Millets Research, Rajendranagar, Hyderabad-500030, Telangana, India.
D. Mohan Reddy
Acharya N.G. Ranga Agricultural University, Lam, Guntur-522034, Andhra Pradesh, India.
Venkateswarlu Ronda
Indian Institute of Millets Research, Rajendranagar, Hyderabad-500030, Telangana, India.
D. Seva Nayak
Indian Institute of Millets Research, Rajendranagar, Hyderabad-500030, Telangana, India.
M. Reddisekhar
S.V. Agricultural College, Acharya N.G. Ranga Agricultural University, Tirupati-517502, Andhra Pradesh, India.
*Author to whom correspondence should be addressed.
Abstract
The present study evaluated genetic variability and trait associations in 103 forage pearl millet genotypes (97 genotypes and 6 checks) across three distinct environments (e.g., the Kharif season of 2022 (E1), Summer season of 2023 (E2), and Kharif season of 2023 (E3)) during 2022-23. Sixteen morphological traits were assessed using a randomized complete block design with two replications. Significant differences were observed among genotypes, environments, and genotype × environment interactions. Correlation analysis identified key traits positively associated with green fodder yield, such as leaf length, leaf width, and plant height at first cut. Principal component analysis revealed that four principal components explained 72% of the total variability, with the first component influenced by leaf count and width. Hierarchical cluster analysis grouped genotypes into five clusters, with Cluster IV showing superior forage traits. This study identifies promising genotypes for future breeding programs focused on improving forage productivity in arid and semi-arid regions.
Keywords: Forage improvement, trait associations, principal component analysis, cluster analysis, biomass yield