Deciphering the Morpho-physiological and Grain Yield Trait Architecture of Pigeonpea (Cajanus cajan L. millsp.) through Integrated Variability and Multivariate Analyses
Krishna B. Gaiwal
*
Department of Genetics and Plant Breeding, Vasantrao Naik Marathwada Agricultural University, Parbhani, 431 401, India and International Crops Research Institute for the Semi Arid Tropics (ICRISAT), Patancheru, Telangana, 502 324, India.
Shivaji P. Mehtre
Department of Genetics and Plant Breeding, Vasantrao Naik Marathwada Agricultural University, Parbhani, 431 401, India.
Hirakant H. Kalpande
Department of Genetics and Plant Breeding, Vasantrao Naik Marathwada Agricultural University, Parbhani, 431 401, India.
Deepak K. Patil
Department of Genetics and Plant Breeding, Vasantrao Naik Marathwada Agricultural University, Parbhani, 431 401, India.
Dilip K. Zate
Department of Genetics and Plant Breeding, Vasantrao Naik Marathwada Agricultural University, Parbhani, 431 401, India.
Godavari Pawar
Department of Genetics and Plant Breeding, Vasantrao Naik Marathwada Agricultural University, Parbhani, 431 401, India.
Manzoor Hussain Dar
International Crops Research Institute for the Semi Arid Tropics (ICRISAT), Patancheru, Telangana, 502 324, India.
Prakash I. Gangashetty
International Crops Research Institute for the Semi Arid Tropics (ICRISAT), Patancheru, Telangana, 502 324, India.
*Author to whom correspondence should be addressed.
Abstract
Pigeonpea (Cajanus cajan (L.) Millsp.) is a major grain legume of the semi-arid tropics, contributing to food and nutritional security. A comprehensive understanding of genetic variability and trait interrelationships is essential for enhancing selection efficiency. In the present study, 40 pigeonpea genotypes were evaluated under field conditions to quantify genetic variability, associations among phenological, physiological, and yield-related traits, and identify major sources of phenotypic variation using multivariate analysis. Analysis of variance revealed significant genotypic differences for most of the traits. Correlation analysis showed that grain yield was positively associated with phenological traits and key physiological attributes, highlighting the integrated role of maturity duration and physiological efficiency in yield determination. Principal component analysis identified three major components explaining more than 75% of the total phenotypic variation. The first principal component was primarily influenced by physiological traits, the second by phenological and yield-related traits, and the third by seed weight. Among the evaluated genotypes, ICP 7650, PRG 176, and ICPL 88039 displayed the highest mean photosynthetic rates, whereas ICP 11611, ICP 8148, and ICP 7650 excelled in grain yield performance. Overall, the integration of variability parameters, correlation analysis, and PCA provided valuable insights into trait architecture in pigeonpea and identified key traits contributing to phenotypic diversity, strengthening targeted s breeding and selection strategies.
Keywords: Pigeonpea, genetic variability, heritability, grain yield, physiological traits, correlation analysis, principal component analysis