Legume Research
Web of Science
  • Year: 2026
  • Volume: 49
  • Issue: 8

Integrating Multivariate and Econometric Approaches to Assess Yield-contributing Traits in Field Pea Production

  • Author:
  • Subhash Kumar Jawla1, Namami Gohain2, Bhartendu Yadav1,*, Pradeep Joliya3, Shubh Laxmi4, Gaurav Tomer5, Rowndel Khwairakpam6, Atin Kumar7
  • Total Page Count: 9
  • Page Number: 1365 to 1373

1Department of Agricultural Economics and Extension, School of Agriculture, Lovely Professional University, Phagwara-144 411, Punjab, India

2Department of Economics and Sociology, Punjab Agriculture University, Ludhiana-141 004, Punjab, India

3Faculty of Agricultural Sciences, GLA University, Mathura-281 406, Uttar Pradesh, India

4Bihar Agricultural University, Sabour, Bhagalpur-813 210, Bihar, India

5Faculty of Agriculture, Guru Kashi University, Bathinda-151 302, Punjab, India

6School of Agriculture, Graphic Era Hill University, Dehradun-248 002, Uttarakhand, India

7School of Agriculture, Uttaranchal University, Dehradun-248 007, Uttarakhand, India

*Corresponding Author: Bhartendu Yadav, Department of Agricultural Economics and Extension, School of Agriculture, Lovely Professional University, Phagwara-144 411, Punjab, India, Email: yadvbhartendu@gmail.com

Abstract

It is essential to identify the important traits that affect the seed yield and maximize the productivity and guide the breeding programs. Research has shown variations in the factors that determine yield, but the issue of prioritizing traits for breeding in pea cultivation is still unresolved.

In this study, the relationship between the key morphological and yield-related traits of peas was analysed using multiple linear regression and principal component analysis (PCA). The 94 varieties of peas were evaluated on the basis of seed yield, number of legumes, number of seeds per pod, pod length, plant height and number of branches. The statistical models were reliably validated through diagnostic plots and sampling adequacy measures.

Positive seed yield indicators found significant were pod length, number of pods per plant and number of seeds per pod; whereas negligible effect was found for plant height and number of branches. PCA confirmed the multivariate structure of yield and highlighted breeding traits as its main drivers. These findings provide solid and useful information for improving pea varieties and provide guidance to breeders to focus on optimizing pod and seed traits to increase yields under similar growing conditions.

Keywords

Agronomical traits, Econometrics, Multivariate, PCA, Pea, Yield