Legume Research
Web of Science
  • Year: 2026
  • Volume: 49
  • Issue: 9

Parametric and Non-parametric Statistical Approaches for Estimation of Genotype × Environment Interaction of Pigeon Pea [Cajanus cajan (L.) Millspaugh] Genotypes

  • Author:
  • Alok Shrivastava1, Y.P. Bhavana1, Nitin Varshney1, Y.A. Garde1, K.G. Modha2, Neha Mishra3, Pradeep Mishra4,*
  • Total Page Count: 9
  • Page Number: 1499 to 1507

1Department of Agricultural Statistics, N.M. College of Agriculture, Navsari Agricultural University, Navsari-396 450, Gujarat, India

2Department of Plant Breeding and Genetics, N.M. College of Agriculture, Navsari Agricultural University, Navsari-396 450, Gujarat, India

3Department of Mathematics and Statistics, School of Physical Sciences, Amity University, Mohali-140 306, Punjab, India

4College of Agriculture, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Rewa-486 001, Madhya Pradesh, India

*Corresponding Author: Pradeep Mishra, College of Agriculture, Jawaharlal Nehru Krishi Vishwa Vidyalaya, Rewa-486 001, Madhya Pradesh, India, Email: pradeepjnkvv@gmail.com

Abstract

The genotype-by-site interaction might be stronger than the genotype-by-year interaction, making it difficult to identify superior genotypes in multi-location trials. This is influenced by the Genotype × Environment interaction (GEI). The estimation of G, E and G × E interactions (or GEI) ensures valid recommendations of suitable varieties able to overcome the pressure due to variable occurring conditions. The determination of GEI factors helps geneticists in their breeding programs to shift the selection toward varieties suited for wide environments or specific to certain niches.

This requires genotype evaluation in multi-environment trials in the latter stages of selection. To evaluate genotype-environment interaction (GEI), fourteen pigeon pea genotypes were studied in four Gujarat sites. The additive main effects and multiplicative interaction (AMMI) analysis of variance (ANOVA) showed that genotype-environment interaction (GEI), IPCA 1 and IPCA 2 were significant across all genotypes.

Pigeon pea genotype NPMK-15-05 (G9) yielded best. AMMI 1 and 2 plots showed stable ICPL-87119 (G12) and BP-12-31 (G5) genotypes. The genotypes with the strongest non-parametric stability were NPMK-15-05 (G9), ICPL-87119 (G12) and NPMK-15–03 (G8). GGE (Which-win-where) biplot analysis showed that NPMK-15-05 (G9) won.

Keywords

AMMI, G × E interaction (GEI), GGE biplot, Non-parametric statistics, Parametric, Pigeon pea