Identification of Adapted and Stable Cultivars, Using the AMMI Model and Linear Regression Technique

Authors

  • Cristina Dias Polytechnic Institute of Portalegre, Campus Politécnico,10, 7300-555 Portalegre, Portugal and Center of Mathematics and Applications (CMA), Portugal.
  • Carla Santos Polytechnic Institute of Beja, R. de Pedro Soares, 7800-295 Beja, Portugal and Center of Mathematics and Applications (CMA), Portugal.
  • Isabel Borges Polytechnic Institute of Portalegre, Campus Politécnico,10, 7300-555 Portalegre, Portugal and VALORIZA, Portalegre, Portugal.
  • Joao Tiago Mexia Faculty of Sciences and Technology, Nova University of Lisbon, Largo da Torre, 2825-149 Caparica, Portugal and Center of Mathematics and Applications (CMA), Portugal.

DOI:

https://doi.org/10.9734/bpi/eias/v4/5419C

Keywords:

Adaptability analysis, cultivar recommendation, GE interaction, AMMI analysis

Abstract

Identify superior performing genotypes across a wide range of environmental conditions, is an important topic in genetics, plant breeding, and agronomy. This paper focus in the main properties of linear regression analysis (LR), and of the additive main effects and multiplicative interaction (AMMI) model. The study compares LR and AMMI with particular emphasis in determining yield stability of different genotypes across different environments. The application is made using a data set from a breeding program of durum wheat (Triticum aestivum L., Durum Group) conducted in Portugal. The results of the two models shows that the AMMI analysis had more stable results, being more efficient in describing the GE interaction than the LR.

Published

2023-06-05

How to Cite

Cristina Dias, Carla Santos, Isabel Borges, & Joao Tiago Mexia. (2023). Identification of Adapted and Stable Cultivars, Using the AMMI Model and Linear Regression Technique. Emerging Issues in Agricultural Sciences Vol. 4, 1–8. https://doi.org/10.9734/bpi/eias/v4/5419C

Issue

Emerging Issues in Agricultural Sciences Vol. 4

Section

Chapters