A dataset for the application of the Bayesian AMMI (B-AMMI) model to identify high-yielding and stable barley genotypes

Name: A dataset for the application of the Bayesian AMMI (B-AMMI) model to identify high-yielding and stable barley genotypes
Creator: Salim Rahmati
Published: 2026-09-08T07:50:30.773Z
Keywords: Agriculture

Rahmati, Salim; Pour Aboughadareh, Alireza; Azizi-Mezhad, Reza; Shooshtari, Lia; Etminan, Alireza; Jamshidi, Bita; Bocianowski, Jan; Tratwal, Anna; Jadidi, Omid

doi:10.17632/pgcwt3r99t.1

A dataset for the application of the Bayesian AMMI (B-AMMI) model to identify high-yielding and stable barley genotypes

Published: 8 September 2026| Version 1 | DOI: 10.17632/pgcwt3r99t.1

Contributors:

Salim Rahmati, Alireza Pour Aboughadareh, Reza Azizi-Mezhad, Lia Shooshtari, Alireza Etminan, Bita Jamshidi, Jan Bocianowski, Anna Tratwal, Omid Jadidi

Description

This dataset came from a multi-environment trial that used an RCBD with three replicates to assess 18 promising barley genotypes and two commercial cultivars during two cropping seasons (2021–2023) across five warm-climate stations in Iran.

A dataset for the application of the Bayesian AMMI (B-AMMI) model to identify high-yielding and stable barley genotypes

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