Title:	Bayesian segmented regression model to evaluate the adaptability and stability of maize in Northeastern Brazil.
Authors:	OLIVEIRA, T. R. A. de CARVALHO, H. W. L. de NASCIMENTO, M. SUELA, M. M. CARDOSO, M. J. OLIVEIRA, G. H. F.
Affiliation:	TÂMARA REBECCA ALBUQUERQUE DE OLIVEIRA, UNIVERSIDADE ESTADUAL DO NORTE FLUMINENSE DARCY RIBEIRO; HELIO WILSON LEMOS DE CARVALHO, CPATC; MOYSES NASCIMENTO, UNIVERSIDADE FEDERAL DE VIÇOSA; MATHEUS MASSARIOL SUELA, UNIVERSIDADE FEDERAL DE VIÇOSA; MILTON JOSE CARDOSO, CPAMN; GUSTAVO HUGO FERREIRA OLIVEIRA UNIVERSIDADE FEDERAL DE SERGIPE, UNIVERSIDADE FEDERAL DE SERGIPE.
Date Issued:	2023
Citation:	Crop Breeding and Applied Biotechnology, v. 23, n. 3, e44692334, 2023.
Description:	Although maize is one of the main crops in the Northeast region, yield is still considered low when compared to other regions. One of the main solutions to increasing yield is the selection of cultivars adapted to the conditions of the Northeast region. Thus, the present study aims to use the Bayesian segmented regression model to evaluate the adaptability and stability of maize.
Thesagro:	Zea Mays
Keywords:	Fator de Bayes Interação genótipo x ambiente
Type of Material:	Artigo de periódico
Access:	openAccess
Appears in Collections:	Artigo em periódico indexado (CPAMN)