Open AccessMulti-information analysis for recommendation of flooded-irrigated rice for adaptability and phenotypic stability
Author(s) -
Antônio Carlos Siva Júnior,
Michele Jorge Silva,
Weverton Gomes da Costa,
Ithalo Coelho de Sousa,
Cosme Damião Cruz,
Moysés Nascimento,
Plínio César Soares
Publication year - 2021
Publication title -
agronomy science and biotechnology
Language(s) - English
Resource type - Journals
ISSN - 2359-1455
DOI - 10.33158/asb.r145.v8.2022
Subject(s) - adaptability , cultivar , stability (learning theory) , selection (genetic algorithm) , agriculture , agronomy , microbiology and biotechnology , agricultural engineering , computer science , biology , ecology , engineering , artificial intelligence , machine learning
The GxE interaction is one of the major difficulties of plant breeding programs, both in the selection phase and in the recommendation of cultivars. To assess adaptability and stability, various statistical methods are used. The simultaneous use of some methodologies, using multi-information criteria for cultivar’s recommendation, can extract information that cannot be observed using each methodology separately. The aim of this work was to perform a large description of the behavior of flooded-irrigated rice genotypes, responding to environmental variations, using methods already established in the literature, but exploring the particularities of each methodology that together establish an information criterion for cultivar recommendation. To this end, 18 rice genotypes belonging to flood-irrigated rice breeding program were evaluated over four agricultural years, 2012/2013 to 2015/2016, totaling 12 environments (3 sites × 4 years). Multi-information estimates were performed to adaptability and stability analysis. There was no sign for the effect of the genotypes, and there was the significance of the effects of environment and GxE interaction. The aggregation of information and the large description of the behavior of the flooded rice genotypes demonstrated to be an efficient tool for studies of adaptability and stability.