Tâmara Rebecca Albuquerque de Oliveira, Hélio Wilson Lemos de Carvalho, Moyses Nascimento, Matheus Massariol Suela, Milton José Cardoso, Gustavo Hugo Ferreira Oliveira
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引用次数: 0
Abstract
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. The experiment was set up in a randomized block design with two repetitions, where 25 maize hybrids were evaluated in different states. Initially, the analysis of variance was performed. Then, the Bayesian approach of the segmented regression method was used to select the hybrids regarding adaptability and stability. There was a difference between the genotypes indicated using the a priori distribution and those indicated by the minimally informative a priori distribution. Hybrids 20A55HX, 2B433HX, 2B512HX, and P2830H were considered ideal for the Northeast region.
期刊介绍:
The CBAB – CROP BREEDING AND APPLIED BIOTECHNOLOGY (ISSN 1984-7033) – is the official quarterly journal of the Brazilian Society of Plant Breeding, abbreviated CROP BREED APPL BIOTECHNOL.
It publishes original scientific articles, which contribute to the scientific and technological development of plant breeding and agriculture. Articles should be to do with basic and applied research on improvement of perennial and annual plants, within the fields of genetics, conservation of germplasm, biotechnology, genomics, cytogenetics, experimental statistics, seeds, food quality, biotic and abiotic stress, and correlated areas. The article must be unpublished. Simultaneous submitting to another periodical is ruled out. Authors are held solely responsible for the opinions and ideas expressed, which do not necessarily reflect the view of the Editorial board. However, the Editorial board reserves the right to suggest or ask for any modifications required. The journal adopts the Ithenticate software for identification of plagiarism. Complete or partial reproduction of articles is permitted, provided the source is cited. All content of the journal, except where identified, is licensed under a Creative Commons attribution-type BY. All articles are published free of charge. This is an open access journal.