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Accounting for spatial trends in multi-environment diallel analysis in maize breeding
Spatial trends represent an obstacle to genetic evaluation in maize breeding. Spatial analyses can correct spatial trends, which allow for an increase in selective accuracy. The objective of this study was to compare the spatial (SPA) and non-spatial (NSPA) models in diallel multi-environment trial...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8530354/ https://www.ncbi.nlm.nih.gov/pubmed/34673808 http://dx.doi.org/10.1371/journal.pone.0258473 |
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author | Ferreira Coelho, Igor Peixoto, Marco Antônio Marçal, Tiago de Souza Bernardeli, Arthur Silva Alves, Rodrigo de Lima, Rodrigo Oliveira dos Reis, Edésio Fialho Bhering, Leonardo Lopes |
author_facet | Ferreira Coelho, Igor Peixoto, Marco Antônio Marçal, Tiago de Souza Bernardeli, Arthur Silva Alves, Rodrigo de Lima, Rodrigo Oliveira dos Reis, Edésio Fialho Bhering, Leonardo Lopes |
author_sort | Ferreira Coelho, Igor |
collection | PubMed |
description | Spatial trends represent an obstacle to genetic evaluation in maize breeding. Spatial analyses can correct spatial trends, which allow for an increase in selective accuracy. The objective of this study was to compare the spatial (SPA) and non-spatial (NSPA) models in diallel multi-environment trial analyses in maize breeding. The trials consisted of 78 inter-populational maize hybrids, tested in four environments (E1, E2, E3, and E4), with three replications, under a randomized complete block design. The SPA models accounted for autocorrelation among rows and columns by the inclusion of first-order autoregressive matrices (AR1 ⊗ AR1). Then, the rows and columns factors were included in the fixed and random parts of the model. Based on the Bayesian information criteria, the SPA models were used to analyze trials E3 and E4, while the NSPA model was used for analyzing trials E1 and E2. In the joint analysis, the compound symmetry structure for the genotypic effects presented the best fit. The likelihood ratio test showed that some effects changed regarding significance when the SPA and NSPA models were used. In addition, the heritability, selective accuracy, and selection gain were higher when the SPA models were used. This indicates the power of the SPA model in dealing with spatial trends. The SPA model exhibits higher reliability values and is recommended to be incorporated in the standard procedure of genetic evaluation in maize breeding. The analyses bring the parents 2, 10 and 12, as potential parents in this microregion. |
format | Online Article Text |
id | pubmed-8530354 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-85303542021-10-22 Accounting for spatial trends in multi-environment diallel analysis in maize breeding Ferreira Coelho, Igor Peixoto, Marco Antônio Marçal, Tiago de Souza Bernardeli, Arthur Silva Alves, Rodrigo de Lima, Rodrigo Oliveira dos Reis, Edésio Fialho Bhering, Leonardo Lopes PLoS One Research Article Spatial trends represent an obstacle to genetic evaluation in maize breeding. Spatial analyses can correct spatial trends, which allow for an increase in selective accuracy. The objective of this study was to compare the spatial (SPA) and non-spatial (NSPA) models in diallel multi-environment trial analyses in maize breeding. The trials consisted of 78 inter-populational maize hybrids, tested in four environments (E1, E2, E3, and E4), with three replications, under a randomized complete block design. The SPA models accounted for autocorrelation among rows and columns by the inclusion of first-order autoregressive matrices (AR1 ⊗ AR1). Then, the rows and columns factors were included in the fixed and random parts of the model. Based on the Bayesian information criteria, the SPA models were used to analyze trials E3 and E4, while the NSPA model was used for analyzing trials E1 and E2. In the joint analysis, the compound symmetry structure for the genotypic effects presented the best fit. The likelihood ratio test showed that some effects changed regarding significance when the SPA and NSPA models were used. In addition, the heritability, selective accuracy, and selection gain were higher when the SPA models were used. This indicates the power of the SPA model in dealing with spatial trends. The SPA model exhibits higher reliability values and is recommended to be incorporated in the standard procedure of genetic evaluation in maize breeding. The analyses bring the parents 2, 10 and 12, as potential parents in this microregion. Public Library of Science 2021-10-21 /pmc/articles/PMC8530354/ /pubmed/34673808 http://dx.doi.org/10.1371/journal.pone.0258473 Text en © 2021 Ferreira Coelho et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Ferreira Coelho, Igor Peixoto, Marco Antônio Marçal, Tiago de Souza Bernardeli, Arthur Silva Alves, Rodrigo de Lima, Rodrigo Oliveira dos Reis, Edésio Fialho Bhering, Leonardo Lopes Accounting for spatial trends in multi-environment diallel analysis in maize breeding |
title | Accounting for spatial trends in multi-environment diallel analysis in maize breeding |
title_full | Accounting for spatial trends in multi-environment diallel analysis in maize breeding |
title_fullStr | Accounting for spatial trends in multi-environment diallel analysis in maize breeding |
title_full_unstemmed | Accounting for spatial trends in multi-environment diallel analysis in maize breeding |
title_short | Accounting for spatial trends in multi-environment diallel analysis in maize breeding |
title_sort | accounting for spatial trends in multi-environment diallel analysis in maize breeding |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8530354/ https://www.ncbi.nlm.nih.gov/pubmed/34673808 http://dx.doi.org/10.1371/journal.pone.0258473 |
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