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...

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Autores principales: Igor Ferreira Coelho, Marco Antônio Peixoto, Tiago de Souza Marçal, Arthur Bernardeli, Rodrigo Silva Alves, Rodrigo Oliveira de Lima, Edésio Fialho dos Reis, Leonardo Lopes Bhering
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Publicado: Public Library of Science (PLoS) 2021
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Acceso en línea:https://doaj.org/article/106ac149ede0474f9b5c9fe13bc44965
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spelling oai:doaj.org-article:106ac149ede0474f9b5c9fe13bc449652021-11-04T06:07:13ZAccounting for spatial trends in multi-environment diallel analysis in maize breeding1932-6203https://doaj.org/article/106ac149ede0474f9b5c9fe13bc449652021-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8530354/?tool=EBIhttps://doaj.org/toc/1932-6203Spatial 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.Igor Ferreira CoelhoMarco Antônio PeixotoTiago de Souza MarçalArthur BernardeliRodrigo Silva AlvesRodrigo Oliveira de LimaEdésio Fialho dos ReisLeonardo Lopes BheringPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 10 (2021)
institution DOAJ
collection DOAJ
language EN
topic Medicine
R
Science
Q
spellingShingle Medicine
R
Science
Q
Igor Ferreira Coelho
Marco Antônio Peixoto
Tiago de Souza Marçal
Arthur Bernardeli
Rodrigo Silva Alves
Rodrigo Oliveira de Lima
Edésio Fialho dos Reis
Leonardo Lopes Bhering
Accounting for spatial trends in multi-environment diallel analysis in maize breeding
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 article
author Igor Ferreira Coelho
Marco Antônio Peixoto
Tiago de Souza Marçal
Arthur Bernardeli
Rodrigo Silva Alves
Rodrigo Oliveira de Lima
Edésio Fialho dos Reis
Leonardo Lopes Bhering
author_facet Igor Ferreira Coelho
Marco Antônio Peixoto
Tiago de Souza Marçal
Arthur Bernardeli
Rodrigo Silva Alves
Rodrigo Oliveira de Lima
Edésio Fialho dos Reis
Leonardo Lopes Bhering
author_sort Igor Ferreira Coelho
title 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_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_sort accounting for spatial trends in multi-environment diallel analysis in maize breeding
publisher Public Library of Science (PLoS)
publishDate 2021
url https://doaj.org/article/106ac149ede0474f9b5c9fe13bc44965
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