Path analysis under multiple-trait BLUP: application in the study of interrelationships among traits related to cotton fiber length

Multi-trait best linear unbiased prediction (BLUP) is, generally, the most appropriate method to genetic evaluation because it considers the genetic and residual correlations among traits and conduct to higher selection accuracy. Thus, the present study aimed to identify traits correlated to th...

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Main Authors: Rodrigo Alves, João Rocha, Larissa Teodoro, Luiz Carvalho, Francisco Farias, Marcos Resende, Leonardo Bhering, Paulo Teodoro
Format: Article
Language:English
Published: Facultad de Ciencias Agrarias. Universidad Nacional de Cuyo 2020-10-01
Series:Revista de la Facultad de Ciencias Agrarias
Subjects:
Online Access:http://172.22.185.100/ojs3/index.php/RFCA/article/view/2910
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spelling doaj-169d9f6b82c24703a51cb97776298c642021-04-16T18:40:15ZengFacultad de Ciencias Agrarias. Universidad Nacional de CuyoRevista de la Facultad de Ciencias Agrarias0370-46611853-86652020-10-01Path analysis under multiple-trait BLUP: application in the study of interrelationships among traits related to cotton fiber lengthRodrigo Alves0João Rocha1Larissa Teodoro2Luiz Carvalho3Francisco Farias4Marcos Resende5Leonardo Bhering6Paulo Teodoro7INCT Café/Federal University of Viçosa. Department of Statistics. University Campus. 36570-000. Viçosa, MG. Brazil.Federal University of Viçosa. Department of General Biology. University Campus. 36570-000. Viçosa. MG. Brazil.Federal University of Mato Grosso do Sul. Department of Plant Science. University Campus. 79560-000. Chapadão do Sul. MS. Brazil.National Cotton Research Center. Embrapa Cotton. 58428-095. Campina Grande. PB. Brazil.National Cotton Research Center. Embrapa Cotton. 58428-095. Campina Grande. PB. Brazil.INCT Café/Federal University of Viçosa. Department of Statistics. University Campus. 36570-000. Viçosa, MG. Brazil.Federal University of Viçosa. Department of General Biology. University Campus. 36570-000. Viçosa. MG. Brazil.Federal University of Mato Grosso do Sul. Department of Plant Science. University Campus. 79560-000. Chapadão do Sul. MS. Brazil. Multi-trait best linear unbiased prediction (BLUP) is, generally, the most appropriate method to genetic evaluation because it considers the genetic and residual correlations among traits and conduct to higher selection accuracy. Thus, the present study aimed to identify traits correlated to the fiber length via path analysis under multi-trait BLUP for the cotton breeding. To this end, thirty-six elite lines were evaluated in three environments and phenotyped for many traits related to fiber quality and agronomic traits. Variance components were estimated via residual maximum likelihood (REML). The genetic correlation coefficients among traits were obtained through mixed model output, and to graphically express these results a correlation network was built. Subsequently, we performed path analysis considering fiber length as a principal dependent variable. Genetic parameters obtained by multi-trait BLUP model indicate that the phenotypic variance for most traits is mostly composed of residual effects, which reinforces the need for using more accurate statistical methods such as multi-trait BLUP. The results found for genetic correlations and path analysis under multi-trait BLUP reveal the difficulty of selection based on important fiber quality traits, especially fiber length, since most traits show very low cause-and-effect relationship, and other important traits present undesirable cause-and-effect relationship. Highlights Multiple-trait BLUP is the most appropriate method to predict genetic values. This is the first study in cotton to perform path analysis under multiple-trait BLUP. The findings of this study indicate that there is no genotype presenting all desirable traits. http://172.22.185.100/ojs3/index.php/RFCA/article/view/2910Modelo mixtogenotipo x ambientecorrelación genéticaselección genéticaGossypium hirsutum
collection DOAJ
language English
format Article
sources DOAJ
author Rodrigo Alves
João Rocha
Larissa Teodoro
Luiz Carvalho
Francisco Farias
Marcos Resende
Leonardo Bhering
Paulo Teodoro
spellingShingle Rodrigo Alves
João Rocha
Larissa Teodoro
Luiz Carvalho
Francisco Farias
Marcos Resende
Leonardo Bhering
Paulo Teodoro
Path analysis under multiple-trait BLUP: application in the study of interrelationships among traits related to cotton fiber length
Revista de la Facultad de Ciencias Agrarias
Modelo mixto
genotipo x ambiente
correlación genética
selección genética
Gossypium hirsutum
author_facet Rodrigo Alves
João Rocha
Larissa Teodoro
Luiz Carvalho
Francisco Farias
Marcos Resende
Leonardo Bhering
Paulo Teodoro
author_sort Rodrigo Alves
title Path analysis under multiple-trait BLUP: application in the study of interrelationships among traits related to cotton fiber length
title_short Path analysis under multiple-trait BLUP: application in the study of interrelationships among traits related to cotton fiber length
title_full Path analysis under multiple-trait BLUP: application in the study of interrelationships among traits related to cotton fiber length
title_fullStr Path analysis under multiple-trait BLUP: application in the study of interrelationships among traits related to cotton fiber length
title_full_unstemmed Path analysis under multiple-trait BLUP: application in the study of interrelationships among traits related to cotton fiber length
title_sort path analysis under multiple-trait blup: application in the study of interrelationships among traits related to cotton fiber length
publisher Facultad de Ciencias Agrarias. Universidad Nacional de Cuyo
series Revista de la Facultad de Ciencias Agrarias
issn 0370-4661
1853-8665
publishDate 2020-10-01
description Multi-trait best linear unbiased prediction (BLUP) is, generally, the most appropriate method to genetic evaluation because it considers the genetic and residual correlations among traits and conduct to higher selection accuracy. Thus, the present study aimed to identify traits correlated to the fiber length via path analysis under multi-trait BLUP for the cotton breeding. To this end, thirty-six elite lines were evaluated in three environments and phenotyped for many traits related to fiber quality and agronomic traits. Variance components were estimated via residual maximum likelihood (REML). The genetic correlation coefficients among traits were obtained through mixed model output, and to graphically express these results a correlation network was built. Subsequently, we performed path analysis considering fiber length as a principal dependent variable. Genetic parameters obtained by multi-trait BLUP model indicate that the phenotypic variance for most traits is mostly composed of residual effects, which reinforces the need for using more accurate statistical methods such as multi-trait BLUP. The results found for genetic correlations and path analysis under multi-trait BLUP reveal the difficulty of selection based on important fiber quality traits, especially fiber length, since most traits show very low cause-and-effect relationship, and other important traits present undesirable cause-and-effect relationship. Highlights Multiple-trait BLUP is the most appropriate method to predict genetic values. This is the first study in cotton to perform path analysis under multiple-trait BLUP. The findings of this study indicate that there is no genotype presenting all desirable traits.
topic Modelo mixto
genotipo x ambiente
correlación genética
selección genética
Gossypium hirsutum
url http://172.22.185.100/ojs3/index.php/RFCA/article/view/2910
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