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 the fi...
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| Autores principales: | , , , , , , , |
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| Formato: | Online |
| Lenguaje: | eng |
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Facultad de Ciencias Agrarias-UNCuyo
2021
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| Materias: | |
| Acceso en línea: | https://revistas.uncu.edu.ar/ojs3/index.php/RFCA/article/view/2910 |
| id |
I11-R107article-2910 |
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Universidad Nacional de Cuyo |
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Revistas en línea |
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Revistas en línea |
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Revista de la Facultad de Ciencias Agrarias |
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Revista de la Facultad de Ciencias Agrarias |
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I-11 |
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R-107 |
| language |
eng |
| format |
Online |
| author |
Alves, Rodrigo Rocha, João Teodoro, Larissa Carvalho, Luiz Farias, Francisco Resende, Marcos Bhering, Leonardo Teodoro, Paulo |
| spellingShingle |
Alves, Rodrigo Rocha, João Teodoro, Larissa Carvalho, Luiz Farias, Francisco Resende, Marcos Bhering, Leonardo Teodoro, Paulo Path analysis under multiple-trait BLUP: application in the study of interrelationships among traits related to cotton fiber length Mixed model genotype x environment genetic correlation genetic selection Gossypium hirsutum Modelo mixto genotipo x ambiente correlación genética selección genética Gossypium hirsutum |
| author_facet |
Alves, Rodrigo Rocha, João Teodoro, Larissa Carvalho, Luiz Farias, Francisco Resende, Marcos Bhering, Leonardo Teodoro, Paulo |
| author_sort |
Alves, Rodrigo |
| 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 |
| 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.
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| publisher |
Facultad de Ciencias Agrarias-UNCuyo |
| publishDate |
2021 |
| url |
https://revistas.uncu.edu.ar/ojs3/index.php/RFCA/article/view/2910 |
| topic |
Mixed model genotype x environment genetic correlation genetic selection Gossypium hirsutum Modelo mixto genotipo x ambiente correlación genética selección genética Gossypium hirsutum |
| topic_facet |
Mixed model genotype x environment genetic correlation genetic selection Gossypium hirsutum Modelo mixto genotipo x ambiente correlación genética selección genética Gossypium hirsutum |
| work_keys_str_mv |
AT alvesrodrigo pathanalysisundermultipletraitblupapplicationinthestudyofinterrelationshipsamongtraitsrelatedtocottonfiberlength AT rochajoao pathanalysisundermultipletraitblupapplicationinthestudyofinterrelationshipsamongtraitsrelatedtocottonfiberlength AT teodorolarissa pathanalysisundermultipletraitblupapplicationinthestudyofinterrelationshipsamongtraitsrelatedtocottonfiberlength AT carvalholuiz pathanalysisundermultipletraitblupapplicationinthestudyofinterrelationshipsamongtraitsrelatedtocottonfiberlength AT fariasfrancisco pathanalysisundermultipletraitblupapplicationinthestudyofinterrelationshipsamongtraitsrelatedtocottonfiberlength AT resendemarcos pathanalysisundermultipletraitblupapplicationinthestudyofinterrelationshipsamongtraitsrelatedtocottonfiberlength AT bheringleonardo pathanalysisundermultipletraitblupapplicationinthestudyofinterrelationshipsamongtraitsrelatedtocottonfiberlength AT teodoropaulo pathanalysisundermultipletraitblupapplicationinthestudyofinterrelationshipsamongtraitsrelatedtocottonfiberlength |
| _version_ |
1800220886761996288 |
| spelling |
I11-R107article-29102021-07-07T00:50:21Z Path analysis under multiple-trait BLUP: application in the study of interrelationships among traits related to cotton fiber length Path analysis under multiple-trait BLUP: application in the study of interrelationships among traits related to cotton fiber length Alves, Rodrigo Rocha, João Teodoro, Larissa Carvalho, Luiz Farias, Francisco Resende, Marcos Bhering, Leonardo Teodoro, Paulo Mixed model genotype x environment genetic correlation genetic selection Gossypium hirsutum Modelo mixto genotipo x ambiente correlación genética selección genética Gossypium hirsutum 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. 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. Facultad de Ciencias Agrarias-UNCuyo 2021-07-07 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion application/pdf https://revistas.uncu.edu.ar/ojs3/index.php/RFCA/article/view/2910 10.48162/rev.39.001 Revista de la Facultad de Ciencias Agrarias UNCuyo; Vol. 53 No. 1 (2021): January-June; 1-10 Revista de la Facultad de Ciencias Agrarias UNCuyo; Vol. 53 Núm. 1 (2021): Enero-Junio; 1-10 1853-8665 0370-4661 eng https://revistas.uncu.edu.ar/ojs3/index.php/RFCA/article/view/2910/2824 Derechos de autor 2021 Revista de la Facultad de Ciencias Agrarias UNCuyo https://creativecommons.org/licenses/by-nc-sa/3.0/deed.es |
