Machine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands
Corresponding author - E-mail: wep@cca.ufpb.br
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| Format: | article |
| Language: | English |
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2024
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| Online Access: | http://dx.doi.org/10.1590/1807-1929/agriambi.v29n1e283168 http://hdl.handle.net/20.500.14066/4473 |
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| _version_ | 1870612073147269120 |
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| author | Pereira, Walter Esfrain |
| author2 | Centurión Insaurralde, Liz Mariela Valdez Cáceres, Carolina Martínez López, Oscar Roberto |
| author2_role | author author author |
| author_browse | Centurión Insaurralde, Liz Mariela Martínez López, Oscar Roberto Pereira, Walter Esfrain Valdez Cáceres, Carolina |
| author_facet | Pereira, Walter Esfrain Centurión Insaurralde, Liz Mariela Valdez Cáceres, Carolina Martínez López, Oscar Roberto |
| author_role | author |
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| bitstream.url.fl_str_mv | http://repositorio.conacyt.gov.py/bitstream/20.500.14066/4473/1/Machine%20learning%20for%20ranking%20multivariate%20variables%20in%20cattle%20breeds%20raised%20in%20Paraguayan%20wetlands.pdf http://repositorio.conacyt.gov.py/bitstream/20.500.14066/4473/4/Machine%20learning%20for%20ranking%20multivariate%20variables%20in%20cattle%20breeds%20raised%20in%20Paraguayan%20wetlands.jpg http://repositorio.conacyt.gov.py/bitstream/20.500.14066/4473/2/license_rdf http://repositorio.conacyt.gov.py/bitstream/20.500.14066/4473/3/license.txt http://repositorio.conacyt.gov.py/bitstream/20.500.14066/4473/5/Machine%20learning%20for%20ranking%20multivariate%20variables%20in%20cattle%20breeds%20raised%20in%20Paraguayan%20wetlands.pdf.txt |
| dc.creator.none.fl_str_mv | Pereira, Walter Esfrain Centurión Insaurralde, Liz Mariela Valdez Cáceres, Carolina Martínez López, Oscar Roberto |
| dc.date.accessioned.none.fl_str_mv | 2024-10-28T20:12:34Z |
| dc.date.available.none.fl_str_mv | 2024-10-28T20:12:34Z |
| dc.date.issued.none.fl_str_mv | 2024-07-30 |
| dc.format.extent.es.fl_str_mv | 13 páginas |
| dc.identifier.citation.en.fl_str_mv | Pereira, W. E., Centurión, L. M., Valdez, C., & Martínez-López, R. (2025). Machine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands [Aprendizado de máquina para classificação de variáveis multivariadas em raças bovinas criadas em pântanos do Paraguai]. Revista Brasileira de Engenharia Agrícola e Ambiental, 29(1), Artículo e283168. http://dx.doi.org/10.1590/1807-1929/agriambi.v29n1e283168 |
| dc.identifier.doi.es.fl_str_mv | 10.1590/1807-1929/agriambi.v29n1e283168 |
| dc.identifier.essn.es.fl_str_mv | 1807-1929 |
| dc.identifier.issn.es.fl_str_mv | 1415-4366 |
| dc.identifier.other.es.fl_str_mv | http://dx.doi.org/10.1590/1807-1929/agriambi.v29n1e283168 |
| dc.identifier.uri.none.fl_str_mv | http://hdl.handle.net/20.500.14066/4473 |
| dc.language.iso.es.fl_str_mv | eng |
| dc.publisher.es.fl_str_mv | Universidade Federal de Campina Grande. Centro de Tecnologia e Recursos Naturais. Unidade Acadêmica de Engenharia Agrícola |
| dc.relation.projectCONACYT.es.fl_str_mv | BINV02-84 |
| dc.rights.*.fl_str_mv | Atribución 4.0 Internacional |
| dc.rights.accessRights.es.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.rights.copyright.es.fl_str_mv | © 2024 Walter E. Pereira et al. |
| dc.rights.uri.*.fl_str_mv | http://creativecommons.org/licenses/by/4.0/ |
| dc.subject.other.es.fl_str_mv | Blood variables Cattle adaptability in wetlands Phenotypic variables SHAP Variáveis sanguíneas Adaptabilidade bovina em pântanos Variáveis fenotípicas SHAP |
| dc.title.alternative.pt.fl_str_mv | Aprendizado de máquina para classificação de variáveis multivariadas em raças bovinas criadas em pântanos do Paraguai |
| dc.title.es.fl_str_mv | Machine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands |
| dc.type.es.fl_str_mv | info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| description | Corresponding author - E-mail: wep@cca.ufpb.br |
| eu_rights_str_mv | openAccess |
| format | article |
| id | CONACYT_ea715ae54b704523b64ce949bd8ce04b |
| identifier_str_mv | Pereira, W. E., Centurión, L. M., Valdez, C., & Martínez-López, R. (2025). Machine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands [Aprendizado de máquina para classificação de variáveis multivariadas em raças bovinas criadas em pântanos do Paraguai]. Revista Brasileira de Engenharia Agrícola e Ambiental, 29(1), Artículo e283168. http://dx.doi.org/10.1590/1807-1929/agriambi.v29n1e283168 1415-4366 10.1590/1807-1929/agriambi.v29n1e283168 1807-1929 |
| language | eng |
| network_acronym_str | CONACYT |
| network_name_str | Repositorio Institucional CONACYT |
| oai_identifier_str | oai:repositorio.conacyt.gov.py:20.500.14066/4473 |
| publishDate | 2024 |
| publishDateSort | 2024 |
| repository.mail.fl_str_mv | repositorio.institucional@conacyt.gov.py |
| repository.name.fl_str_mv | Repositorio Institucional CONACYT |
| repository_id_str | |
| rights_invalid_str_mv | Atribución 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ © 2024 Walter E. Pereira et al. |
| spelling | 70efde92-247f-4b23-8a08-870760d781b460034cac100-d135-4c49-b180-e1a08b975b46600c1b492eb-54b5-40ef-bb42-41ff7b05f04a6007246002024-10-28T20:12:34Z2024-10-28T20:12:34Z2024-07-30Pereira, W. E., Centurión, L. M., Valdez, C., & Martínez-López, R. (2025). Machine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands [Aprendizado de máquina para classificação de variáveis multivariadas em raças bovinas criadas em pântanos do Paraguai]. Revista Brasileira de Engenharia Agrícola e Ambiental, 29(1), Artículo e283168. http://dx.doi.org/10.1590/1807-1929/agriambi.v29n1e2831681415-4366http://dx.doi.org/10.1590/1807-1929/agriambi.v29n1e283168http://hdl.handle.net/20.500.14066/447310.1590/1807-1929/agriambi.v29n1e2831681807-1929Corresponding author - E-mail: wep@cca.ufpb.brThis study focuses on the performance of cows for meat production raised in the wetlands of Paraguay, examining five cattle genotypes: Brahman, Brangus, and Nelore, as well as two local breeds at risk of extinction. The main objective is to identify and rank phenotypic variables, including blood, clinical, hair, and health variables, demonstrating causal linkage with the live weight of the cows analyzed. Initially, high correlations were identified between different variables included in this study; then, using advanced Machine learning (ML) techniques and the application of Shapley additive explanations (SHAP), a deeper understanding was provided of the factors strongly associated with adaptability in these environments, and, therefore, the respective zootechnical performance. The association between cattle genotypic components linked with the season of the year proved to be the most influential factor on cattle live weight. Variables such as hair length, hematocrit, phosphatase, phosphorus, creatine phosphokinase, creatinine, protein, cortisol, calcium, and the presence of endoparasites were highlighted, demonstrating their hierarchical importance for animal selection. ML models are effective tools for establishing hierarchies of relevance in complex phenotypic multivariable, which is crucial in breeding programs for different zootechnical species and in special and specific environments like wetlands.Este estudo foca no desempenho de vacas para produção de carne, criadas nos pântanos do Paraguai, examinando cinco genótipos bovinos; Brahman, Brangus, Nelore, bem como duas raças locais em risco de extinção. O principal objetivo é identificar e classificar variáveis fenotípicas que incluem variáveis sanguíneas, clínicas, de pelagem e saúde, demonstrando ligação causal com o peso vivo das vacas analisadas. Inicialmente, foram identificadas correlações elevadas entre diferentes variáveis incluídas neste estudo, e, então, utilizando técnicas avançadas de aprendizado de máquina e a aplicação de explicações aditivas de Shapley (SHAP), foi proporcionado um entendimento mais profundo dos fatores fortemente associados à adaptabilidade nestes ambientes, e, portanto, o respectivo desempenho zootécnico. A associação entre o componente genotípico bovino ligado à estação do ano mostrou ser o fator influente mais predominante sobre o peso vivo bovino. Variáveis como comprimento do pelo, hematócrito, fosfatase, fósforo, creatina phosphokinase, creatinina, proteína, cortisol, cálcio e a presença de endoparasitas foram destacadas, demonstrando sua importância hierárquica para a seleção animal. Os modelos de ML são ferramentas eficazes para estabelecer hierarquias de relevância em multivariáveis fenotípicas complexas, o que é crucial em programas de melhoramento genético em diferentes espécies zootécnicas, bem como em ambientes especiais e específicos, como os pântanos.Consejo Nacional de Ciencia y TecnologíaPrograma Paraguayo para el Desarrollo de la Ciencia y Tecnología. Financiamiento de estancias de investigación13 páginasengUniversidade Federal de Campina Grande. Centro de Tecnologia e Recursos Naturais. Unidade Acadêmica de Engenharia AgrícolaAtribución 4.0 Internacionalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccess© 2024 Walter E. Pereira et al.Blood variablesCattle adaptability in wetlandsPhenotypic variablesSHAPVariáveis sanguíneasAdaptabilidade bovina em pântanosVariáveis fenotípicasSHAPMachine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlandsAprendizado de máquina para classificação de variáveis multivariadas em raças bovinas criadas em pântanos do Paraguaiinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersion1Revista Brasileira de Engenharia Agrícola e AmbientalBINV02-8429Pereira, Walter EsfrainCenturión Insaurralde, Liz MarielaValdez Cáceres, CarolinaMartínez López, Oscar RobertoORIGINALMachine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands.pdfMachine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands.pdfArtículo científicoapplication/pdf4314113http://repositorio.conacyt.gov.py/bitstream/20.500.14066/4473/1/Machine%20learning%20for%20ranking%20multivariate%20variables%20in%20cattle%20breeds%20raised%20in%20Paraguayan%20wetlands.pdfb7759d516ae0a04c4b88ad7febba83b5MD51THUMBNAILMachine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands.jpgMachine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands.jpgArtículo científicoimage/jpeg233179http://repositorio.conacyt.gov.py/bitstream/20.500.14066/4473/4/Machine%20learning%20for%20ranking%20multivariate%20variables%20in%20cattle%20breeds%20raised%20in%20Paraguayan%20wetlands.jpga77c15701c96f8a6a55d0eb4b84443faMD54CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8908http://repositorio.conacyt.gov.py/bitstream/20.500.14066/4473/2/license_rdf0175ea4a2d4caec4bbcc37e300941108MD52LICENSElicense.txtlicense.txttext/plain; charset=utf-81698http://repositorio.conacyt.gov.py/bitstream/20.500.14066/4473/3/license.txt858b22fda432bd774e469302988c1974MD53TEXTMachine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands.pdf.txtMachine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands.pdf.txtExtracted texttext/plain39128http://repositorio.conacyt.gov.py/bitstream/20.500.14066/4473/5/Machine%20learning%20for%20ranking%20multivariate%20variables%20in%20cattle%20breeds%20raised%20in%20Paraguayan%20wetlands.pdf.txte49a92c22ad6d9d7cd7243e77cbf29a9MD5520.500.14066/4473oai:repositorio.conacyt.gov.py:20.500.14066/44732026-02-12 19:30:38.495Repositorio Institucional CONACYTrepositorio.institucional@conacyt.gov.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 |
| spellingShingle | Machine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands Pereira, Walter Esfrain Blood variables Cattle adaptability in wetlands Phenotypic variables SHAP Variáveis sanguíneas Adaptabilidade bovina em pântanos Variáveis fenotípicas SHAP |
| status_str | publishedVersion |
| title | Machine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands |
| title_full | Machine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands |
| title_fullStr | Machine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands |
| title_full_unstemmed | Machine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands |
| title_short | Machine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands |
| title_sort | Machine learning for ranking multivariate variables in cattle breeds raised in Paraguayan wetlands |
| topic | Blood variables Cattle adaptability in wetlands Phenotypic variables SHAP Variáveis sanguíneas Adaptabilidade bovina em pântanos Variáveis fenotípicas SHAP |
| url | http://dx.doi.org/10.1590/1807-1929/agriambi.v29n1e283168 http://hdl.handle.net/20.500.14066/4473 |