Chemical attributes of corn under the path analysis in an Amazon ecosystemic domain

Detalhes bibliográficos
Autor(a) principal: Pinheiro, Luana da Silva
Data de Publicação: 2024
Outros Autores: Vieira, Mateus Monteles, Nunes, Gabriel Gustavo Tavares, Silva, Claudete Rosa da, Oliveira, Job Teixeira, Castro, Tulio Russino, Roque, Cassiano Garcia, Silva, Priscilla Andrade
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Engenharia na Agricultura
Texto Completo: https://periodicos.ufv.br/reveng/article/view/16811
Resumo: The present study aims to expose information about the dynamics between the chemical attributes of corn and the direct and indirect influence of these attributes on the proteins of the grain. The attributes analyzed were grain mass, total soluble solids, pH, total titratable acidity, ashes, moisture content, lipids, proteins, and carbohydrates. A network of correlations was obtained and descriptive statistical results of the attributes were generated. Through a path analysis, in which protein content was the main variable, the direct and indirect correlation between the attributes was determined. The moisture level and ash content obtained for the corn were similar to those found in literature. The levels of protein, lipids, and carbohydrates were lower than those established in the Brazilian Table of Food Composition. It was concluded that lipids were the attributes that best determine corn proteins.
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spelling Chemical attributes of corn under the path analysis in an Amazon ecosystemic domainChemical attributes of corn under the path analysis in an Amazon ecosystemic domainagroecologybiotechnologyprecision agricultureproductivityZea mays L.AgroecologyBiotechnologyPrecision AgricultureMulticollinearityThe present study aims to expose information about the dynamics between the chemical attributes of corn and the direct and indirect influence of these attributes on the proteins of the grain. The attributes analyzed were grain mass, total soluble solids, pH, total titratable acidity, ashes, moisture content, lipids, proteins, and carbohydrates. A network of correlations was obtained and descriptive statistical results of the attributes were generated. Through a path analysis, in which protein content was the main variable, the direct and indirect correlation between the attributes was determined. The moisture level and ash content obtained for the corn were similar to those found in literature. The levels of protein, lipids, and carbohydrates were lower than those established in the Brazilian Table of Food Composition. It was concluded that lipids were the attributes that best determine corn proteins.The present study aims to expose information about the dynamics between the chemical attributes of corn and the direct and indirect influence of these attributes on the proteins of the grain. The attributes analyzed were grain mass, total soluble solids, pH, total titratable acidity, ashes, moisture content, lipids, proteins, and carbohydrates. A network of correlations was obtained and descriptive statistical results of the attributes were generated. Through a path analysis, in which protein content was the main variable, the direct and indirect correlation between the attributes was determined. The moisture level and ash content obtained for the corn were similar to those found in literature. The levels of protein, lipids, and carbohydrates were lower than those established in the Brazilian Table of Food Composition. It was concluded that lipids were the attributes that best determine corn proteins.Universidade Federal de Viçosa - UFV2024-08-23info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://periodicos.ufv.br/reveng/article/view/1681110.13083/reveng.v32i1.16811Engineering in Agriculture; Vol. 32 No. Contínua (2024); 37-46Revista Engenharia na Agricultura - REVENG; v. 32 n. Contínua (2024); 37-462175-68131414-3984reponame:Engenharia na Agriculturainstname:Universidade Federal de Viçosa (UFV)instacron:UFVenghttps://periodicos.ufv.br/reveng/article/view/16811/9922Copyright (c) 2024 Revista Engenharia na Agricultura - REVENGhttps://creativecommons.org/licenses/by-nc/4.0info:eu-repo/semantics/openAccessPinheiro, Luana da SilvaVieira, Mateus MontelesNunes, Gabriel Gustavo TavaresSilva, Claudete Rosa daOliveira, Job TeixeiraCastro, Tulio RussinoRoque, Cassiano GarciaSilva, Priscilla Andrade2024-08-23T17:28:56Zoai:ojs.periodicos.ufv.br:article/16811Revistahttps://periodicos.ufv.br/revengPUBhttps://periodicos.ufv.br/reveng/oairevistaengenharianagricultura@gmail.com||andrerosa@ufv.br||tramitacao.reveng@gmail.com|| reveng@ufv.br2175-68131414-3984opendoar:2024-08-23T17:28:56Engenharia na Agricultura - Universidade Federal de Viçosa (UFV)false
dc.title.none.fl_str_mv Chemical attributes of corn under the path analysis in an Amazon ecosystemic domain
Chemical attributes of corn under the path analysis in an Amazon ecosystemic domain
title Chemical attributes of corn under the path analysis in an Amazon ecosystemic domain
spellingShingle Chemical attributes of corn under the path analysis in an Amazon ecosystemic domain
Pinheiro, Luana da Silva
agroecology
biotechnology
precision agriculture
productivity
Zea mays L.
Agroecology
Biotechnology
Precision Agriculture
Multicollinearity
title_short Chemical attributes of corn under the path analysis in an Amazon ecosystemic domain
title_full Chemical attributes of corn under the path analysis in an Amazon ecosystemic domain
title_fullStr Chemical attributes of corn under the path analysis in an Amazon ecosystemic domain
title_full_unstemmed Chemical attributes of corn under the path analysis in an Amazon ecosystemic domain
title_sort Chemical attributes of corn under the path analysis in an Amazon ecosystemic domain
author Pinheiro, Luana da Silva
author_facet Pinheiro, Luana da Silva
Vieira, Mateus Monteles
Nunes, Gabriel Gustavo Tavares
Silva, Claudete Rosa da
Oliveira, Job Teixeira
Castro, Tulio Russino
Roque, Cassiano Garcia
Silva, Priscilla Andrade
author_role author
author2 Vieira, Mateus Monteles
Nunes, Gabriel Gustavo Tavares
Silva, Claudete Rosa da
Oliveira, Job Teixeira
Castro, Tulio Russino
Roque, Cassiano Garcia
Silva, Priscilla Andrade
author2_role author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Pinheiro, Luana da Silva
Vieira, Mateus Monteles
Nunes, Gabriel Gustavo Tavares
Silva, Claudete Rosa da
Oliveira, Job Teixeira
Castro, Tulio Russino
Roque, Cassiano Garcia
Silva, Priscilla Andrade
dc.subject.por.fl_str_mv agroecology
biotechnology
precision agriculture
productivity
Zea mays L.
Agroecology
Biotechnology
Precision Agriculture
Multicollinearity
topic agroecology
biotechnology
precision agriculture
productivity
Zea mays L.
Agroecology
Biotechnology
Precision Agriculture
Multicollinearity
description The present study aims to expose information about the dynamics between the chemical attributes of corn and the direct and indirect influence of these attributes on the proteins of the grain. The attributes analyzed were grain mass, total soluble solids, pH, total titratable acidity, ashes, moisture content, lipids, proteins, and carbohydrates. A network of correlations was obtained and descriptive statistical results of the attributes were generated. Through a path analysis, in which protein content was the main variable, the direct and indirect correlation between the attributes was determined. The moisture level and ash content obtained for the corn were similar to those found in literature. The levels of protein, lipids, and carbohydrates were lower than those established in the Brazilian Table of Food Composition. It was concluded that lipids were the attributes that best determine corn proteins.
publishDate 2024
dc.date.none.fl_str_mv 2024-08-23
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://periodicos.ufv.br/reveng/article/view/16811
10.13083/reveng.v32i1.16811
url https://periodicos.ufv.br/reveng/article/view/16811
identifier_str_mv 10.13083/reveng.v32i1.16811
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://periodicos.ufv.br/reveng/article/view/16811/9922
dc.rights.driver.fl_str_mv Copyright (c) 2024 Revista Engenharia na Agricultura - REVENG
https://creativecommons.org/licenses/by-nc/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2024 Revista Engenharia na Agricultura - REVENG
https://creativecommons.org/licenses/by-nc/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Viçosa - UFV
publisher.none.fl_str_mv Universidade Federal de Viçosa - UFV
dc.source.none.fl_str_mv Engineering in Agriculture; Vol. 32 No. Contínua (2024); 37-46
Revista Engenharia na Agricultura - REVENG; v. 32 n. Contínua (2024); 37-46
2175-6813
1414-3984
reponame:Engenharia na Agricultura
instname:Universidade Federal de Viçosa (UFV)
instacron:UFV
instname_str Universidade Federal de Viçosa (UFV)
instacron_str UFV
institution UFV
reponame_str Engenharia na Agricultura
collection Engenharia na Agricultura
repository.name.fl_str_mv Engenharia na Agricultura - Universidade Federal de Viçosa (UFV)
repository.mail.fl_str_mv revistaengenharianagricultura@gmail.com||andrerosa@ufv.br||tramitacao.reveng@gmail.com|| reveng@ufv.br
_version_ 1818372027320369152

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