Multivariate analysis of peanut mechanized harvesting

Detalhes bibliográficos
Autor(a) principal: Noronha, Rafael H.F. [UNESP]
Data de Publicação: 2018
Outros Autores: Zerbato, Cristiano [UNESP], da Silva, Rouverson P. [UNESP], Ormond, Antonio T.S. [UNESP], de Oliveira, Mailson F. [UNESP]
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1590/1809-4430-Eng.Agric.v38n2p244-250/2018
http://hdl.handle.net/11449/179897
Resumo: The peanuts harvesting mechanization is affected by the soil physical characteristics and it may increase the losses due to the production of pods in subsurface. The objective of the experiment was to identify the clusters through multivariate exploratory approaches from similarity in six soil textures (very clayey, clayey, silty clayey loam, clayey loam, sandy loam and sandy) in the state of São Paulo, Brazil, determining the main agronomic variables that most influenced the clustering division to assist the decision-making process in peanuts mechanized harvesting. The data were analyzed by the multivariate exploratory that is performed to simplify the description of a set of interrelated variables, using: yield, maturity, soil and pod moisture content, windrow width and height, visible and invisible digging losses, and gathering losses, as agronomic indicators of quality. The low and high clay content were grouped into clusters I and III, respectively, according to the agronomic traits of the peanut crop. The principal components analysis (PC) allowed a single distribution of accesses since only two eigenvalues were higher than one: the highest eigenvalues of 4.51 and 1.79, resulted in a Biplot that explained 70% of the original variability, 50.11% and 19.89% of which in the PC1 and PC2, respectively. The multivariate analysis indicated that high peanut yields in soils with low clay are correlated with the losses during the peanut mechanized harvesting operation.
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spelling Multivariate analysis of peanut mechanized harvestingArachis hypogaea L.Principal components analysisSoil textural classesThe peanuts harvesting mechanization is affected by the soil physical characteristics and it may increase the losses due to the production of pods in subsurface. The objective of the experiment was to identify the clusters through multivariate exploratory approaches from similarity in six soil textures (very clayey, clayey, silty clayey loam, clayey loam, sandy loam and sandy) in the state of São Paulo, Brazil, determining the main agronomic variables that most influenced the clustering division to assist the decision-making process in peanuts mechanized harvesting. The data were analyzed by the multivariate exploratory that is performed to simplify the description of a set of interrelated variables, using: yield, maturity, soil and pod moisture content, windrow width and height, visible and invisible digging losses, and gathering losses, as agronomic indicators of quality. The low and high clay content were grouped into clusters I and III, respectively, according to the agronomic traits of the peanut crop. The principal components analysis (PC) allowed a single distribution of accesses since only two eigenvalues were higher than one: the highest eigenvalues of 4.51 and 1.79, resulted in a Biplot that explained 70% of the original variability, 50.11% and 19.89% of which in the PC1 and PC2, respectively. The multivariate analysis indicated that high peanut yields in soils with low clay are correlated with the losses during the peanut mechanized harvesting operation.São Paulo State University - UNESPSão Paulo State University - UNESPUniversidade Estadual Paulista (Unesp)Noronha, Rafael H.F. [UNESP]Zerbato, Cristiano [UNESP]da Silva, Rouverson P. [UNESP]Ormond, Antonio T.S. [UNESP]de Oliveira, Mailson F. [UNESP]2018-12-11T17:37:12Z2018-12-11T17:37:12Z2018-03-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article244-250application/pdfhttp://dx.doi.org/10.1590/1809-4430-Eng.Agric.v38n2p244-250/2018Engenharia Agricola, v. 38, n. 2, p. 244-250, 2018.1808-43890100-6916http://hdl.handle.net/11449/17989710.1590/1809-4430-Eng.Agric.v38n2p244-250/2018S0100-691620180002002442-s2.0-85047614963S0100-69162018000200244.pdfScopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengEngenharia Agricola0,305info:eu-repo/semantics/openAccess2024-06-06T15:18:44Zoai:repositorio.unesp.br:11449/179897Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-06-06T15:18:44Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Multivariate analysis of peanut mechanized harvesting
title Multivariate analysis of peanut mechanized harvesting
spellingShingle Multivariate analysis of peanut mechanized harvesting
Noronha, Rafael H.F. [UNESP]
Arachis hypogaea L.
Principal components analysis
Soil textural classes
title_short Multivariate analysis of peanut mechanized harvesting
title_full Multivariate analysis of peanut mechanized harvesting
title_fullStr Multivariate analysis of peanut mechanized harvesting
title_full_unstemmed Multivariate analysis of peanut mechanized harvesting
title_sort Multivariate analysis of peanut mechanized harvesting
author Noronha, Rafael H.F. [UNESP]
author_facet Noronha, Rafael H.F. [UNESP]
Zerbato, Cristiano [UNESP]
da Silva, Rouverson P. [UNESP]
Ormond, Antonio T.S. [UNESP]
de Oliveira, Mailson F. [UNESP]
author_role author
author2 Zerbato, Cristiano [UNESP]
da Silva, Rouverson P. [UNESP]
Ormond, Antonio T.S. [UNESP]
de Oliveira, Mailson F. [UNESP]
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv Noronha, Rafael H.F. [UNESP]
Zerbato, Cristiano [UNESP]
da Silva, Rouverson P. [UNESP]
Ormond, Antonio T.S. [UNESP]
de Oliveira, Mailson F. [UNESP]
dc.subject.por.fl_str_mv Arachis hypogaea L.
Principal components analysis
Soil textural classes
topic Arachis hypogaea L.
Principal components analysis
Soil textural classes
description The peanuts harvesting mechanization is affected by the soil physical characteristics and it may increase the losses due to the production of pods in subsurface. The objective of the experiment was to identify the clusters through multivariate exploratory approaches from similarity in six soil textures (very clayey, clayey, silty clayey loam, clayey loam, sandy loam and sandy) in the state of São Paulo, Brazil, determining the main agronomic variables that most influenced the clustering division to assist the decision-making process in peanuts mechanized harvesting. The data were analyzed by the multivariate exploratory that is performed to simplify the description of a set of interrelated variables, using: yield, maturity, soil and pod moisture content, windrow width and height, visible and invisible digging losses, and gathering losses, as agronomic indicators of quality. The low and high clay content were grouped into clusters I and III, respectively, according to the agronomic traits of the peanut crop. The principal components analysis (PC) allowed a single distribution of accesses since only two eigenvalues were higher than one: the highest eigenvalues of 4.51 and 1.79, resulted in a Biplot that explained 70% of the original variability, 50.11% and 19.89% of which in the PC1 and PC2, respectively. The multivariate analysis indicated that high peanut yields in soils with low clay are correlated with the losses during the peanut mechanized harvesting operation.
publishDate 2018
dc.date.none.fl_str_mv 2018-12-11T17:37:12Z
2018-12-11T17:37:12Z
2018-03-01
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://dx.doi.org/10.1590/1809-4430-Eng.Agric.v38n2p244-250/2018
Engenharia Agricola, v. 38, n. 2, p. 244-250, 2018.
1808-4389
0100-6916
http://hdl.handle.net/11449/179897
10.1590/1809-4430-Eng.Agric.v38n2p244-250/2018
S0100-69162018000200244
2-s2.0-85047614963
S0100-69162018000200244.pdf
url http://dx.doi.org/10.1590/1809-4430-Eng.Agric.v38n2p244-250/2018
http://hdl.handle.net/11449/179897
identifier_str_mv Engenharia Agricola, v. 38, n. 2, p. 244-250, 2018.
1808-4389
0100-6916
10.1590/1809-4430-Eng.Agric.v38n2p244-250/2018
S0100-69162018000200244
2-s2.0-85047614963
S0100-69162018000200244.pdf
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Engenharia Agricola
0,305
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 244-250
application/pdf
dc.source.none.fl_str_mv Scopus
reponame:Repositório Institucional da UNESP
instname:Universidade Estadual Paulista (UNESP)
instacron:UNESP
instname_str Universidade Estadual Paulista (UNESP)
instacron_str UNESP
institution UNESP
reponame_str Repositório Institucional da UNESP
collection Repositório Institucional da UNESP
repository.name.fl_str_mv Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)
repository.mail.fl_str_mv
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