Loss sampling methods for soybean mechanical harvest

Detalhes bibliográficos
Autor(a) principal: Strini Paixão, Carla Segatto
Data de Publicação: 2022
Outros Autores: Voltarelli, Murilo Aparecido, Costa Souza, Jarlyson Brunno, de Brito Filho, Armando Lopes, Silva, Rouverson Pereira da
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Bioscience journal (Online)
Texto Completo: https://seer.ufu.br/index.php/biosciencejournal/article/view/56409
Resumo: Harvesting is one of the most important stages of the agricultural production process. However, the lack of monitoring during this operation and the absence of efficient methodologies to quantify losses have contributed to the decline in the quality of the operation. The objective of this study was to monitor mechanized soybean harvest by quantifying losses through two methodologies using statistical process control. The study was conducted in March 2016 in an agricultural area in the municipality of Ribeirão Preto, SP, using a John Deere harvester model 1470 with a tangential-type track system and separation by a straw-blower. The experimental design followed the standards established by statistical process control, and every 8 min of harvest, the total losses by the circular framework and rectangular framework methodologies were simultaneously quantified, totaling 40 points. Data were analyzed using descriptive statistics and statistical process control. The averages of the circular methodology framework were values above those found in the rectangular methodology framework, presenting greater representativeness of losses. The process was considered unable to maintain losses of soybeans at acceptable levels during mechanical harvest throughout the operation of the two frameworks. The circular framework for collecting samples at different locations resulted in higher reliability of data.
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spelling Loss sampling methods for soybean mechanical harvestControl ChartsGrain HarvesterGlycine max L. Loss MethodologyStatistical Process Control. Agricultural SciencesHarvesting is one of the most important stages of the agricultural production process. However, the lack of monitoring during this operation and the absence of efficient methodologies to quantify losses have contributed to the decline in the quality of the operation. The objective of this study was to monitor mechanized soybean harvest by quantifying losses through two methodologies using statistical process control. The study was conducted in March 2016 in an agricultural area in the municipality of Ribeirão Preto, SP, using a John Deere harvester model 1470 with a tangential-type track system and separation by a straw-blower. The experimental design followed the standards established by statistical process control, and every 8 min of harvest, the total losses by the circular framework and rectangular framework methodologies were simultaneously quantified, totaling 40 points. Data were analyzed using descriptive statistics and statistical process control. The averages of the circular methodology framework were values above those found in the rectangular methodology framework, presenting greater representativeness of losses. The process was considered unable to maintain losses of soybeans at acceptable levels during mechanical harvest throughout the operation of the two frameworks. The circular framework for collecting samples at different locations resulted in higher reliability of data.A colheita é a última etapa do processo de produção, mas a falta de monitoramento dessa operação, juntamente com a ausência de metodologias eficientes para quantificar perdas, contribuiu para o declínio na qualidade da operação. O objetivo deste estudo foi monitorar a colheita mecanizada de soja, quantificando perdas através de duas metodologias, pelo controle estatístico do processo. O estudo foi realizado em março de 2016, em uma área agrícola no município de Ribeirão Preto - SP, utilizando uma colheitadeira John Deere modelo 1470 com sistema de esteira do tipo tangencial e separação por soprador de palha. O delineamento experimental seguiu os padrões estabelecidos pelo controle estatístico do processo e, a cada oito minutos de colheita, quantificaram-se simultaneamente as perdas totais pelas metodologias de estrutura circular e estrutura retangular, totalizando 40 pontos. Os dados foram analisados ​​por meio de estatística descritiva e controle estatístico do processo. A média do referencial metodológico circular apresenta valores acima dos encontrados no referencial retangular, apresentando maior representatividade das perdas. O processo foi considerado incapaz de manter as perdas da colheita mecânica da soja em níveis aceitáveis ​​ao longo da operação para as duas estruturas. A estrutura circular para coletar amostras em diferentes locais resulta em maior confiabilidade dos dados.Universidade Federal de Uberlândia2022-08-12info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://seer.ufu.br/index.php/biosciencejournal/article/view/5640910.14393/BJ-v38n0a2022-56409Bioscience Journal ; Vol. 38 (2022): Continuous Publication; e38050Bioscience Journal ; v. 38 (2022): Continuous Publication; e380501981-3163reponame:Bioscience journal (Online)instname:Universidade Federal de Uberlândia (UFU)instacron:UFUenghttps://seer.ufu.br/index.php/biosciencejournal/article/view/56409/34442Brazil; Contemporary Copyright (c) 2022 Carla Segatto Strini Paixão, Murillo Aperecido Voltarelli, Jarlyson Brunno Costa Souza, Armando Lopes de Brito Filho, Rouverson Pereira da Silvahttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessStrini Paixão, Carla Segatto Voltarelli, Murilo AparecidoCosta Souza, Jarlyson Brunnode Brito Filho, Armando LopesSilva, Rouverson Pereira da2023-12-16T21:23:37Zoai:ojs.www.seer.ufu.br:article/56409Revistahttps://seer.ufu.br/index.php/biosciencejournalPUBhttps://seer.ufu.br/index.php/biosciencejournal/oaibiosciencej@ufu.br||1981-31631516-3725opendoar:2023-12-16T21:23:37Bioscience journal (Online) - Universidade Federal de Uberlândia (UFU)false
dc.title.none.fl_str_mv Loss sampling methods for soybean mechanical harvest
title Loss sampling methods for soybean mechanical harvest
spellingShingle Loss sampling methods for soybean mechanical harvest
Strini Paixão, Carla Segatto
Control Charts
Grain Harvester
Glycine max L.
Loss Methodology
Statistical Process Control.
Agricultural Sciences
title_short Loss sampling methods for soybean mechanical harvest
title_full Loss sampling methods for soybean mechanical harvest
title_fullStr Loss sampling methods for soybean mechanical harvest
title_full_unstemmed Loss sampling methods for soybean mechanical harvest
title_sort Loss sampling methods for soybean mechanical harvest
author Strini Paixão, Carla Segatto
author_facet Strini Paixão, Carla Segatto
Voltarelli, Murilo Aparecido
Costa Souza, Jarlyson Brunno
de Brito Filho, Armando Lopes
Silva, Rouverson Pereira da
author_role author
author2 Voltarelli, Murilo Aparecido
Costa Souza, Jarlyson Brunno
de Brito Filho, Armando Lopes
Silva, Rouverson Pereira da
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Strini Paixão, Carla Segatto
Voltarelli, Murilo Aparecido
Costa Souza, Jarlyson Brunno
de Brito Filho, Armando Lopes
Silva, Rouverson Pereira da
dc.subject.por.fl_str_mv Control Charts
Grain Harvester
Glycine max L.
Loss Methodology
Statistical Process Control.
Agricultural Sciences
topic Control Charts
Grain Harvester
Glycine max L.
Loss Methodology
Statistical Process Control.
Agricultural Sciences
description Harvesting is one of the most important stages of the agricultural production process. However, the lack of monitoring during this operation and the absence of efficient methodologies to quantify losses have contributed to the decline in the quality of the operation. The objective of this study was to monitor mechanized soybean harvest by quantifying losses through two methodologies using statistical process control. The study was conducted in March 2016 in an agricultural area in the municipality of Ribeirão Preto, SP, using a John Deere harvester model 1470 with a tangential-type track system and separation by a straw-blower. The experimental design followed the standards established by statistical process control, and every 8 min of harvest, the total losses by the circular framework and rectangular framework methodologies were simultaneously quantified, totaling 40 points. Data were analyzed using descriptive statistics and statistical process control. The averages of the circular methodology framework were values above those found in the rectangular methodology framework, presenting greater representativeness of losses. The process was considered unable to maintain losses of soybeans at acceptable levels during mechanical harvest throughout the operation of the two frameworks. The circular framework for collecting samples at different locations resulted in higher reliability of data.
publishDate 2022
dc.date.none.fl_str_mv 2022-08-12
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://seer.ufu.br/index.php/biosciencejournal/article/view/56409
10.14393/BJ-v38n0a2022-56409
url https://seer.ufu.br/index.php/biosciencejournal/article/view/56409
identifier_str_mv 10.14393/BJ-v38n0a2022-56409
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://seer.ufu.br/index.php/biosciencejournal/article/view/56409/34442
dc.rights.driver.fl_str_mv https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.coverage.none.fl_str_mv Brazil; Contemporary
dc.publisher.none.fl_str_mv Universidade Federal de Uberlândia
publisher.none.fl_str_mv Universidade Federal de Uberlândia
dc.source.none.fl_str_mv Bioscience Journal ; Vol. 38 (2022): Continuous Publication; e38050
Bioscience Journal ; v. 38 (2022): Continuous Publication; e38050
1981-3163
reponame:Bioscience journal (Online)
instname:Universidade Federal de Uberlândia (UFU)
instacron:UFU
instname_str Universidade Federal de Uberlândia (UFU)
instacron_str UFU
institution UFU
reponame_str Bioscience journal (Online)
collection Bioscience journal (Online)
repository.name.fl_str_mv Bioscience journal (Online) - Universidade Federal de Uberlândia (UFU)
repository.mail.fl_str_mv biosciencej@ufu.br||
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