Loss sampling methods for soybean mechanical harvest
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , |
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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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|| |
_version_ |
1797069065104130048 |