Sugarcane Harvesting Quality by Digital Image Processing

Detalhes bibliográficos
Autor(a) principal: De Moura Araújo, Guilherme
Data de Publicação: 2020
Outros Autores: dos Santos, Fernando Ferreira Lima, de Almeida, Samira Luns Hatum [UNESP], Martins, Rodrigo Nogueira, Voltarelli, Murilo Aparecido, Paixão, Carla Segatto Strini, de Assis de Carvalho Pinto, Francisco
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1007/s12355-020-00867-2
http://hdl.handle.net/11449/199220
Resumo: Sugarcane, a major crop in the Brazilian agribusiness sector, has had significant changes in its cultivation over the years. The harvest of sugarcane was usually carried out manually. However, due to the great demand for labours and high health hazards, manual harvesting was replaced by a mechanized process. Harvesters have a basal cutting mechanism composed of blades that are responsible for cutting the sugarcane. The blades must be continuously analysed and replaced if necessary. The analysis of these blades is performed qualitatively, in which the operator analyses the current conditions of the blades (based on prior experiences); or quantitatively, using a digital calliper to measure the thickness of the blade, wherein the increase in thickness indicates greater wear. Both approaches require the harvester to be stationary and are extremely time-consuming. In order to obtain more efficient results, the present study proposes a novel method to analyse blade wear and harvesting quality through the use of digital image processing. The change in geometric characteristics (area, perimeter, rectangularity, and length) of the blades over time was evaluated along with blade wear and harvesting quality indices (damage index to stalks). The obtained results indicated that the proposed methodology was effective at assessing the quality of the harvesting operation of sugarcane and the wear in the mechanisms of basal cutting present in sugarcane harvesters. The error in estimating the damage index ranged between 0.030 and 0.033%.
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spelling Sugarcane Harvesting Quality by Digital Image ProcessingAutomationCut qualityGeometric propertiesModellingSugarcane, a major crop in the Brazilian agribusiness sector, has had significant changes in its cultivation over the years. The harvest of sugarcane was usually carried out manually. However, due to the great demand for labours and high health hazards, manual harvesting was replaced by a mechanized process. Harvesters have a basal cutting mechanism composed of blades that are responsible for cutting the sugarcane. The blades must be continuously analysed and replaced if necessary. The analysis of these blades is performed qualitatively, in which the operator analyses the current conditions of the blades (based on prior experiences); or quantitatively, using a digital calliper to measure the thickness of the blade, wherein the increase in thickness indicates greater wear. Both approaches require the harvester to be stationary and are extremely time-consuming. In order to obtain more efficient results, the present study proposes a novel method to analyse blade wear and harvesting quality through the use of digital image processing. The change in geometric characteristics (area, perimeter, rectangularity, and length) of the blades over time was evaluated along with blade wear and harvesting quality indices (damage index to stalks). The obtained results indicated that the proposed methodology was effective at assessing the quality of the harvesting operation of sugarcane and the wear in the mechanisms of basal cutting present in sugarcane harvesters. The error in estimating the damage index ranged between 0.030 and 0.033%.Universidade Federal de Viçosa/UFV, Av. Ph Rolfs, s/nUniversidade Federal de São Carlos/UFSCAR, Rodovia Lauri Simões de Barros, km 12 - SP-189 - AracaçuCentro Universitário FACENSUniversity of California Davis, One Shields AveUniversidade Estadual Paulista “Júlio de Mesquita Filho”/UNESP, Via de Acesso Professor Paulo Donato Castelane Castellane S/N - Vila IndustrialUniversidade Estadual Paulista “Júlio de Mesquita Filho”/UNESP, Via de Acesso Professor Paulo Donato Castelane Castellane S/N - Vila IndustrialUniversidade Federal de Viçosa (UFV)Universidade Federal de São Carlos (UFSCar)Centro Universitário FACENSDavisUniversidade Estadual Paulista (Unesp)De Moura Araújo, Guilhermedos Santos, Fernando Ferreira Limade Almeida, Samira Luns Hatum [UNESP]Martins, Rodrigo NogueiraVoltarelli, Murilo AparecidoPaixão, Carla Segatto Strinide Assis de Carvalho Pinto, Francisco2020-12-12T01:34:00Z2020-12-12T01:34:00Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1007/s12355-020-00867-2Sugar Tech.0974-07400972-1525http://hdl.handle.net/11449/19922010.1007/s12355-020-00867-22-s2.0-85089082177Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengSugar Techinfo:eu-repo/semantics/openAccess2021-10-23T05:01:53Zoai:repositorio.unesp.br:11449/199220Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T13:41:37.470448Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Sugarcane Harvesting Quality by Digital Image Processing
title Sugarcane Harvesting Quality by Digital Image Processing
spellingShingle Sugarcane Harvesting Quality by Digital Image Processing
De Moura Araújo, Guilherme
Automation
Cut quality
Geometric properties
Modelling
title_short Sugarcane Harvesting Quality by Digital Image Processing
title_full Sugarcane Harvesting Quality by Digital Image Processing
title_fullStr Sugarcane Harvesting Quality by Digital Image Processing
title_full_unstemmed Sugarcane Harvesting Quality by Digital Image Processing
title_sort Sugarcane Harvesting Quality by Digital Image Processing
author De Moura Araújo, Guilherme
author_facet De Moura Araújo, Guilherme
dos Santos, Fernando Ferreira Lima
de Almeida, Samira Luns Hatum [UNESP]
Martins, Rodrigo Nogueira
Voltarelli, Murilo Aparecido
Paixão, Carla Segatto Strini
de Assis de Carvalho Pinto, Francisco
author_role author
author2 dos Santos, Fernando Ferreira Lima
de Almeida, Samira Luns Hatum [UNESP]
Martins, Rodrigo Nogueira
Voltarelli, Murilo Aparecido
Paixão, Carla Segatto Strini
de Assis de Carvalho Pinto, Francisco
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Universidade Federal de Viçosa (UFV)
Universidade Federal de São Carlos (UFSCar)
Centro Universitário FACENS
Davis
Universidade Estadual Paulista (Unesp)
dc.contributor.author.fl_str_mv De Moura Araújo, Guilherme
dos Santos, Fernando Ferreira Lima
de Almeida, Samira Luns Hatum [UNESP]
Martins, Rodrigo Nogueira
Voltarelli, Murilo Aparecido
Paixão, Carla Segatto Strini
de Assis de Carvalho Pinto, Francisco
dc.subject.por.fl_str_mv Automation
Cut quality
Geometric properties
Modelling
topic Automation
Cut quality
Geometric properties
Modelling
description Sugarcane, a major crop in the Brazilian agribusiness sector, has had significant changes in its cultivation over the years. The harvest of sugarcane was usually carried out manually. However, due to the great demand for labours and high health hazards, manual harvesting was replaced by a mechanized process. Harvesters have a basal cutting mechanism composed of blades that are responsible for cutting the sugarcane. The blades must be continuously analysed and replaced if necessary. The analysis of these blades is performed qualitatively, in which the operator analyses the current conditions of the blades (based on prior experiences); or quantitatively, using a digital calliper to measure the thickness of the blade, wherein the increase in thickness indicates greater wear. Both approaches require the harvester to be stationary and are extremely time-consuming. In order to obtain more efficient results, the present study proposes a novel method to analyse blade wear and harvesting quality through the use of digital image processing. The change in geometric characteristics (area, perimeter, rectangularity, and length) of the blades over time was evaluated along with blade wear and harvesting quality indices (damage index to stalks). The obtained results indicated that the proposed methodology was effective at assessing the quality of the harvesting operation of sugarcane and the wear in the mechanisms of basal cutting present in sugarcane harvesters. The error in estimating the damage index ranged between 0.030 and 0.033%.
publishDate 2020
dc.date.none.fl_str_mv 2020-12-12T01:34:00Z
2020-12-12T01:34:00Z
2020-01-01
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/10.1007/s12355-020-00867-2
Sugar Tech.
0974-0740
0972-1525
http://hdl.handle.net/11449/199220
10.1007/s12355-020-00867-2
2-s2.0-85089082177
url http://dx.doi.org/10.1007/s12355-020-00867-2
http://hdl.handle.net/11449/199220
identifier_str_mv Sugar Tech.
0974-0740
0972-1525
10.1007/s12355-020-00867-2
2-s2.0-85089082177
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Sugar Tech
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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
_version_ 1808128266886709248