Technical and economic viability of manual harvesting
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFLA |
Texto Completo: | http://repositorio.ufla.br/jspui/handle/1/46813 |
Resumo: | Precision coffee growing is a concept that implies the use of precision agriculture techniques in coffee plantations. For the coffee growing, the precision electronic resources coupled to the harvesters are very scarce. Thereby, the harvest of coffee plantations that compose the grid sampling for generation of thematic maps can be performed manually. The aim of the present study was to generate a linear regression model to estimate the time required to harvest, estimate the labor costs to harvest manually the georeferenced sample points for generation of coffee yield maps. The study was performed in a coffee area of 56 hectares using two sampling points per hectare, totaling 112 points, being evaluated four coffee plants for each point. The manual harvest of the points was performed by four rural workers with experience in the coffee harvest. Afterwards, the collected volume was measured by a graduated container and the times were obtained by the digital stopwatch. Based on the data obtained in the field, a linear correlation model was established between the harvest time of each sampling point and the yield of the point, whose R² value was 78.27, cost was R$ 8.92 per point. These results are relevant for estimating the amount of labor force required to generate manually harvest yield maps according to the producer’s coffee yield estimate, contributing to the closure of the precision coffee growing cycle. |
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Technical and economic viability of manual harvestingPrecision agricultureCrop mappingField efficiencyCostsColheita manual - ViabilidadeColheita manual - CustosAgricultura de precisãoCultivo - MapeamentoEficiência de campoPrecision coffee growing is a concept that implies the use of precision agriculture techniques in coffee plantations. For the coffee growing, the precision electronic resources coupled to the harvesters are very scarce. Thereby, the harvest of coffee plantations that compose the grid sampling for generation of thematic maps can be performed manually. The aim of the present study was to generate a linear regression model to estimate the time required to harvest, estimate the labor costs to harvest manually the georeferenced sample points for generation of coffee yield maps. The study was performed in a coffee area of 56 hectares using two sampling points per hectare, totaling 112 points, being evaluated four coffee plants for each point. The manual harvest of the points was performed by four rural workers with experience in the coffee harvest. Afterwards, the collected volume was measured by a graduated container and the times were obtained by the digital stopwatch. Based on the data obtained in the field, a linear correlation model was established between the harvest time of each sampling point and the yield of the point, whose R² value was 78.27, cost was R$ 8.92 per point. These results are relevant for estimating the amount of labor force required to generate manually harvest yield maps according to the producer’s coffee yield estimate, contributing to the closure of the precision coffee growing cycle.Universidade Federal de Lavras2021-07-23T18:42:38Z2021-07-23T18:42:38Z2020-07info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfFARIA, R. de O. et al. Technical and economic viability of manual harvesting coffee yield maps. Coffee Science, Lavras, v. 15, e151674, 2020. DOI: 10.25186/.v15i.1674.http://repositorio.ufla.br/jspui/handle/1/46813Coffee Sciencereponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLAhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessFaria, Rafael de OliveiraSilva, Fábio Moreira daFerraz, Gabriel Araújo e SilvaHerrera, Miguel Angel DiazBarbosa, Brenon Diennevan SouzaAlonso, Diego José CarvalhoSoares, Daniel Veigaeng2021-07-23T18:43:22Zoai:localhost:1/46813Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2021-07-23T18:43:22Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false |
dc.title.none.fl_str_mv |
Technical and economic viability of manual harvesting |
title |
Technical and economic viability of manual harvesting |
spellingShingle |
Technical and economic viability of manual harvesting Faria, Rafael de Oliveira Precision agriculture Crop mapping Field efficiency Costs Colheita manual - Viabilidade Colheita manual - Custos Agricultura de precisão Cultivo - Mapeamento Eficiência de campo |
title_short |
Technical and economic viability of manual harvesting |
title_full |
Technical and economic viability of manual harvesting |
title_fullStr |
Technical and economic viability of manual harvesting |
title_full_unstemmed |
Technical and economic viability of manual harvesting |
title_sort |
Technical and economic viability of manual harvesting |
author |
Faria, Rafael de Oliveira |
author_facet |
Faria, Rafael de Oliveira Silva, Fábio Moreira da Ferraz, Gabriel Araújo e Silva Herrera, Miguel Angel Diaz Barbosa, Brenon Diennevan Souza Alonso, Diego José Carvalho Soares, Daniel Veiga |
author_role |
author |
author2 |
Silva, Fábio Moreira da Ferraz, Gabriel Araújo e Silva Herrera, Miguel Angel Diaz Barbosa, Brenon Diennevan Souza Alonso, Diego José Carvalho Soares, Daniel Veiga |
author2_role |
author author author author author author |
dc.contributor.author.fl_str_mv |
Faria, Rafael de Oliveira Silva, Fábio Moreira da Ferraz, Gabriel Araújo e Silva Herrera, Miguel Angel Diaz Barbosa, Brenon Diennevan Souza Alonso, Diego José Carvalho Soares, Daniel Veiga |
dc.subject.por.fl_str_mv |
Precision agriculture Crop mapping Field efficiency Costs Colheita manual - Viabilidade Colheita manual - Custos Agricultura de precisão Cultivo - Mapeamento Eficiência de campo |
topic |
Precision agriculture Crop mapping Field efficiency Costs Colheita manual - Viabilidade Colheita manual - Custos Agricultura de precisão Cultivo - Mapeamento Eficiência de campo |
description |
Precision coffee growing is a concept that implies the use of precision agriculture techniques in coffee plantations. For the coffee growing, the precision electronic resources coupled to the harvesters are very scarce. Thereby, the harvest of coffee plantations that compose the grid sampling for generation of thematic maps can be performed manually. The aim of the present study was to generate a linear regression model to estimate the time required to harvest, estimate the labor costs to harvest manually the georeferenced sample points for generation of coffee yield maps. The study was performed in a coffee area of 56 hectares using two sampling points per hectare, totaling 112 points, being evaluated four coffee plants for each point. The manual harvest of the points was performed by four rural workers with experience in the coffee harvest. Afterwards, the collected volume was measured by a graduated container and the times were obtained by the digital stopwatch. Based on the data obtained in the field, a linear correlation model was established between the harvest time of each sampling point and the yield of the point, whose R² value was 78.27, cost was R$ 8.92 per point. These results are relevant for estimating the amount of labor force required to generate manually harvest yield maps according to the producer’s coffee yield estimate, contributing to the closure of the precision coffee growing cycle. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-07 2021-07-23T18:42:38Z 2021-07-23T18:42:38Z |
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 |
FARIA, R. de O. et al. Technical and economic viability of manual harvesting coffee yield maps. Coffee Science, Lavras, v. 15, e151674, 2020. DOI: 10.25186/.v15i.1674. http://repositorio.ufla.br/jspui/handle/1/46813 |
identifier_str_mv |
FARIA, R. de O. et al. Technical and economic viability of manual harvesting coffee yield maps. Coffee Science, Lavras, v. 15, e151674, 2020. DOI: 10.25186/.v15i.1674. |
url |
http://repositorio.ufla.br/jspui/handle/1/46813 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
http://creativecommons.org/licenses/by/4.0/ info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
http://creativecommons.org/licenses/by/4.0/ |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Lavras |
publisher.none.fl_str_mv |
Universidade Federal de Lavras |
dc.source.none.fl_str_mv |
Coffee Science reponame:Repositório Institucional da UFLA instname:Universidade Federal de Lavras (UFLA) instacron:UFLA |
instname_str |
Universidade Federal de Lavras (UFLA) |
instacron_str |
UFLA |
institution |
UFLA |
reponame_str |
Repositório Institucional da UFLA |
collection |
Repositório Institucional da UFLA |
repository.name.fl_str_mv |
Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA) |
repository.mail.fl_str_mv |
nivaldo@ufla.br || repositorio.biblioteca@ufla.br |
_version_ |
1815439073188249600 |