Forecasting of the annual yield of Arabic coffee using water deficiency
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1590/S0100-204X2018001200002 http://hdl.handle.net/11449/186566 |
Resumo: | The objective of this work was to develop agrometeorological models for the forecasting of the annual yields of Arabic coffee (Coffea arabica), using monthly water deficits (DEFs) during the coffee cycle, in important locations in the state of Minas Gerais, Brazil. For the construction of the models, a meteorological data set spanning of 18 years and multiple linear regressions were used. The models were calibrated in high- and low-yield seasons due to the high-biennial yields in Brazil. All calibrated models for high- and low-yield seasons were accurate and significant at 5% probability, with mean absolute percentage errors <= 2.9%. The minimum forecasting period for yield is six months for southern Minas Gerais and Cerrado Mineiro. In high-yield seasons, water deficits affect more the reproductive stage of coffee and, in low-yield seasons, they affect more the vegetative stage of the crop. |
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Forecasting of the annual yield of Arabic coffee using water deficiencyCoffea arabicaagrometeorologyclimateforecastingmodelwater balanceThe objective of this work was to develop agrometeorological models for the forecasting of the annual yields of Arabic coffee (Coffea arabica), using monthly water deficits (DEFs) during the coffee cycle, in important locations in the state of Minas Gerais, Brazil. For the construction of the models, a meteorological data set spanning of 18 years and multiple linear regressions were used. The models were calibrated in high- and low-yield seasons due to the high-biennial yields in Brazil. All calibrated models for high- and low-yield seasons were accurate and significant at 5% probability, with mean absolute percentage errors <= 2.9%. The minimum forecasting period for yield is six months for southern Minas Gerais and Cerrado Mineiro. In high-yield seasons, water deficits affect more the reproductive stage of coffee and, in low-yield seasons, they affect more the vegetative stage of the crop.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Univ Estadual Paulista, Fac Ciencias Agr & Vet, Dept Econ Adm & Educ, Via Acesso Prof Paulo Donato Castellane S-N, BR-14884900 Jaboticabal, SP, BrazilUniv Estadual Paulista, Fac Ciencias Agr & Vet, Dept Econ Adm & Educ, Via Acesso Prof Paulo Donato Castellane S-N, BR-14884900 Jaboticabal, SP, BrazilFAPESP: 2014/05025-4Empresa Brasil Pesq AgropecUniversidade Estadual Paulista (Unesp)Oliveira Aparecido, Lucas Eduardo de [UNESP]Rolim, Glauco de Souza [UNESP]2019-10-05T06:22:24Z2019-10-05T06:22:24Z2018-12-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article1299-1310application/pdfhttp://dx.doi.org/10.1590/S0100-204X2018001200002Pesquisa Agropecuaria Brasileira. Brasilia Df: Empresa Brasil Pesq Agropec, v. 53, n. 12, p. 1299-1310, 2018.0100-204Xhttp://hdl.handle.net/11449/18656610.1590/S0100-204X2018001200002S0100-204X2018001201299WOS:000455011400002S0100-204X2018001201299.pdfWeb of Sciencereponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengPesquisa Agropecuaria Brasileirainfo:eu-repo/semantics/openAccess2024-06-06T13:43:58Zoai:repositorio.unesp.br:11449/186566Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T22:30:24.859387Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Forecasting of the annual yield of Arabic coffee using water deficiency |
title |
Forecasting of the annual yield of Arabic coffee using water deficiency |
spellingShingle |
Forecasting of the annual yield of Arabic coffee using water deficiency Oliveira Aparecido, Lucas Eduardo de [UNESP] Coffea arabica agrometeorology climate forecasting model water balance |
title_short |
Forecasting of the annual yield of Arabic coffee using water deficiency |
title_full |
Forecasting of the annual yield of Arabic coffee using water deficiency |
title_fullStr |
Forecasting of the annual yield of Arabic coffee using water deficiency |
title_full_unstemmed |
Forecasting of the annual yield of Arabic coffee using water deficiency |
title_sort |
Forecasting of the annual yield of Arabic coffee using water deficiency |
author |
Oliveira Aparecido, Lucas Eduardo de [UNESP] |
author_facet |
Oliveira Aparecido, Lucas Eduardo de [UNESP] Rolim, Glauco de Souza [UNESP] |
author_role |
author |
author2 |
Rolim, Glauco de Souza [UNESP] |
author2_role |
author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
Oliveira Aparecido, Lucas Eduardo de [UNESP] Rolim, Glauco de Souza [UNESP] |
dc.subject.por.fl_str_mv |
Coffea arabica agrometeorology climate forecasting model water balance |
topic |
Coffea arabica agrometeorology climate forecasting model water balance |
description |
The objective of this work was to develop agrometeorological models for the forecasting of the annual yields of Arabic coffee (Coffea arabica), using monthly water deficits (DEFs) during the coffee cycle, in important locations in the state of Minas Gerais, Brazil. For the construction of the models, a meteorological data set spanning of 18 years and multiple linear regressions were used. The models were calibrated in high- and low-yield seasons due to the high-biennial yields in Brazil. All calibrated models for high- and low-yield seasons were accurate and significant at 5% probability, with mean absolute percentage errors <= 2.9%. The minimum forecasting period for yield is six months for southern Minas Gerais and Cerrado Mineiro. In high-yield seasons, water deficits affect more the reproductive stage of coffee and, in low-yield seasons, they affect more the vegetative stage of the crop. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-12-01 2019-10-05T06:22:24Z 2019-10-05T06:22:24Z |
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/S0100-204X2018001200002 Pesquisa Agropecuaria Brasileira. Brasilia Df: Empresa Brasil Pesq Agropec, v. 53, n. 12, p. 1299-1310, 2018. 0100-204X http://hdl.handle.net/11449/186566 10.1590/S0100-204X2018001200002 S0100-204X2018001201299 WOS:000455011400002 S0100-204X2018001201299.pdf |
url |
http://dx.doi.org/10.1590/S0100-204X2018001200002 http://hdl.handle.net/11449/186566 |
identifier_str_mv |
Pesquisa Agropecuaria Brasileira. Brasilia Df: Empresa Brasil Pesq Agropec, v. 53, n. 12, p. 1299-1310, 2018. 0100-204X 10.1590/S0100-204X2018001200002 S0100-204X2018001201299 WOS:000455011400002 S0100-204X2018001201299.pdf |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Pesquisa Agropecuaria Brasileira |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
1299-1310 application/pdf |
dc.publisher.none.fl_str_mv |
Empresa Brasil Pesq Agropec |
publisher.none.fl_str_mv |
Empresa Brasil Pesq Agropec |
dc.source.none.fl_str_mv |
Web of Science 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_ |
1808129433511395328 |