Can nonlinear agrometeorological models estimate coffee foliation?

Detalhes bibliográficos
Autor(a) principal: de Oliveira Aparecido, Lucas Eduardo
Data de Publicação: 2022
Outros Autores: Lorençone, João A, Lorençone, Pedro A, de Souza Rolim, Glauco [UNESP], de Meneses, Kamila C [UNESP], da Silva Cabral de Moraes, José R [UNESP], Torsoni, Guilherme B
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UNESP
Texto Completo: http://dx.doi.org/10.1002/jsfa.11387
http://hdl.handle.net/11449/229084
Resumo: BACKGROUND: The loss of coffee leaves caused by the attack of pests and diseases significantly reduces its production and bean quality. Thus this study aimed to estimate foliation for regions with the highest production of arabica coffee in Brazil using nonlinear models as a function of climate. A 25-year historical series (1995–2019) of Coffea arabica foliation (%) data was obtained by the Procafé Foundation in cultivations with no phytosanitary treatment. The climate data were obtained on a daily scale by NASA/POWER platform with a temporal resolution of 33 years (1987–2019) and a spatial resolution of approximately 106 km, thus allowing the calculation of the reference evapotranspiration (PET). Foliation estimation models were adjusted through regression analysis using four-parameter sigmoidal logistic models. The analysis of the foliation trend of coffee plantations was carried out from degrees-day for 70 locations. RESULTS: The general model calibrated to estimate the arabica coffee foliation was accurate (mean absolute percentage error = 2.19%) and precise (R2adj = 0.99) and can be used to assist decision-making by coffee growers. The model had a sigmoidal trend of reduction, with parameters ymax = 97.63%, ymin = 9%, Xo = 3517.41 DD, and p = 6.27%, showing that foliation could reach 0.009% if the necessary phytosanitary controls are not carried out. CONCLUSION: Locations with high air temperatures over the year had low arabica coffee foliation, as shown by the correlation of −0.94. Therefore, coffee foliation can be estimated using degree days with accuracy and precision through the air temperature. This represents great convenience because crop foliation can be obtained using only a thermometer. © 2021 Society of Chemical Industry.
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spelling Can nonlinear agrometeorological models estimate coffee foliation?air temperatureclimate modelCoffea arabicacrop modelingforecastingBACKGROUND: The loss of coffee leaves caused by the attack of pests and diseases significantly reduces its production and bean quality. Thus this study aimed to estimate foliation for regions with the highest production of arabica coffee in Brazil using nonlinear models as a function of climate. A 25-year historical series (1995–2019) of Coffea arabica foliation (%) data was obtained by the Procafé Foundation in cultivations with no phytosanitary treatment. The climate data were obtained on a daily scale by NASA/POWER platform with a temporal resolution of 33 years (1987–2019) and a spatial resolution of approximately 106 km, thus allowing the calculation of the reference evapotranspiration (PET). Foliation estimation models were adjusted through regression analysis using four-parameter sigmoidal logistic models. The analysis of the foliation trend of coffee plantations was carried out from degrees-day for 70 locations. RESULTS: The general model calibrated to estimate the arabica coffee foliation was accurate (mean absolute percentage error = 2.19%) and precise (R2adj = 0.99) and can be used to assist decision-making by coffee growers. The model had a sigmoidal trend of reduction, with parameters ymax = 97.63%, ymin = 9%, Xo = 3517.41 DD, and p = 6.27%, showing that foliation could reach 0.009% if the necessary phytosanitary controls are not carried out. CONCLUSION: Locations with high air temperatures over the year had low arabica coffee foliation, as shown by the correlation of −0.94. Therefore, coffee foliation can be estimated using degree days with accuracy and precision through the air temperature. This represents great convenience because crop foliation can be obtained using only a thermometer. © 2021 Society of Chemical Industry.Federal Institute of Sul de Minas Gerais (IFSULDEMINAS) – Campus MuzambinhoFederal Institute of Mato Grosso do Sul (IFMS)Department of Exact Sciences State University of São Paulo-UNESP Jaboticabal BrazilDepartment of Exact Sciences State University of São Paulo-UNESP Jaboticabal BrazilFederal Institute of Sul de Minas Gerais (IFSULDEMINAS) – Campus MuzambinhoFederal Institute of Mato Grosso do Sul (IFMS)Universidade Estadual Paulista (UNESP)de Oliveira Aparecido, Lucas EduardoLorençone, João ALorençone, Pedro Ade Souza Rolim, Glauco [UNESP]de Meneses, Kamila C [UNESP]da Silva Cabral de Moraes, José R [UNESP]Torsoni, Guilherme B2022-04-29T08:30:17Z2022-04-29T08:30:17Z2022-01-30info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article584-596http://dx.doi.org/10.1002/jsfa.11387Journal of the Science of Food and Agriculture, v. 102, n. 2, p. 584-596, 2022.1097-00100022-5142http://hdl.handle.net/11449/22908410.1002/jsfa.113872-s2.0-85109148436Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengJournal of the Science of Food and Agricultureinfo:eu-repo/semantics/openAccess2024-06-06T13:42:34Zoai:repositorio.unesp.br:11449/229084Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T16:06:09.417785Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false
dc.title.none.fl_str_mv Can nonlinear agrometeorological models estimate coffee foliation?
title Can nonlinear agrometeorological models estimate coffee foliation?
spellingShingle Can nonlinear agrometeorological models estimate coffee foliation?
de Oliveira Aparecido, Lucas Eduardo
air temperature
climate model
Coffea arabica
crop modeling
forecasting
title_short Can nonlinear agrometeorological models estimate coffee foliation?
title_full Can nonlinear agrometeorological models estimate coffee foliation?
title_fullStr Can nonlinear agrometeorological models estimate coffee foliation?
title_full_unstemmed Can nonlinear agrometeorological models estimate coffee foliation?
title_sort Can nonlinear agrometeorological models estimate coffee foliation?
author de Oliveira Aparecido, Lucas Eduardo
author_facet de Oliveira Aparecido, Lucas Eduardo
Lorençone, João A
Lorençone, Pedro A
de Souza Rolim, Glauco [UNESP]
de Meneses, Kamila C [UNESP]
da Silva Cabral de Moraes, José R [UNESP]
Torsoni, Guilherme B
author_role author
author2 Lorençone, João A
Lorençone, Pedro A
de Souza Rolim, Glauco [UNESP]
de Meneses, Kamila C [UNESP]
da Silva Cabral de Moraes, José R [UNESP]
Torsoni, Guilherme B
author2_role author
author
author
author
author
author
dc.contributor.none.fl_str_mv Federal Institute of Sul de Minas Gerais (IFSULDEMINAS) – Campus Muzambinho
Federal Institute of Mato Grosso do Sul (IFMS)
Universidade Estadual Paulista (UNESP)
dc.contributor.author.fl_str_mv de Oliveira Aparecido, Lucas Eduardo
Lorençone, João A
Lorençone, Pedro A
de Souza Rolim, Glauco [UNESP]
de Meneses, Kamila C [UNESP]
da Silva Cabral de Moraes, José R [UNESP]
Torsoni, Guilherme B
dc.subject.por.fl_str_mv air temperature
climate model
Coffea arabica
crop modeling
forecasting
topic air temperature
climate model
Coffea arabica
crop modeling
forecasting
description BACKGROUND: The loss of coffee leaves caused by the attack of pests and diseases significantly reduces its production and bean quality. Thus this study aimed to estimate foliation for regions with the highest production of arabica coffee in Brazil using nonlinear models as a function of climate. A 25-year historical series (1995–2019) of Coffea arabica foliation (%) data was obtained by the Procafé Foundation in cultivations with no phytosanitary treatment. The climate data were obtained on a daily scale by NASA/POWER platform with a temporal resolution of 33 years (1987–2019) and a spatial resolution of approximately 106 km, thus allowing the calculation of the reference evapotranspiration (PET). Foliation estimation models were adjusted through regression analysis using four-parameter sigmoidal logistic models. The analysis of the foliation trend of coffee plantations was carried out from degrees-day for 70 locations. RESULTS: The general model calibrated to estimate the arabica coffee foliation was accurate (mean absolute percentage error = 2.19%) and precise (R2adj = 0.99) and can be used to assist decision-making by coffee growers. The model had a sigmoidal trend of reduction, with parameters ymax = 97.63%, ymin = 9%, Xo = 3517.41 DD, and p = 6.27%, showing that foliation could reach 0.009% if the necessary phytosanitary controls are not carried out. CONCLUSION: Locations with high air temperatures over the year had low arabica coffee foliation, as shown by the correlation of −0.94. Therefore, coffee foliation can be estimated using degree days with accuracy and precision through the air temperature. This represents great convenience because crop foliation can be obtained using only a thermometer. © 2021 Society of Chemical Industry.
publishDate 2022
dc.date.none.fl_str_mv 2022-04-29T08:30:17Z
2022-04-29T08:30:17Z
2022-01-30
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/10.1002/jsfa.11387
Journal of the Science of Food and Agriculture, v. 102, n. 2, p. 584-596, 2022.
1097-0010
0022-5142
http://hdl.handle.net/11449/229084
10.1002/jsfa.11387
2-s2.0-85109148436
url http://dx.doi.org/10.1002/jsfa.11387
http://hdl.handle.net/11449/229084
identifier_str_mv Journal of the Science of Food and Agriculture, v. 102, n. 2, p. 584-596, 2022.
1097-0010
0022-5142
10.1002/jsfa.11387
2-s2.0-85109148436
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Journal of the Science of Food and Agriculture
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 584-596
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
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