Can nonlinear agrometeorological models estimate coffee foliation?
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , |
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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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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1808128608186662912 |