Models for simulating the frequency of pests and diseases of Coffea arabica L.

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MetadadosDescriçãoIdioma
Autor(es): dc.contributorScience and Technology of Mato Grosso do Sul-
Autor(es): dc.contributorUniversidade Estadual Paulista (Unesp)-
Autor(es): dc.creatorde Oliveira Aparecido, Lucas Eduardo-
Autor(es): dc.creatorde Souza Rolim, Glauco [UNESP]-
Data de aceite: dc.date.accessioned2022-02-22T00:25:10Z-
Data de disponibilização: dc.date.available2022-02-22T00:25:10Z-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2020-12-11-
Data de envio: dc.date.issued2020-07-01-
Fonte completa do material: dc.identifierhttp://dx.doi.org/10.1007/s00484-020-01881-5-
Fonte completa do material: dc.identifierhttp://hdl.handle.net/11449/198650-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/198650-
Descrição: dc.descriptionWe developed models for simulating trends over time as functions of the thermal index and models for estimating the levels of infestation of the coffee leaf miner and coffee berry borer and the severity of disease for coffee leaf rust and cercospora, the main phytosanitary problems in coffee crops around the world. We used historical series of climatic data and levels of pest infestation and disease severity in Coffea arabica for high and low yields for seven locations in the two main coffee-producing regions in the state of Minas Gerais in Brazil, Sul de Minas Gerais and Cerrado Mineiro. We conducted two analyses: (a) we simulated the trends of the progress of diseases and pests over time using non-linear models. We only used the thermal index because air temperature is commonly measured by farmers in the regions. (b) We estimated the levels of pest infestation and disease severity using multiple linear regression, with the levels of diseases and pests as dependent variables and accumulated degree days (DD), coffee foliage (LF) estimated by DD and the number of nodes (NN) estimated by DD as independent variables. We used DD and LF = f (DD) and NN = f (DD) to predict diseases and pests with accuracy. MAPEs were 19.6, 5.7, 9.5, and 15.8% for rust, cercospora, leaf miner, and berry borer, respectively, for Sul de Minas Gerais. Establishing phytosanitary alerts using only air temperature was possible with these models.-
Descrição: dc.descriptionIFMS-Federal Institute of Education Science and Technology of Mato Grosso do Sul Campus of Naviraí-
Descrição: dc.descriptionDepartment of Exact Sciences State University of São Paulo-UNESP-
Descrição: dc.descriptionDepartment of Exact Sciences State University of São Paulo-UNESP-
Formato: dc.format1063-1084-
Idioma: dc.languageen-
Relação: dc.relationInternational Journal of Biometeorology-
???dc.source???: dc.sourceScopus-
Palavras-chave: dc.subjectCercospora-
Palavras-chave: dc.subjectCrop modelling-
Palavras-chave: dc.subjectForecasting;-
Palavras-chave: dc.subjectLeaf miner-
Título: dc.titleModels for simulating the frequency of pests and diseases of Coffea arabica L.-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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