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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

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

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Author(s):
Aparecido, Lucas Eduardo de Oliveira [1] ; Rolim, Glauco de Souza [2]
Total Authors: 2
Affiliation:
[1] IFMS Fed Inst Educ Sci & Technol Mato Grosso do S, Campus Navirai, Navirai - Brazil
[2] State Univ Sao Paulo UNESP, Dept Exact Sci, Jaboticabal - Brazil
Total Affiliations: 2
Document type: Journal article
Source: INTERNATIONAL JOURNAL OF BIOMETEOROLOGY; v. 64, n. 7 MAR 2020.
Web of Science Citations: 0
Abstract

We 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. (AU)

FAPESP's process: 15/17797-4 - Agrometeorological models for forecasting pests and diseases in Coffea arabica L. in the State of Minas Gerais
Grantee:Lucas Eduardo de Oliveira Aparecido
Support Opportunities: Scholarships in Brazil - Doctorate