Agrometeorological models for forecasting pests and diseases in Coffea arabica L. in the State of Minas Gerais

• Grant number: 15/17797-4
• Support Opportunities: Scholarships in Brazil - Doctorate
• Start date: March 01, 2016
• End date: May 23, 2017
• Field of knowledge: Agronomical Sciences - Agronomy - Agricultural Meteorology
• Principal Investigator: Glauco de Souza Rolim
• Grantee: Lucas Eduardo de Oliveira Aparecido
• Host Institution: Faculdade de Ciências Agrárias e Veterinárias (FCAV). Universidade Estadual Paulista (UNESP). Campus de Jaboticabal. Jaboticabal , SP, Brazil

Abstract

The pests and diseases caused extensive damage in coffee plantations. Thus, early warning systems (SAF) are appropriate, besides avoiding the damage and applications excessive of pesticide, assists producers in planning and decision making of the crop. The SAF can be performed with estimation or forecast models. In science estimation is the use of actual data to simulate an actual process, and forecast is the use of actual data to simulate a future process or event. Thus, this project aims to calibrate and test forecasting models, with minimum anticipation for decision making, for the main pests (Broca and Bicho-mineiro) and diseases (Ferrugem and Cercosporiose) of coffee for the state of Minas Gerais. The locations that will be used are: Boa Esperança, Carmo de Minas, Muzambinho and Varginha (South of Minas) and Araxá, Araguari and Patrocínio (Cerrado Mineiro). Meteorological data to be used will come from weather stations surface next to the areas of phytosanitary experiments. Data of forecasting of weather and climate will be used by the global circulation model (MCG) ECMWF (European Center for Medium-Range Weather Forecast). Monthly historical data of pests and diseases of at least 8 years will be provided by PROCAFÉ of coffee of the regions. The modeling will be developed in three steps: the first will be analyzed which weather elements (surface and ECMWF) have higher relation with the coffee pests and diseases and in which periods, using multivariate techniques such as principal component analysis (PCA). In the second stage, the regression analysis, linear and nonlinear will be applied in selected elements of the first stage to predict the pests and diseases in the regions studied. Models will be tested with different periods of anticipation, 1-11 days to forecast pest and diseases. The tests will be conducted to evaluate the accuracy, precision and tendency with the selected models by comparing observed and predicted data. Finally, the third stage will be generated warning maps for the state of Minas Gerais as from ECMWF data.

Scientific publications

(References retrieved automatically from Web of Science and SciELO through information on FAPESP grants and their corresponding numbers as mentioned in the publications by the authors)

APARECIDO, LUCAS EDUARDO DE OLIVEIRA; ROLIM, GLAUCO DE SOUZA. Models for simulating the frequency of pests and diseases of Coffea arabica L.. INTERNATIONAL JOURNAL OF BIOMETEOROLOGY, v. 64, n. 7, MAR 2020. (15/17797-4)

DE OLIVEIRA APARECIDO, LUCAS EDUARDO; DE SOUZA ROLIM, GLAUCO; DA SILVA CABRAL DE MORAES, JOSE REINALDO. Validation of ECMWF climatic data, 1979-2017, and implications for modelling water balance for tropical climates. INTERNATIONAL JOURNAL OF CLIMATOLOGY, v. 40, n. 15, APR 2020. (15/17797-4)

Academic Publications

(References retrieved automatically from State of São Paulo Research Institutions)

APARECIDO, Lucas Eduardo de Oliveira. Agrometeorological models for forecasting pests and diseases in Coffea arabica L. In the state of Minas Gerais. 2019. Doctoral Thesis - Universidade Estadual Paulista (Unesp). Faculdade de Ciências Agrárias e Veterinárias. Jaboticabal Jaboticabal.