Agrometeorological models for groundnut crop yield forecasting in the Jaboticabal, São Paulo State region, Brazil

Victor   Brunini Moreto; Glauco  de Souza Rolim

Agrometeorological models for groundnut crop yield forecasting in the Jaboticabal, São Paulo State region, Brazil

Autores

Victor Brunini Moreto

Glauco de Souza Rolim

Editor

Universidade Estadual de Maringá

Descripción

Forecast is the act of estimating a future ev ent based on current data. Ten-day period (TDP) meteorological data were used for modeling: mean air temperature, precipitation and water balance components (water deficit (DEF) and surplus (EXC) and soil water st orage (SWS)). Meteorological and yield data from 1990-2004 were used for calibration, and 2005-2010 were used for testing. First step was the selection of variables via correlation analysis to determine which TDP and climatic variables have more influence on the crop yield. The selected variables were used to construct mo dels by multiple linear regression, using a stepwise backwa rds process. Among all analyzed models, the following was notable: Yield = - 4.964 x [SWS of 2° TDP of December of the previous year (OPY)] – 1.123 x [SWS of 2° TDP of November OPY] + 0.949 x [EXC of 1° TDP of February of the productive year (PY)] + 2.5 x [SWS of 2° TDP of February OPY] + 19.125 x [EXC of 1° TDP of May OPY] – 3.113 x [EXC of 3° TDP of January OPY] + 1.469 x [EXC of 3 TDP of January of PY] + 3920.526, with MAPE = 5.22%, R 2 = 0.58 and RMSEs = 111.03 kg ha -1 .