Quantitative forecasting of olive yield in Northern Portugal using a bioclimatic model

Abstract

In this work the objective was to develop a bioclimatic model to forecast olive yield based on airborne pollen, soil water content, and favourable conditions for phytopathological attacks. Olive airborne pollen was sampled from 1998 to 2006 using Cour traps installed in the Tras-os-Montes e Alto Douro region, in the provinces of Valenca do Douro and Vila Nova de Foz-Coa. Meteorological data from a meteorological station located in Pinhao, near the pollen samplers, was used to calculate other independent variables. According to the bioclimatic model, at the flowering stage 63% of regional olive production can be predicted from the regional pollen index, with an average deviation between observed and predicted production of 10%. The variable soil water content enabled an increase in forecasting accuracy of about 30%, and a reduction in the average deviation between observed and predicted production of 6%. The final regression with all three variables tested showed that the bioclimatic model was able to predict the annual variability of regional olive fruit production with an accuracy of 97%, the average deviation between observed and predicted production being 3% for internal validation and 6% for external validation.