Forecasting olive ( Olea europaea L.) production using aerobiological and meteorological variables in T étouan (NW Morocco)

This study describes the first forecasting models of the olive fruit production based on pre-peak airborne annual pollen integral (APIn) fromOlea europaea L. and meteorological data prior and during the flowering and ripening olive trees in T étouan (NW of Morocco) over a period of 11 years (2008–2018). Aerobiological sampling was conducted using Burkard volumetric Hirst trap. The data were analyzed by multiple regression analysis. Several forecasting models developed were validated using data of 2018 (not included in the models) and compared with real olive crop data obtained from the Provincial Directions of Agriculture of Tétouan. The main factors influencing the final olive crop were the rainfall registered prior to flowering (March) and during fruit growing and minimum temperatures in July and June. The most accurate fore cast models for the 2018 harvest showed the highest coefficient of determination (R2 = 0.98;p <  000.1) and predicted the lowest RMSE between expected and observed data (452.80 and 398.75). The models developed provide efficient olive crop forecasting using independent variables which can be previously obtained. However, despite that the APIn is a reliable bio-indicator of regional crop yiel d forecasting in intensive farming areas it was not strongly representative in the regression equation probably due to the low airborne pollen concentrations recorded in Tétouan.
Source: Aerobiologia - Category: Environmental Health Source Type: research