Spatially variable pesticide application in olive groves: Evaluation of potential pesticide-savings through stochastic spatial simulation algorithms

Abstract Site-specific management using spatial crown volume characterization can greatly reduce the amount of pesticides applied in agricultural treatments performed with air-assisted sprayers, while helping farmers achieve the European legislation on safe use of pesticides. Nevertheless, variable rate treatments in olive groves have received little attention. Thus, field research was conducted in a 20.6–ha traditional olive grove. Two attributes of the trees - tree crown volume (V) and tree projected area - were determined, using 67 samples for V and all trees of the field (1433) for tree projected area. Spatial continuity of both attributes was modelled with exponential variograms. To gain a measure of local uncertainty, stochastic simulation algorithms were applied. One hundred simulated images were obtained for tree projected area using direct sequential simulation. Tree projected area simulations were used to improve spatial prediction of V, more difficult and more expensive to obtain, taking advantage of the high linear correlation between both variables(rxy = 0.72, p