Yield Mapping of the Hand-harvested Pistachio using Geographic information System (GIS)

Precision Agriculture by managing in-farm variables and acquiring soil and product variable properties, mapping, analyzing variables, and accepting appropriate management practices lead to optimal use of inputs and increase performance with minimizing environmental effects. Therefore, in order to implement precision Agriculture, the first step is sufficient knowledge about the quantity of the yield. so, in this research, the pistachio yield monitoring system was designed and constructed and the machine performance was investigated in the laboratory tests. in this study the number of Connecting chains and height of the reservoir were selected as Variable factors. The number of chains at 3 levels (2, 3 and 4) and reservoir height at 3 levels (10, 20 and 30 cm) were investigated. The results showed that optimum values for the weighing of the product in the reservoir were not significant for the number of chains, so, in order to achieve better equilibrium in this study, four chains were used. Also, with the 20 cm height of the reservoir, the best results were obtained. The highest error value was 3.6%. After the laboratory tests, the system was transferred to the pistachio orchard and weight data were recorded associated with the location of each pistachio tree (by GPS). Among the methods of IDW interpolation, ordinary kriging, simple kriging, and general kriging, the ordinary Kriging method was introduced as the best method due to lower RMSE (1160.89). At the end, the yield map of the product was created by the usual Kriging method in the GIS software, which can be used along with other data as a prescriptive map for better management of the orchards. Among the methods of IDW interpolation, ordinary kriging, simple kriging, and general kriging, the ordinary Kriging method was introduced as the best method due to lower RMSE (1160.89). At the end, the yield map of the product was created by the usual Kriging method in the GIS software, which can be used along with other data as a prescriptive map for better management of the orchards.