Performance Study of SALTMED Model in Predicting Peppermint (Mentha piperita L.) Yield under Different Deficit Irrigation and Salinity Management Conditions

In the recent years, growth simulation models have been attracted for agricultural engineers in order to predict different crop yields. However, growth simulation of medicinal crops has been rarely studied. In current research, for the first time, the performance of SALTMED model in predicting peppermint yield under different deficit irrigation and salinity conditions was studied. Treatments of water deficit included (100% irrigation requirement (as control), 20 and 40% water deficit) and salinity treatments (control, 2, 3 and 4 dS/m). Calibration of model conducted using control treatment data. After insuring the results, validation of model conducted using other treatments data. Results indicated that model accuracy for predicting peppermint yield was relatively good. The coefficient of determination of model during calibration and validation were 0.953 and 0.801. Studying the separate results showed that the model predicted maximum yield of water deficit levels with higher accuracy than salinity levels. Maximum simulated yield of 20 and 40% water deficit levels were 2.75 and 2.83 ton per hectare while the yield of 2, 3 and 4 dS/m obtained as 2.1, 2.06 and 2.05 ton per hectare.