The dry matter content (DMC) is a critical factor for assessing the quality of the potato. Using a fish effluent in the sprinkler irrigation has unknown impacts on the DMC of the tuber. Hence, different irrigation treatments were carried out for the irrigation of potato, including T1: fresh water treatment, T2: fish effluent treat- ment and T3: combined fresh water and fish effluent treatment in which leaf wash- ing was used. A multiple regression model (MLR) was developed in which nutri- ent concentrations were considered as the input while DMC was the output of the model. The model was evaluated by the root mean squared error (RMSE) as well as the mean absolute percentage error (MAPE). Then, sensitivity analysis of DMC due to changing the nutrient concentration was carried out through regression mod- els by the sensemaker package. The results illustrate that the developed regression model is highly accurate due to low RMSE and MAPE. The results of the sensitivity analysis indicate that the impact of nitrate on the DMC due to adding a confounder is weak. In other words, nitrate can be removed from the list of independent vari- ables for developing regression models to simulate DMC. The results show that the averages of dry matter content in T1, T2 and T3 were 20.26%, 21.53 and 25.72%, respectively. The results indicate that DMC is increased in the irrigation treatment in which leaf washing is used to mitigate the impact of fish effluent. It is recommend- able to utilize the leaf washing with fresh water when using fish effluent is planned for irrigating potato
