Artificial Neural Network Modeling of Moisture and Oil Content of Pretreated Deep-Fat-Fried Kurdish Cheese Nuggets

In this research, the effects of chitosan (CH) (0, 0.5 and 1.5%) on moisture and oil content of deep-fat-fried Kurdish cheese nuggets was studied, and artificial neural network was applied for modeling of these parameters during frying. Either pretreated or control samples were fried at 150, 170 and 190◦C for 0, 1, 2, 3 and 4 min. The results indicated that moisture content decreased with increasing frying time and temperature. The highest reduction in fat absorption during frying was observed in samples were coated with batter containing CH (1.5%) that include 19.42%. An artificial netural network was developed to estimate moisture and oil content of fried cheese nuggets. The developed artificial neural network which included 19 hidden neurons could predict moisture and oil content with correlation coefficient of 0.92 and 0.92 for moisture core and crust and 0.84 and 0.85 for oil content, respectively. These results indication method for moisture and oil content of deep-fat-fried Kurdish cheese nuggets.