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The aim of this work was to model the moisture content ( MC ) and drying rate ( DR ) using artificial neural network (ANN) methodology. Many architectures have been tested and the best topology was selected based on a trial and error method. The dataset was randomly divided into 60, 20, and 20 % for training, test, and validation stage of the ANN model, respectively. The best topology was 10-{29-13}-2 obtained with high correlation coefficient  R  (%) of {99.98, 98.41} and low root mean square error RMSE (%) (0.36, 6.29) for  MC  and  DR , respectively. The obtained ANN can be used to interpolate the  MC  and  DR  with high accuracy.

ANN-based approach to model MC/DR of some fruits under solar drying