Bioresource and Agricultural Engineering Commons^™

Modeling The Moisture Content And Drying Rate Of Zucchini (Cucurbita Pepo L.) In A Solar Hybrid Dryer Using Ann And Anfis Methods, Halil Nusret Bulus, Aytac Moralar, Soner Celen

The Philippine Agricultural Scientist

Estimating product drying kinetics is critical to obtain the best drying process without compromising product quality and necessitates the development of numerical drying models. This research aims to compare the prediction models developed using artificial neural network (ANN) and adaptive network-based fuzzy inference system (ANFIS), two popular machine learning approaches in the recent years. Zucchini slices were chosen as samples and dried in a solar-assisted microwave belt dryer at 0.245 m/min belt speed and microwave powers of 0.7, 1, and 1.4 kW. On the data set obtained by computing the moisture content and drying rate values, prediction models were developed …