Modeling the Moisture Content and Drying Rate of Zucchini (Cucurbita pepo L.) in a Solar Hybrid Dryer Using ANN and ANFIS Methods

Authors

Halil Nusret Bulus, Tekirdag Namik Kemal University, Corlu Faculty of Engineering, Department of Computer Engineering, 59830, Tekirdağ, Turkey
Aytac Moralar, Tekirdag Namik Kemal University, Corlu Faculty of Engineering, Department of Mechanical Engineering, 59830, Tekirdağ, Turkey
Soner Celen, Tekirdag Namik Kemal University, Corlu Faculty of Engineering, Department of Mechanical Engineering, 59830, Tekirdağ, TurkeyFollow

Publication Date

9-1-2023

Abstract

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 using ANN and ANFIS approaches. These models were evaluated using the coefficient of determination, mean absolute percent error, and root mean square error data. The ANFIS-based prediction model outperformed the ANN model in terms of drying rate performance, but the ANN model outperformed the ANFIS model in terms of moisture content values. Results showed that both methods established can be utilized to estimate zucchini slices.

Recommended Citation

Bulus, Halil Nusret; Moralar, Aytac; and Celen, Soner (2023) "Modeling the Moisture Content and Drying Rate of Zucchini (Cucurbita pepo L.) in a Solar Hybrid Dryer Using ANN and ANFIS Methods," The Philippine Agricultural Scientist: Vol. 106: No. 3, Article 6.
Available at: https://www.ukdr.uplb.edu.ph/pas/vol106/iss3/6