Measurement and prediction of microwave efficiency during drying of apple leaves

Aghili Nategh, Nahid; Dalvand, Mohammad Jafar

doi:10.22034/jrmam.2023.14049.610

Measurement and prediction of microwave efficiency during drying of apple leaves

Document Type : Research Paper

Authors

nahid aghili nategh ¹

mohammad jafar dalvand ²

¹ Department of Agricultural Machinery Engineering, Sonqor Agriculture Faculty, Razi University, Kermanshah, Iran.

² PhD Graduated in Agricultural Machinery Engineering, Facumlty of Agricultural Engineering and Technology, University of Tehran, Karaj, Iran

https://doi.org/10.22034/jrmam.2023.14049.610

Abstract

Drying is one of the most effective methods to increase the shelf life of food products. Increasing efficiency and reducing energy consumption in drying is essential. Saving time and energy are the best advantages of the microwave drying method. So this work aims to investigates the influences of microwave power (P), mass of product (M) and time (T) on the absorbed energy and energy loss and also predict the efficiency during microwave dehydration of apple leaves. We perform the investigation at P=100, 300 and 600 W, M=20, 40, 60, 80 and 100 g; and T=60, 90, 120, 150 and 180 s. In this paper, three different machine learning methods are used to simulate the absorbed energy and energy loss of apple along with prediction of the microwave efficiency during dehydration process. These methods are: artificial neural networks (ANNs), adaptive neuro fuzzy inference system (ANFIS) and support vector machines (SVM) coupled with firefly algorithm (FFA) Our results indicates that the amount of absorbed energy by apple during microwave dehydration strongly depends on on the amount of the mass. The highest and lowest efficiency of the microwave was observed in the power of 600 W and mass of 100 g, and the lowest efficiency was observed in the time of 180 s and power of 100W. Also, absorbed energy at 600W was found to be almost four times higher than that at 100 W. ANFIS and SVM-FFA showed good results than ANN for predicting absorbed energy, energy loss and microwave efficiency.

Keywords

microwave؛ efficiency؛ SVM؛ firefly algorithm

ANN

ANFIS

Subjects