Drying kinetics of camellia oleifera seeds under hot air drying with ultrasonic pretreatment

Abstract

Camellia oleifera seeds with high moisture content are prone to decay, leading to oil rancidity and seriously affecting subsequent processing and tea oil quality. Thus, an efficient drying method is needed. Hot air drying with ultrasonic pretreatment is a potential drying method for camellia oleifera seeds. In this paper, the effects of key parameters such as ultrasound power, ultrasound pretreatment time, and hot air drying temperature on the moisture ratio of camellia oleifera seeds, as well as the changes in microstructure of both seed shell and seed kernel, and the main quality parameters such as peroxide value and acid value of tea oil were explored. Results showed that the shorter the ultrasound pretreatment time, the greater the ultrasound power, the higher the temperature, the faster the drying rate, and the shorter the drying time. The drying time and specific energy consumption was reduced by up to 26.7 % and 16.8 % with the ultrasonic pretreatment, respectively. The optimal ultrasonic pretreatment time is 2 min, and the ultrasonic power is 300 W. A Genetic Algorithm Optimized Backpropagation Artificial Neural Network (GA-BP-ANN) drying model was proposed to predict the changes in moisture ratio during the drying process of camellia oleifera seeds to provide guidance for the development of intelligent drying system. The experimental results showed that the proposed drying model had a good predictive performance, with an RMSE of 0.0076969 and an R2 of 99.909 %, which can accurately estimate the effect of ultrasonic pretreatment on hot air drying. The research results of this study are expected to reduce post-harvest losses of camellia oleifera fruits and provide theoretical support for the development of drying systems of camellia oleifera seeds and similar agricultural products.