Mathematical and ANN Modelling for Convective Drying of Spanish Cherry Seeds: Bioactive Degradation, Energy Efficiency, and Mass Transfer Evaluation

The seed of the Spanish cherry (Mimusops elengi) possesses notable nutritional and medicinal properties. The convective drying method is employed to investigate the drying properties of the seeds using mathematical and Artificial Neural Networks (ANN) models. This study also determines Mass Transfer (MT) parameters and Specific Energy Consumption (SEC) at drying temperatures of 50, 60, 70, and 80 °C and assesses the influence of these temperatures on biochemical parameters. All five mathematical models, namely, Newton, Logarithmic, Page, Henderson and Pabis, Midilli and Kucuk, and the ANN model, exhibit a high degree of accuracy in their fit. The ANN model surpasses all empirical models in predicting drying behaviour across all drying temperatures, with the highest correlation coefficient of 0.9987 and the lowest root mean square error value of 0.01364. Moisture diffusivity and the convective mass transfer coefficient were found ranged from 4.46 × 10^–9 to 10.2 × 10^–9 m²/s and 8.9 × 10^–7 to 25.3 × 10^–7 m/s, respectively, at drying temperatures of 50 to 80 °C. The SEC were found 354.21 to 185.42 kWh/kg, respectively, at 50 to 80 °C drying temperatures. A degradation kinetic study evaluated the impact of drying temperature on bioactive compounds, including Total Phenolic Content (TPC), Total Flavonoid Content (TFC), and antioxidant activity. The degradation rate was found higher for TPC compared to antioxidant activity and TFC at different drying temperatures. This study will help facilitate a unified strategy for researchers and local farmers to develop technologies and processing techniques that utilize the enormous potential of this fruit seed.