Study of microwave and convective drying kinetics of pea pods (Pisum sativum L.): A new modeling approach using support vector regression methods optimized by dragonfly algorithm technique

Abstract

Machine learning and mathematical modeling techniques have been conducted to model the thin layer drying kinetics of pea pods, under either microwave or conventional air drying,. The effect of nine different microwave output powers (200–1000 W) and five different ventilated oven temperatures (40, 60, 80, 100, and 120°C) on drying kinetics was studied. The experimental drying rates were fitted to 11 literature semi‐empirical models to determine the kinetic parameters, finding the higher goodness‐of‐fit for the Midilli et al. model (average R2 = 0.999 for both drying methods). Moreover, the data were modeled using support vector machine (SVM) for regression which was optimized with dragonfly algorithm (DA) technique. The best result was obtained by Gaussian kernel with the optimal parameters σ, C, and ε values estimated as 0.2871, 78.45, and 0, respectively. The small root mean square error (RMSE = 0 …