Hybrid Modeling of Solar Drying of Peppers: Integration of Classical Thermodynamics and a Predictive Random Forest Model
Mamadou Lamine Coly *
Semiconductor and Solar Energy Laboratory, Cheikh Anta Diop University, P.O. Box 5005, Dakar, Senegal.
BA. Ibrahima
Research Group of Bioactive Substances, Cheikh Anta Diop University, P.O. Box 5005, Dakar, Senegal.
Bou Counta Mbaye
Fluid Mechanics and Applications Laboratory, Cheikh Anta Diop University, P.O. Box 5005, Dakar, Senegal.
Waly Faye
Fluid Mechanics and Applications Laboratory, Cheikh Anta Diop University, P.O. Box 5005, Dakar, Senegal.
Mamadou Seck Gueye
Semiconductor and Solar Energy Laboratory, Cheikh Anta Diop University, P.O. Box 5005, Dakar, Senegal.
Demba Diallo
Semiconductor and Solar Energy Laboratory, Cheikh Anta Diop University, P.O. Box 5005, Dakar, Senegal.
Omar Ngor Thiam
Fluid Mechanics and Applications Laboratory, Cheikh Anta Diop University, P.O. Box 5005, Dakar, Senegal.
*Author to whom correspondence should be addressed.
Abstract
This study investigated the drying behaviour of green, red and yellow peppers in an indirect forced-convection solar dryer by combining conventional drying-kinetics analysis with Random Forest prediction. Solar irradiance, dryer-air temperature, product temperature and changes in product moisture content were monitored during drying. Irradiance reached 872 W/m², while dryer-air and product temperatures reached 54.6 °C and 56.6 °C, respectively. The air temperature exceeded ambient temperature by more than 21 °C during the reported period. All varieties showed a decrease in moisture content with time, with a higher initial evaporation rate and faster dehydration observed for green peppers. Red and yellow peppers showed broadly similar moisture-content profiles. Six semi-empirical models were fitted to the experimental moisture-ratio data. The two-term model provided the best fit for green peppers (R² = 0.9947), whereas the Midilli model performed best for red and yellow peppers (R² = 0.9908 and 0.9903, respectively). Effective diffusivity, estimated using a simplified solution of Fick's second law, was highest for green peppers (4.943 × 10⁻¹⁰ m²/s), followed by yellow (3.125 × 10⁻¹⁰ m²/s) and red peppers (2.768 × 10⁻¹⁰ m²/s). Random Forest feature importance identified elapsed time (approximately 35%) and product temperature (approximately 28.7%) as the leading predictors of residual moisture ratio. The findings describe varietal differences in solar-drying kinetics and show the potential value of combining semi-empirical drying models with data-driven prediction.
Keywords: Drying, solar dryer, modeling, predictive model, peppers