Modelagem matemática e cinética de secagem de grãos de café (coffea arabica L.)

Abstract

Mathematical modeling is an essential tool for understanding and optimizing industrial processes. In the context of the drying of coffee beans (Coffea arabica L.), its application enables the prediction of the moisture behavior of the final product under different drying operating conditions. In this context, this study aimed to apply and compare different mathematical models—Page, Midilli, Lewis, and Henderson & Pabis—to describe the drying kinetics of coffee beans, using experimental data obtained from previous studies. Model fitting was performed using nonlinear regression, and the model performance was evaluated based on the coefficient of determination (R²) and the chi-square parameter (χ²). The Midilli model showed the best performance, reaching R² values of up to 0.9999 and χ² on the order of 10⁻⁶, followed by the Page model, which also presented consistent fits in agreement with the experimental data. In contrast, the Lewis and Henderson & Pabis models, although showing good performance at lower temperatures, exhibited slight deviations from the experimental data. The results indicated that the drying coefficient (K) increased substantially with increasing temperature, highlighting the acceleration of the moisture reduction process and the physical consistency of the obtained results. Therefore, this study reinforces the potential of mathematical modeling as a tool for optimizing coffee drying processes, contributing to improvements in post-harvest stages and to maintaining grain quality, a key factor for the added value and competitiveness of the product in the market.