Method for computer-aided modeling of water adsorption isotherms in Achira biscuits (Canna edulis K.)

Mathematical modeling of water adsorption isotherms (WAI) plays a fundamental role in food engineering, enabling the quantitative description and prediction of moisture sorption behavior in food systems. Despite its relevance, there is a notable gap in the literature concerning computer-aided methods for fitting WAI data. This study aims to fill that gap by introducing an advanced computational approach for modeling WAI using three empirical equations: Peleg, Polynomial, and Double Log Polynomial (DLP). A comprehensive experimental dataset was used, consisting of WAI measurements from Achira biscuits over a wide range of water activities (a_w: 0.1 to 0.9) and storage temperatures (25, 35, and 45 °C). The predictive performance of each model was assessed using statisticalgoodness-of-fit metrics, including root mean square error (RMSE), coefficient of determination (R²), and adjusted R², supported by graphical analysis. All models achieved excellent fitting results, with RMSE values below 5 % and R² and R²_adj consistently above 99 %. These findings validate the effectiveness of the computer-aided modeling framework for accurately describing WAI behavior in low-moisture foods. Furthermore, the study demonstrates the potential of this approach as a practical and reliable tool for optimizing storage conditions, enhancing moisture control, and supporting decision-making in food quality and shelf-life management. This study:•Enables the statistical modeling of WAI.•Proposes an advanced framework for the computer-aided procedure of WAI.