Modeling sorption properties of maize by-products obtained using the Dynamic Dewpoint Isotherm (DDI) method

Abstract

The amount of water available in food for enzymatic and oxidative reactions as well as for microbiological proliferation is an important factor in the conservation, storage, and development of new food products. Adsorption and desorption steps at different temperatures act as important parameters used to further understand the behavior, response, and interference of moisture in the technological properties of food. This behavior can be observed using sorption isotherms. The use of by-products from maize processing has increased. Obtaining food from these materials depends on the technological analysis of these raw materials. The objective of this study was to show the benefits of a predictive experimental model of the sorption behavior of flours obtained from two different by-products of waxy corn wet-milling using the Dynamic Dewpoint Isotherm (DDI) method. The sorption profiles of flours at 20, 30, and 40 °C were estimated and mathematically fitted to different models. This study showed type III sorption curves (Thommes et al., 2015) behavior for both flours and the mathematical adequacy of different models. Numerical math methodology, with validated statistics, showed that the Peleg model is the best fit. The net isosteric heat of sorption estimated using the Clausius–Clapeyron equation, decreased in both flours when the moisture content of samples increased. Residual pattern analysis and linear graphical correlation of predicted models and experimental data showed that the scoring method using the interpolation of data obtained in the analyses of statistical factors and segregation using Sturges’ rule, is a viable way to determine the most suitable mathematical model to describe sorption curves.