Work

Predicting equilibrium water activity using different moisture isotherms and estimating moisture transfer in a multicomponent mixture for vegetable chips

Year: 2025

Type: article

Abstract: The objective of this work was to develop a prediction model to calculate the equilibrium water activity ( a w e ) of a formulation blend used to manufacture vegetable chips and to assess the moisture transfer occurring among the formulation constituents. Experimental moisture sorption isotherms were determined for each ingredient and described by different models. The Guggenheim-Anderson-de Boer (GAB) model better described the isotherms of dry ingredients whereas piecewise models better described wet ingredients as determined by the Bayesian Information Criterion (BIC). The blend equilibrium water activity, a w e , was determined using the most suitable models describing each ingredient's isotherm and assuming the blend's initial moisture content remains constant at equilibrium. The prediction model had high accuracy demonstrated by the low values of key statistical parameters like the Mean Absolute Error (MAE), the Root Mean Square Error (RMSE) and the Mean Absolute Percentage Error (MAPE), calculated as 0.007, 0.008 and, 0.73 %, respectively. Investigation into moisture transfer revealed that mashed potatoes lost 29 % moisture, while a flavor powder ingredient exhibited a notable 7525 % increase due to deliquescent properties. The findings suggest that the equilibrium water activity can be reliably calculated and utilized to estimate moisture redistribution among the blend's constituents in the vegetable chip formulations. • GAB model best fit dry ingredients showing gradual moisture uptake as a w increased. • Piecewise models best fit ingredients with rapid moisture uptake above a critical a w . • Bayesian Information Criterion used to evaluate moisture sorption models' adequacy. • Developed model predicts equilibrium water activity with high accuracy, RMSE = 0.008. • Sweet potato retained more moisture than mashed potato due to higher sugar content.

Source: LWT

DOI: 10.1016/j.lwt.2025.117732

Authors: Hrithik Shetty, Bhavesh Patel, Debora Saibene, Yael Vodovotz, Osvaldo H Campanella

Institutions: The Ohio State University, PepsiCo (United Kingdom)

Language: English

Topic: Food Drying and Modeling

Subfield: Food Science

Field: Agricultural and Biological Sciences

Domain: Life Sciences

SDG: Zero hunger

Open Access status: gold

Estimated APC paid: $3,240