Applications of Probabilistic Engineering in Food Moisture Management

By Dr. J. Antonio Torres

Tecnologico de Monterrey, Mexico

Thursday April 26th, 2018 at 11:00 am (Mexico City, MX; UTC -05:00)

The estimation of the product moisture content impact on quality and safety during its shelf-life is essential to formulate products, design processes, select packaging options, and recommend handling conditions from when the product leaves the packaging line until it reaches the final consumer. Although an appropriate selection of ingredient, drying methods and processing parameters can yield foods with desirable quality factors, they remain sensitive to moisture gain/loss during storage and transportation. Therefore, moisture exchange with the environment must be prevented by packaging materials achieving the shelf-life needed for product distribution. Also important is a marketing decision stating the percentage of products that must retain a desirable quality at the end of their shelf-life. The management of the moisture content and its interaction with intrinsic properties and the surrounding environment requires mathematical models and information obtained using good statistical designs, adequate methods and measuring instruments, and well-trained personnel. This information has statistical variability including that due to the natural variation of ingredients and the handling environment. Despite control efforts and specification limits, food production, processing steps and packaging materials will also contribute to modeling data variability. This presentation focuses on the inclusion of this variability in a Monte Carlo-based probabilistic approach when using estimation models for moisture management purposes. The examples to be presented include comparisons of deterministic and probabilistic determinations of: (1) Equilibrium a_w for multiple ingredients with different initial a_w; (2) Shelf-life of moisture-sensitive products; (3) Estimation of the required packaging moisture permeance; and (4) Estimation of the optimized package fill setting by risk analysis considering moisture exchange with the environment.