Simulating shelf life determination by two simultaneous criteria

A Multi-Model Approach to Implement a Dynamic Shelf Life Criterion in Meat Supply Chains

The high perishability of fresh meat results in short sales and consumption periods, which can lead to high amounts of food waste, especially when a fixed best-before date is stated. Thus, the aim of this study was the development of a real-time dynamic shelf-life criterion (DSLC) for fresh pork filets based on a multi-model approach combining predictive microbiology and sensory modeling. Therefore, 647 samples of ma-packed pork loin were investigated in isothermal and non-isothermal storage trials. For the identification of the most suitable spoilage predictors, typical meat quality parameters (pH-value, color, texture, and sensory characteristics) as well as microbial contamination (total viable count, Pseudomonas spp., lactic acid bacteria, Brochothrix thermosphacta, Enterobacteriaceae) were analyzed at specific investigation points. Dynamic modeling was conducted using a combination of the modified Gompertz model (microbial data) or a linear approach (sensory data) and the Arrhenius model. Based on these models, a four-point scale grading system for the DSLC was developed to predict the product status and shelf-life as a function of temperature data in the supply chain. The applicability of the DSLC was validated in a pilot study under real chain conditions and showed an accurate real-time prediction of the product status.

Shelf Life of Food Products: From Open Labeling to Real-Time Measurements

The labels currently used on food and beverage products only provide consumers with a rough guide to their expected shelf lives because they assume that a product only experiences a limited range of predefined handling and storage conditions. These static labels do not take into consideration conditions that might shorten a product's shelf life (such as temperature abuse), which can lead to problems associated with food safety and waste. Advances in shelf-life estimation have the potential to improve the safety, reliability, and sustainability of the food supply. Selection of appropriate kinetic models and data-analysis techniques is essential to predict shelf life, to account for variability in environmental conditions, and to allow real-time monitoring. Novel analytical tools to determine safety and quality attributes in situ coupled with modern tracking technologies and appropriate predictive tools have the potential to provide accurate estimations of the remaining shelf life of a food product in real time. This review summarizes the necessary steps to attain a transition from open labeling to real-time shelf-life measurements.

A New Look at Kinetics in Relation to Food Storage

Modern mathematical software and user-friendly interactive programs can simplify and speed up kinetics calculations. They also open the way for new approaches to storage data gathering and analysis. This is demonstrated with a recently introduced simple exponential model that is interchangeable with the Arrhenius equation and endpoints and successive points methods and that estimates chemical degradation kinetics parameters from a small number of isothermal or nonisothermal experimental data. Also presented are a method to determine shelf life using two chemical markers and a global phenomenological model for peaked reactions, such as those encountered in lipid oxidation. Also recently introduced are freely downloadable Wolfram Demonstrations and other interactive software to generate, visualize, examine, and/or compare actual or hypothetical storage scenarios in minutes. They include programs that solve pairs of simultaneous nonlinear algebraic or differential rate equations by passing two reconstructed degradation curves, or a single nonisothermal curve, through two entered experimental points by moving the degradation parameters’ sliders on the screen.