Implementation of a time-temperature-indicator as a shelf life predictive tool for a ready-to-eat salad
Claudia Waldhans, Antonia Albrecht, Rolf Ibald, Dirk Wollenweber, Judith Kreyenschmidt
Abstract
• An app-based system for the digital read-out TTIs was tested for read-to-eat salad • A shelf life model was developed for sliced carrots as the most perishable part • Activation energies of the TTI and product based on microbial growth were consistent • TTIs could predict the product shelf life relatively reliable on a laboratory scale • Charging conditions and systematic errors in practice must be improved and eliminated Dynamic shelf life of a food product is a promising tool for reducing food waste. Time-temperature-indicators (TTIs) for continuous temperature monitoring and shelf life models of perishable products, such as ready-to-eat (RTE) salads, can serve as a basis for such developments. Supply chains can be simplified using digitalized TTI read-out systems. This study tested a novel app system for the digital read-out of OnVu™ TTIs for a RTE salad under laboratory and real supply chain conditions. The RTE salad, consisting of green lettuce, corn, and sliced carrots, was first analyzed to define microbial spoilage kinetics. The data were combined with a predictive model for the OnVu™ TTI, and the shelf life prediction of the RTE salad based on app measurements was validated in laboratory and real-life pilot studies. Sliced carrots were identified as the shelf-life-limiting component and, thus, selected as the basis for modeling. The spoilage kinetics analysis revealed an activation energy of 23.15 kcal/mol, consistent with the activation energy of the TTI. Laboratory analysis showed high accordance between the predicted shelf life by TTI (183 h) and the product shelf life (182 h) at 4°C, however, also high variations in a dynamic temperature scenario due to differences in initial bacterial counts. Pilot studies showed that the TTI shelf lives were shorter than product shelf lives at storage temperatures of 2°C – 217 h for TTI and 261 h for product – and 7°C – 89 h for TTI and 130 h for product – due to unexpectedly faster discoloration. Charging conditions in practice and model improvements can help optimize the process. Nevertheless, the predicted TTI and product shelf lives had generally consistent kinetics, revealing that eliminating systematic errors could help improve the reliability of the app-based system.