TIME TEMPERATURE HISTORIES OF PERISHABLE FOODS DURING SHOPPING, TRANSPORT AND HOME REFRIGERATED STORAGE

摘要

The time temperature histories of perishable foods after shopping and during home refrigerator storage were studied. RFID based temperature data loggers were used to predict mean temperature histories and mean storage times in both parts of the after shopping history. The data were transformed into frequency distribution functions. These functions were used for a microbial risk assessment case study of potential Listeria monocytogenes (LM) growth and survival. @risk software was used to generate the Monte-Carlo prediction of the distribution function of the final LM concentration. Sensitivity analysis was done to predict the most important factors influencing the final concentration and to determine the most promising factors for decreasing the risk of violating legislation regarding microbial concentrations during the shelf-life of products.