Utilization of mathematical models to manage risk of holding cold food without temperature control

Multiparametric quantification of thermal heterogeneity within aqueous materials by water 1H NMR spectroscopy: Paradigms and algorithms

Processes involving heat generation and dissipation play an important role in the performance of numerous materials. The behavior of (semi-)aqueous materials such as hydrogels during production and application, but also properties of biological tissue in disease and therapy (e.g., hyperthermia) critically depend on heat regulation. However, currently available thermometry methods do not provide quantitative parameters characterizing the overall temperature distribution within a volume of soft matter. To this end, we present here a new paradigm enabling accurate, contactless quantification of thermal heterogeneity based on the line shape of a water proton nuclear magnetic resonance (¹H NMR) spectrum. First, the ¹H NMR resonance from water serving as a "temperature probe" is transformed into a temperature curve. Then, the digital points of this temperature profile are used to construct a histogram by way of specifically developed algorithms. We demonstrate that from this histogram, at least eight quantitative parameters describing the underlying statistical temperature distribution can be computed: weighted median, weighted mean, standard deviation, range, mode(s), kurtosis, skewness, and entropy. All mathematical transformations and calculations are performed using specifically programmed EXCEL spreadsheets. Our new paradigm is helpful in detailed investigations of thermal heterogeneity, including dynamic characteristics of heat exchange at sub-second temporal resolution.

Prediction of Escherichia coli O157:H7, Salmonella , and Listeria monocytogenes Growth in Leafy Greens without Temperature Control

A recent study by the Centers for Disease Control and Prevention reported that between 1998 and 2008, leafy greens outbreaks accounted for 22.3% of foodborne outbreaks in the United States. Several studies on the growth of bacteria at different temperatures have been conducted; however, there is a need for the prediction of bacterial growth when leafy greens are transported without temperature control. Food products, when taken out of refrigeration, undergo a temperature change, with the rate of temperature change being proportional to the difference in the temperature of food and its surroundings. The objective of this study was to estimate the growth of Escherichia coli O157:H7, Salmonella enterica , and L. monocytogenes in leafy greens during transportation from retail to home at ambient temperatures ranging from 10 to 40°C for up to 10 h. Experiments were conducted to monitor the temperature increase in fresh spinach taken from refrigeration temperature to ambient temperature. The growth of pathogens was predicted using these changing temperature profiles with the three-phase linear model as a primary model and the square root model as the secondary model. The levels of E. coli O157:H7, S. enterica , and L. monocytogenes increased by 3.12, 2.43, and 3.42 log CFU at 40°C for the 10-h period, respectively, when no lag phase was assumed. If leafy greens are not kept out of refrigeration for more than 3 h, when the air temperature is 40°C or more, pathogen growth should be less than 1 log CFU. These results would assist in developing recommendations for food transportation without refrigeration.

Transportation of perishable and refrigerated foods in mylar foil bags and insulated containers: a time-temperature study

Data are lacking on the temperature changes of food during transport without the use of refrigerated trucks. The purpose of this study was to evaluate the ability of several insulated and noninsulated containers with or without frozen gel packs to keep perishable and refrigerated foods within the temperature safe zone in relationship to duration of transport. The study was designed to duplicate the practices exhibited by customers purchasing perishable food products from a cash-and-carry business. Approximately 40 perishable food items were evaluated. Four types of containers were tested: a mylar foil bag, a commercial insulated bag, a generic insulated bag, and a commercial insulated blanket. Mixed foods were placed into these containers with or without frozen gel packs, transported in unrefrigerated vehicles, and monitored for 4 h for temperature changes. Two environmental temperatures, room temperature of 21.1°C and a stress temperature of 37.8°C, were evaluated. The internal temperature and surface temperature of the food products in these containers increased slowly but remained well below the U.S. Food and Drug Administration Food Code requirements. The various containers were similar in their ability to retain coolness. The presence of frozen gel packs dramatically enhanced the cold-holding capacity of the containers. The temperature of foods increased more rapidly when stressed in a heated environment. The containers tested used with the frozen gel packs can keep the surface and internal temperatures of various perishable foods (starting at 4.4°C or less) within the Food Code recommendation of under 21.1°C for 4 h. Cash-and-carry businesses should strongly encourage their retail customers to utilize these containers with frozen gel packs to safely transport perishable foods.

Validation of mathematical models for Salmonella growth in raw ground beef under dynamic temperature conditions representing loss of refrigeration

Temperature is a primary factor in controlling the growth of microorganisms in food. The current U. S. Food and Drug Administration Model Food Code guidelines state that food can be kept out of temperature control for up to 4 h without qualifiers, or up to 6 h, if the food product starts at an initial 41 °F (5 °C) temperature and does not exceed 70 °F (21 °C) at 6 h. This project validates existing ComBase computer models for Salmonella growth under changing temperature conditions modeling scenarios using raw ground beef as a model system. A cocktail of Salmonella serovars isolated from different meat products ( Salmonella Copenhagen, Salmonella Montevideo, Salmonella Typhimurium, Salmonella Saintpaul, and Salmonella Heidelberg) was made rifampin resistant and used for all experiments. Inoculated samples were held in a programmable water bath at 4.4 °C (40 °F) and subjected to linear temperature changes to different final temperatures over various lengths of time and then returned to 4.4 °C (40 °F). Maximum temperatures reached were 15.6, 26.7, or 37.8 °C (60, 80, or 100 °F), and the temperature increases took place over 4, 6, and 8 h, with varying cooling times. Our experiments show that when maximum temperatures were lower (15.6 or 26.7 °C), there was generally good agreement between the ComBase models and experiments: when temperature increases of 15.6 or 26.7 °C occurred over 8 h, experimental data were within 0.13 log CFU of the model predictions. When maximum temperatures were 37 °C, predictive models were fail-safe. Overall bias of the models was 1.11. and accuracy was 2.11. Our experiments show the U.S. Food and Drug Administration Model Food Code guidelines for holding food out of temperature control are quite conservative. Our research also shows that the ComBase models for Salmonella growth are accurate or fail-safe for dynamic temperature conditions as might be observed due to power loss from natural disasters or during transport out of temperature control.