P. M. Davidson

Inactivation of Escherichia coli K-12 in Apple Juice Using Combination of High-Pressure Homogenization and Chitosan

Apple juice and apple cider were inoculated with Escherichia coli K-12 and processed using a high-pressure homogenizer to study bacterial inactivation. Seven levels of pressure ranging from 50 to 350 MPa were used in the high-pressure homogenizer. Two types of chitosan (regular and water soluble) with 2 levels of concentration 0.01% and 0.1% were investigated for synergistic effect with high-pressure homogenization for the bacterial inactivation. E. coli K-12 inactivation was evaluated as a function of homogenizing pressure at different concentration of 2 types of chitosan in apple juice and cider. High-pressure homogenization (HPH) induced significant inactivation in the range of 100 to 200 MPa, while thermal inactivation was the primary factor for the bacterial inactivation above 250 MPa. Significant (P < 0.05) 2-way interactions involving pressure and type of substrate or pressure and chitosan concentration were observed during the study. The homogenization pressure and the incremental quantity of chitosan (both types) acted synergistically with the pressure to give higher inactivation. Significantly (P < 0.05) higher inactivation was observed in apple juice than apple cider at same homogenizing pressure. No effect of type of chitosan was observed on the bacterial inactivation.

Microbiological Analysis of Food Contact Surfaces in Child Care Centers

ABSTRACT A study of six child care centers was conducted to assess the microbiological quality of three food contact surfaces (one food serving surface and two food preparation surfaces) and one non-food contact surface (diaper changing surface) to determine the effectiveness of cleaning and sanitization procedures within the facilities. Aerobic plate counts (APCs) and Escherichia coli/coliform counts of 50-cm2 areas on all surfaces were determined using standard microbiological swabbing methods. Samples were taken three times a day (preopening, lunchtime, and following final cleanup) twice per month for 8 months in each child care center (n = 288 sampling times). Mean log APCs over the survey period were 1.32, 1.71, 1.34, 1.96, 1.50, and 1.81 log CFU/50 cm2 for the six centers. Mean log coliform counts were 0.15, 0.40, 0.33, 1.41, 0.28, and 1.12 CFU/50 cm2 for the same centers. Coliforms were detected in 283 of 1,149 (24.7%) samples, with counts ranging from 1 to 2,000 CFU/50 cm2, while E. coli was detected in 18 of 1,149 (1.6%) samples, with counts ranging from 1 to 35 CFU/50 cm2. The findings of this study demonstrated that the extent of bacterial contamination was dependent on the center, time of day, and the area sampled. While no direct correlation between contamination and illness can be made, given the high risk of food-borne illness associated with children, microbial contamination of food contact or non-food contact surfaces is an aspect of food safety that requires more attention. Emphasis on training and the development of modified standard sanitation operating procedures for child care centers are needed to reduce potential hazards.

Relationships between Ultimate pH and Microbial, Chemical, and Physical Characteristics of Vacuum‐Packaged Pork Loins

This study evaluated the effect of ultimate pH (pHu) of pork on shelf life based upon microbial growth, drip loss, and oxidative rancidity (2-thiobarbituric acid [TBA] procedure) in vacuum-packaged loins stored at 4 degrees C. Glucose and lactate concentrations of the pork loins were also measured. Thirty-six pork loins (pH = 5.56 to 6.57) were collected at a commercial slaughter facility 1-d postslaughter. All pigs were from the same genetic line. Loins were grouped by pH (group: pH range): A: 5.55 to 5.70, B: 5.71 to 5.85, C: 5.86 to 6.00, D: 6.01 to 6.15, and E: > 6.16. They were analyzed at days 0, 6, 14, 24, and 34. For aerobic plate counts, groups A and B were significantly lower than C through E, while psychrotrophic or Enterobacteriaceae counts of groups A and A through C were significantly lower than groups B through E and D and E, respectively. Lactic acid bacteria counts were not significantly influenced by pHu. Group A had higher glucose concentrations than groups C through E and higher lactate concentrations than groups D through E on most sampling days. Group A had a higher TBA value than group E at days 0 and 34. Group A displayed greater drip loss than groups D and E at day 6 and groups B through D on days 24 and 34. Based on the microbial and drip loss results, a pork loin pHu of 5.8 to 5.9 appears to be optimum to provide a vacuum-packaged shelf life of at least 24 d with minimum drip loss.

Thermal Inactivation of Escherichia coli O157:H7 When Grown Statically or Continuously in a Chemostat

The objective of this study was to determine if survivor curves for heat-inactivated Escherichia coli O157:H7 were affected by the physiological state of the cells relative to growth conditions and pH of the heating menstruum. A comparison was made between the log-linear model and non-log-linear Weibull approach. Cells were grown statically in aerobic culture tubes or in an aerobic chemostat in tryptic soy broth (pH 7.2). The heating menstruum was unbuffered peptone or phosphate buffer (pH 7.0). Thermal inactivation was carried out at 58, 59, 60, and 61°C, and recovery was on a nonselective medium. Longer inactivation times for statically grown cells indicated potential stress adaptation. This was more prevalent at 58°C. Shape response was also significantly different, with statically grown cells exhibiting decreasing thermal resistance over time and chemostat cells showing the opposite effect. Buffering the heating menstruum to ca. pH 7 resulted in inactivation curves that showed less variability or scatter of data points. Time to specific log reduction values (t(d)) for the Weibull model were conservative relative to the log-linear model depending upon the stage of reduction. The Weibull model offered the most accurate fit of the data in all cases, especially considering the log-linear model is equivalent to the Weibull model with a fixed shape factor of 1. The determination of z-value for the log-linear model showed a strong correlation between log D-value and process temperature. Correlations for the Weibull model parameters (log δ and log p) versus process temperature were not statistically significant.

Escherichia coli thermal inactivation relative to physiological state.

Studies have explored the use of various nonlinear regression techniques to better describe shoulder and/or tailing effects in survivor curves. Researchers have compiled and developed a number of diverse models for describing microbial inactivation and presented goodness of fit analysis to compare them. However, varying physiological states of microorganisms could affect the measured response in a particular population and add uncertainty to results from predictive models. The objective of this study was to determine if the shape and magnitude of the survivor curve are possibly the result of the physiological state, relative to growth conditions, of microbial cells at the time of heat exposure. Inactivation tests were performed using Escherichia coli strain K-12 in triplicate for three growth conditions: statically grown cells, chemostat-grown cells, and chemostat-grown cells with buffered (pH 6.5) feed media. Chemostat cells were significantly less heat resistant than the static or buffered chemostat cells at 58 degrees C. Regression analysis was performed using the GInaFiT freeware tool for Microsoft Excel. A nonlinear Weibull model, capable of fitting tailing effects, was effective for describing both the static and buffered chemostat cells. The log-linear response best described inactivation of the nonbuffered chemostat cells. Results showed differences in the inactivation response of microbial cells depending on their physiological state. The use of any model should take into consideration the proper use of regression tools for accuracy and include a comprehensive understanding of the growth and inactivation conditions used to generate thermal inactivation data.