Modelling the effect of pH and pectin concentration on the PEF inactivation of Salmonella enterica serovar Typhimurium by using the Monte Carlo simulation

Advances in pulsed electric stimuli as a physical method for treating liquid foods

There is a need for alternative technologies that can deliver safe and nutritious foods at lower costs as compared to conventional processes. Pulsed electric field (PEF) technology has been utilised for a plethora of different applications in the life and physical sciences, such as gene/drug delivery in medicine and extraction of bioactive compounds in food science and technology. PEF technology for treating liquid foods involves engineering principles to develop the equipment, and quantitative biochemistry and microbiology techniques to validate the process. There are numerous challenges to address for its application in liquid foods such as the 5-log pathogen reduction target in food safety, maintaining the food quality, and scale up of this physical approach for industrial integration. Here, we present the engineering principles associated with pulsed electric fields, related inactivation models of microorganisms, electroporation and electropermeabilization theory, to increase the quality and safety of liquid foods; including water, milk, beer, wine, fruit juices, cider, and liquid eggs. Ultimately, we discuss the outlook of the field and emphasise research gaps.

Development of predictive models evaluating the spoilage-delaying effect of a bioprotective culture on different yeast species in yogurt

Yeast spoilage of fermented dairy products causes challenges for the dairy industry, including economic losses due to wasted product. Food cultures with bioprotective effects are becoming more widely used to help ensure product quality throughout product shelf life. To assist the dairy industry when evaluating product quality throughout shelf life and the effect of bioprotective cultures, we aimed to build stochastic models that provide reliable predictions of yeast spoilage in yogurt with and without bioprotective culture. Growth characterizations of Debaryomyces hansenii, Yarrowia lipolytica, Saccharomyces cerevisiae, and Kluyveromyces marxianus at storage temperatures of 7, 12, and 16°C during a 30-d storage period were conducted in yogurt with and without a bioprotective culture containing Lacticaseibacillus rhamnosus strains. The kinetic growth parameters were calculated using the Buchanan growth model, and these parameters were used as baseline values in Monte Carlo models to translate the yeast growth into spoilage levels. The models were developed using 100,000 simulations and they predicted yeast spoilage levels in yogurt by the 4 yeast types. Each modeled yogurt batch was set to be contaminated with yeast at a concentration drawn from a normal distribution with a mean of 1 log₁₀ cfu/mL and standard deviation of 1 log₁₀ cfu/mL and stored for 30 d at a temperature drawn from a normal distribution with a mean of 6.1°C and a standard deviation of 2.8°C. Considering a spoilage level of 5 log₁₀ cfu/mL, the predicted number of spoiled samples was reduced 3-fold during the first 10 d and by 2-fold at the end of shelf life when a bioprotective culture was added to the yogurt. The models were evaluated by sensitivity analyses, where the main effect factors were maximum yeast population, storage temperature, and yeast strain. The models were validated by comparing the model output to actual observed spoilage data from a European dairy using the bioprotective culture. When the model prediction, based on a mixture of the 4 specific yeast strains, was compared with spoilage data from the European dairy, the observed effect of bioprotective cultures was considerably higher than predicted, potentially influenced by the presence of contaminating strains more sensitive to a bioprotective culture than those characterized here. The developed Monte Carlo models can predict yeast spoilage levels in yogurt at specific production settings and how this may be affected by various parameters and addition of bioprotective cultures.

Modeling the Reduction of Salmonella spp. on Chicken Breasts and Wingettes during Scalding for QMRA of the Poultry Supply Chain in China

The objective of this study was to develop predictive models for describing the inoculated Salmonella reductions on chicken during the scalding process in China. Salmonella reductions on chicken breasts at a 100 s treatment were 1.12 ± 0.07, 1.38 ± 0.01, and 2.17 ± 0.11 log CFU/g at scalding temperatures of 50, 60 and 70 °C, respectively. For chicken wingettes, 0.87 ± 0.02, 0.99 ± 0.14 and 1.11 ± 0.17 log CFU/g reductions were obtained at 50, 60 and 70 °C after the 100 s treatment, respectively. Greater bacterial reductions were observed on chicken breasts than on chicken wingettes (p < 0.05). A logistic (−1.12, 0.06) distribution could describe the bacterial reductions on chicken breasts at 50–60 °C. Weibull, exponential and log-linear models were compared for describing the bacterial reduction on chicken breasts at 70 °C and the Weibull model showed the best fit as indicated by the pseudo-R², root mean square error (RMSE) and standard error of prediction (SEP) values. For chicken wingettes, a logistic (−0.95, 0.07) distribution could be used to describe the bacterial reduction at 50–70 °C. The developed predictive models could provide parts of the input data for microbial risk assessment of the poultry supply chain in China.

The effects of orange juice clarification on the physiology of Escherichia coli; growth-based and flow cytometric analysis

Orange juice (OJ) is a food product available in various forms which can be processed to a greater or lesser extent. Minimally-processed OJ has a high consumer perception but presents a potential microbiological risk due to acid-tolerant bacteria. Clarification of OJ (such as removal of cloud) is a common processing step in many OJ products. However, many of the antimicrobial components of OJ such as essential oils are present in the cloud fraction. Here, the effect of clarification by filtration on the viability and physiology of Escherichia coli K-12 was tested using total viable count (TVC) and flow cytometric (FCM) analysis. The latter technique was also used to monitor intracellular pH during incubation in OJ. Removal of the OJ cloud fraction was shown to have dramatic effects on bacterial viability and physiology during storage at a range of incubation temperatures. For instance, at 4 °C, a significantly lower number of healthy cells and a significantly higher number of injured cells were observed in 0.22 μm-filtered OJ at 24h post-inoculation, compared to filtered OJ samples containing particles between 0.22 μm and 11 μm in size. Similarly, there was a significant difference between the number of healthy bacteria in the 0.7 μm-filtered OJ and both 0.22 μm-filtered and 1.2 μm-filtered OJ after 24 hour incubation at 22.5 °C. This indicated that OJ cloud between 0.7 μm and 0.22 μm in size might have an adverse effect on the viability of E. coli K-12. Furthermore, FCM allowed the rapid analysis of bacterial physiology without the requirement for growth on agar plates, and revealed the extent of the viable but non-culturable (VBNC) population. For example, at 4 °C, while the FCM viable count did not substantially decrease until 48 h, decreases in TVC were observed between 0 and 48 hour incubation, due to a subset of injured bacteria entering the VBNC state, hence being unable to grow on agar plates. This study highlights the application of FCM in monitoring bacterial physiology in foods, and potential effects of OJ clarification on bacterial physiology.

Selection of process conditions by risk assessment for apple juice pasteurization by UV-heat treatments at moderate temperatures

The effect of bactericidal UV-C treatments (254 nm) on Escherichia coli O157:H7 suspended in apple juice increased synergistically with temperature up to a threshold value. The optimum UV-C treatment temperature was 55 °C, yielding a 58.9% synergistic lethal effect. Under these treatment conditions, the UV-heat (UV-H55 °C) lethal variability achieving 5-log reductions had a logistic distribution (α = 37.92, β = 1.10). Using this distribution, UV-H55 °C doses to achieve the required juice safety goal with 95, 99, and 99.9% confidence were 41.17, 42.97, and 46.00 J/ml, respectively, i.e., doses higher than the 37.58 J/ml estimated by a deterministic procedure. The public health impact of these results is that the larger UV-H55 °C dose required for achieving 5-log reductions with 95, 99, and 99.9% confidence would reduce the probability of hemolytic uremic syndrome in children by 76.3, 88.6, and 96.9%, respectively. This study illustrates the importance of including the effect of data variability when selecting operational parameters for novel and conventional preservation processes to achieve high food safety standards with the desired confidence level.