Predictive modeling for growth of non- and cold-adapted Listeria monocytogenes on fresh-cut cantaloupe at different storage temperatures

Growth Prediction of the Total Bacterial Count in Freshly Squeezed Strawberry Juice during Cold Storage Using Electronic Nose and Electronic Tongue

The growth models of total bacterial count in freshly squeezed strawberry juice were established by gas and taste sensors in this paper. By selecting the optimal sensors and fusing the response values, the Modified Gompertz, Logistic, Huang and Baranyi models were used to predict and simulate the growth of bacteria. The results showed that the R² values for fitting the growth model of total bacterial count of the sensor S7 (an electronic nose sensor), of sweetness and of the principal components scores were 0.890-0.944, 0.861-0.885 and 0.954-0.964, respectively. The correlation coefficients, or R-values, between models fitted by the response values and total bacterial count ranged from 0.815 to 0.999. A single system of electronic nose (E-nose) or electronic tongue (E-tongue) sensors could be used to predict the total bacterial count in freshly squeezed strawberry juice during cold storage, while the higher rate was gained by the combination of these two systems. The fusion of E-nose and E-tongue had the best fitting-precision in predicting the total bacterial count in freshly squeezed strawberry juice during cold storage. This study proved that it was feasible to predict the growth of bacteria in freshly squeezed strawberry juice using E-nose and E-tongue sensors.

Initial and Final Cell Concentrations Significantly Influence the Maximum Growth Rate of Listeria monocytogenes in Published Literature Data for Whole Intact Fresh Produce

ABSTRACT

Listeria monocytogenes has shown the ability to grow on fresh uncut produce; however, the factors that control growth are not well understood. Peer-reviewed journal articles (n = 29) meeting the inclusion criteria and related to the growth of L. monocytogenes on fresh produce were found through university library databases and Google Scholar searches. Growth models were fit to each of the extracted 130 data sets to estimate log CFU per day rates of growth by using the DMFit tool. Multiple linear stepwise regression models for factors influencing growth rate were developed using R software. Factors included were temperature, nutrient level of inoculation buffer, initial cell concentration, final cell concentration, inoculation method, container permeability, and surface characteristics. The full model produced adjusted R2, Akaike information criterion, and root mean square error values of 0.41, 488, and 1.61, respectively. Stepwise regression resulted in a reduced model with parameters for incubation temperature, inoculation buffer type, initial and final cell concentrations, container characteristics, and produce surface characteristics. Model fit statistics improved slightly in the reduced model. A further reduced three-parameter model included storage temperature and initial and final cell concentrations, with interaction terms. This three-parameter model had adjusted R2, Akaike information criterion, and root mean square error values of 0.66, 417, and 1.24, respectively. Incubation temperature (P = 1.00E-09) initial cell concentration (P = 3.05E-12), and final cell concentration (P = 4.17E-09) all had highly significant effects on maximum growth rate. Our findings show the importance of inoculum concentration and produce microbial carrying capacity on the estimated growth rate and highlight the overall importance that temperature has on growth rate. Future experiments should consider initial inoculum concentration carefully when conducting growth studies for L. monocytogenes on whole produce.

HIGHLIGHTS

Evaluation of microbiological quality and safety of fresh-cut fruit products at retail levels in Korea

The risk of foodborne illnesses caused by pathogens could be increased in fresh-cut fruit products owing to contamination during processing. Therefore, this study was conducted to investigate the microbiological quality and safety of commercial fresh-cut fruit products in Korea. Additionally, the growth of Listeria monocytogenes in selected fresh-cut fruits was evaluated, and their growth curves were analyzed using predictive growth modeling. The mean count of total aerobic bacteria, coliforms, and yeast/mold was 3.67±1.73 log₁₀ CFU/g, 1.54±1.01 log₁₀ CFU/g, and 3.81±1.51 log₁₀ CFU/g, respectively. Escherichia coli, Staphylococcus aureus, Escherichia coli O157:H7, L. monocytogenes, Salmonella spp., and Cyclospora spp. were not detected in any of the tested samples. Only Bacillus cereus was detected in a few samples at the mean level of 1.72±0.13 log₁₀ CFU/g. The growth of L. monocytogenes varied depending on the type of fruit; they grew well in non-acidic fresh-cut fruit products during storage at 10 °C.

Evaluation of the Stress Tolerance of Salmonella with Different Antibiotic Resistance Profiles

Disease caused by antibiotic-resistant Salmonella is a serious clinical problem that poses a great threat to public health. The present study is aimed at assessing differences in bacterial kinetics with different antibiotic resistance profiles under environmental stress and at developing microbial tolerance models in lettuce during storage from 4 to 36°C. The drug-resistance phenotypes of 10 Salmonella Typhimurium (S. Typhimurium) isolates were examined using the broth microdilution method. The results of 10 S. Typhimurium isolates in the suspensions showed that a slow trend towards reduction of drug-sensitive (DS) isolates in relation to the others though without statistical difference. Compared to DS S. Typhimurium SA62, greater bacterial reduction was observed in multidrug-resistant (MDR) S. Typhimurium HZC3 during lettuce storage at 4°C (P < 0.05). It was likely that a cross-response between antibiotic resistance and food-associated stress tolerance. The greater growth in lettuce at 12°C was observed for DS S. Typhimurium SA62 compared to MDR S. Typhimurium HZC3 and was even statistically different (P < 0.05), while no significant difference was observed for bacterial growth between MDR S. Typhimurium HZC3 and DS S. Typhimurium SA62 strains in lettuce storage from 16 to 36°C (P > 0.05). The goodness-of-fit indices indicated the Log-linear primary model provided a satisfactory fit to describe the MDR S. Typhimurium HZC3 and DS S. Typhimurium SA62 survival at 4°C. A square root secondary model could be used to describe the effect of temperature (12, 16, 28, and 36°C) on the growth rates of S. Typhimurium HZC3 (adj - R 2 = 0.91, RMSE = 0.06) and S. Typhimurium SA62 (adj - R 2 = 0.99, RMSE = 0.01) derived from the Huang primary model. It was necessary to pay attention to the tolerance of antibiotic resistant bacteria under environmental stress, and the generated models could provide parts of the input data for microbial risk assessment of Salmonella with different antibiotic resistance profile in lettuce.

Growth Kinetics of Listeria monocytogenes in Cut Produce

Cut produce continues to constitute a significant portion of the fresh fruit and vegetables sold directly to consumers. As such, the safety of these items during storage, handling, and display remains a concern. Cut tomatoes, cut leafy greens, and cut melons, which have been studied in relation to their ability to support pathogen growth, have been specifically identified as needing temperature control for safety. Data are needed on the growth behavior of foodborne pathogens in other types of cut produce items that are commonly offered for retail purchase and are potentially held without temperature control. This study assessed the survival and growth of Listeria monocytogenes in cut produce items that are commonly offered for retail purchase, specifically broccoli, green and red bell peppers, yellow onions, canned green and black olives, fresh green olives, cantaloupe flesh and rind, avocado pulp, cucumbers, and button mushrooms. The survival of L. monocytogenes strains representing serotypes 1/2a, 1/2b, and 4b was determined on the cut produce items for each strain individually at 5, 10, and 25°C for up to 720 h. The modified Baranyi model was used to determine the growth kinetics (the maximum growth rates and maximum population increases) in the L. monocytogenes populations. The products that supported the most rapid growth of L. monocytogenes, considering the fastest growth and resulting population levels, were cantaloupe flesh and avocado pulp. When stored at 25°C, the maximum growth rates for these products were 0.093 to 0.138 log CFU/g/h and 0.130 to 0.193 log CFU/g/h, respectively, depending on the strain. Green olives and broccoli did not support growth at any temperature. These results can be used to inform discussions surrounding whether specific time and temperature storage conditions should be recommended for additional cut produce items.

A Computational Study of Amensalistic Control of Listeria monocytogenes by Lactococcus lactis under Nutrient Rich Conditions in a Chemostat Setting

We study a previously introduced mathematical model of amensalistic control of the foodborne pathogen Listeria monocytogenes by the generally regarded as safe lactic acid bacteria Lactococcus lactis in a chemostat setting under nutrient rich growth conditions. The control agent produces lactic acids and thus affects pH in the environment such that it becomes detrimental to the pathogen while it is much more tolerant to these self-inflicted environmental changes itself. The mathematical model consists of five nonlinear ordinary differential equations for both bacterial species, the concentration of lactic acids, the pH and malate. The model is algebraically too involved to allow a comprehensive, rigorous qualitative analysis. Therefore, we conduct a computational study. Our results imply that depending on the growth characteristics of the medium in which the bacteria are cultured, the pathogen can survive in an intermediate flow regime but will be eradicated for slower flow rates and washed out for higher flow rates.