A mathematical model for predicting growth/no-growth of psychrotrophic C. botulinum in meat products with five variables

Effect of Sodium Nitrite, Nisin and Lactic Acid on the Prevalence and Antibiotic Resistance Patterns of Listeria monocytogenes Naturally Present in Poultry

The impact of treating minced chicken meat with sodium nitrite (SN, 100 ppm), nisin (Ni, 10 ppm) and lactic acid (LA, 3000 ppm) on the levels of some microbial groups indicating hygiene quality were investigated. Specifically, aerobic plate counts and culture-based counts of psychrotrophic microorganisms and enterobacteria were obtained. Additionally, the prevalence of Listeria monocytogenes and the resistance of 245 isolates from this bacterium to 15 antibiotics were documented. L. monocytogenes was isolated using the ISO 11290-1:2017 method and confirmed with polymerase chain reaction using the lmo1030 gene. Antibiotic resistance was established using the disc diffusion technique (EUCAST and CLSI criteria). Twenty-four hours after treatment, the microbial load (log10 cfu/g) was reduced (p < 0.05) relative to controls in those samples treated with LA, with counts of 5.51 ± 1.05 (LA-treated samples) vs. 7.53 ± 1.02 (control) for APC, 5.59 ± 1.14 (LA) vs. 7.13 ± 1.07 (control) for psychrotrophic microorganisms and 2.33 ± 0.51 (LA) vs. 4.23 ± 0.88 (control) for enterobacteria. L. monocytogenes was detected in 70% (control samples), 60% (samples receiving SN), 65% (Ni) and 50% (LA) (p > 0.05) of samples. All strains showed resistance to multiple antimicrobials (between 3 and 12). In all, 225 isolates (91.8%) showed a multi-drug resistant (MDR) phenotype, and one isolate (0.4%) showed an extensively drug-resistant (XDR) phenotype. The mean number of resistances per strain was lower (p < 0.01) in the control samples, at 5.77 ± 1.22, than in those receiving treatment, at 6.39 ± 1.51. It is suggested that the use of food additives might increase the prevalence of resistance to antibiotics in L. monocytogenes, although additional studies would be necessary to verify this finding by analyzing a higher number of samples and different foodstuffs and by increasing the number of antimicrobial compounds and concentrations to be tested.

Quality Evaluation and Mathematical Modelling Approach to Estimate the Growth Parameters of Total Viable Count in Sausages with Different Casings

The growth kinetics for the total viable count (TVC) in sausages with modified hog casings (treated by surfactant solutions and slush salt with lactic acid), natural hog casings and sheep casings as a function of the storage time (up to 50 days) were studied for the first time. The growth of TVC was fitted by the Baranyi model, and the maximum specific growth rate, lag time and initial and final cell populations were estimated via DMFit. The coefficient of determination of the Baranyi model reached 0.94, 0.77 and 0.86 for sausages stuffed in modified hog casings (MHC), control hog casings (CHC) and natural sheep casings (NSC), respectively. The experimental data for the initial populations were 4.69 ± 0.10 log cfu/g for MHC, 4.79 ± 0.10 log cfu/g for CHC and 3.74 ± 0.14 log cfu/g for NSC, whilst the predicted initial cell populations for MHC, CHC and NSC were 4.81 ± 0.20 log cfu/g, 5.19 ± 0.53 log cfu/g and 3.74 ± 0.54 log cfu/g, respectively. Their shelf lives can also be predicted. The results show that the average pH value of MHC samples (6.96 ± 0.01) was significantly lower than that of CHC (7.09 ± 0.01) and NSC (7.05 ± 0.02) samples at day 50 (p < 0.05). Sausages with CHC possessed a significant higher water holding capacity (99.48 ± 0.14%) at d 29 than those with MHC (97.40 ± 0.46%) and NSC (98.55 ± 0.17%) (p < 0.05). On the last day, the average moisture content for samples with NSC (38.30 ± 3.23%) was significantly higher than that for those with MHC (29.38 ± 2.52%) and CHC (29.15 ± 1.16%) (p < 0.05).

Modeling the combined effect of temperature, pH, acetic and lactic acid concentrations on the growth/no growth interface of acid-tolerant Bacillus spores

The application of minimal processing technologies has led to increased spoilage incidents in low-acid pasteurized sauces due to the outgrowth of acid-tolerant spore-forming spoilage bacteria (ATSSB). Controlling the germination and subsequent growth of ATSSB spores is vital to enhance the ambient storage stability of pasteurized sauces. This study developed and validated a set of growth/no growth (G/NG) models for spores of two ATSSB strains (Bacillus velezensis and Bacillus subtilis subsp. subtilis) isolated from pasteurized sauces. The G/NG data at two levels of temperature (22 and 30 °C) were collected in Nutrient Broth (a_w = 0.98 adjusted with NaCl) by a full factorial design with five equidistant levels of pH (4.4-5.6), four concentrations of total acetic acid (0.0-0.3% (w/w)), and four concentrations of total lactic acid (0.00-1.00% (w/w)). The growth, starting from heat-treated (10 min 80 °C) spores, of each strain was assessed under 160 combinations by regular optical density measurements during three months. Twelve replicates were made for each combination. The developed models demonstrate that without organic acids even the lowest pH (4.4) allows a high growth possibility of the ATSSB spores, while acetic and lactic acids exhibit a significant antibacterial activity, which can be enhanced at decreased pH. The growth starting from B. subtilis spores can be inhibited for at least three months with 1.0% (w/w) total lactic acid in the water phase at both temperatures, which was not the case for B. velezensis, while 0.3% acetic acid achieves a full inhibition on both strains at 22 °C. With a combination of 0.3% acetic acid and 0.7% lactic acid, no growth should occur in the investigated range. This research is one of the first studies exploring the feasibility of ambient storage for low-acid pasteurized sauces eliminating preservatives such as benzoic and sorbic acids, and proves the synergistic effect of decreased pH and the presence of acetic and lactic acids on inhibiting bacterial growth from ATSSB spores.

Nitrate Is Nitrate: The Status Quo of Using Nitrate through Vegetable Extracts in Meat Products

Nitrate and nitrites are used to give the characteristic color to cured meat products and to preserve them. According to the scientific knowledge available at the moment, these compounds are approved as food additives based on a detailed ponderation between the potential risks and benefits. The controversy over nitrites has increased with the release of an IARC Monograph suggesting an association between colorectal cancer and dietary nitrite in processed meats. The trend in “clean label” products reinforced the concern of consumers about nitrates and nitrites in meat products. This review aims to explain the role of nitrates and nitrites used in meat products. The potential chemical hazards and health risks linked to the consumption of cured meat products are described. Different strategies aiming to replace synthetic nitrate and nitrite and obtain green-label meat products are summarized, discussing their impact on various potential hazards. In the light of the present knowledge, the use or not of nitrite is highly dependent on the ponderation of two main risks—the eventual formation of nitrosamines or the eventual out-growth of severe pathogens. It is evident that synthetic nitrite and nitrate alternatives must be researched, but always considering the equilibrium that is the safety of a meat product.

Extensive growth and growth boundary model for non-proteolytic Clostridium botulinum - Evaluation and validation with MAP and smoked foods

The growth inhibiting effect of lactic acid bacteria (LAB) on non-proteolytic Clostridium botulinum was studied. LAB had no significant effect on growth of C. botulinum and their effect was not included in the model to be evaluated. An available cardinal parameter growth and growth boundary model for non-proteolytic C. botulinum (Koukou et al., 2021; https://doi.org/10.1016/j.ijfoodmicro.2021.109162) was evaluated using a total of 822 time-to-toxin (TTT) formation data extracted from the scientific literature for seafood, poultry, vegetables and meat products. These data included smoked products and food stored in air, vacuum or modified atmosphere packaging (MAP) with added CO₂. The available extensive model predicted TTT formation without bias (B_f-TTT value = 0.99) and with a reasonable accuracy (A_f-TTT value = 1.76). The model was successfully validated for seafood and poultry products. This study substantially increased the range of applicability of the available growth and growth boundary model for non-proteolytic C. botulinum. The performed evaluation showed this model can be used to predict environmental conditions to prevent growth in seafood and poultry products including smoked fish and MAP foods. It is expected that this validated model will contribute to product development and innovation including new sodium reduced foods.

Effect of Food Matrix Type on Growth Characteristics of and Hemolysin Production by Vibrio alginolyticus

ABSTRACT

The growth of and hemolysin production by two V. alginolyticus strains (HY9901 and ATCC 17749T) at 30°C were investigated in briny tilapia, shrimp, scallop, oyster, pork, chicken, freshwater fish, and egg fried rice. Bacteria were enumerated by plate counting. Hemolysin production was evaluated with blood agar and hemolytic titer tests. The two V. alginolyticus strains had similar growth and hemolysin production patterns in all tested foods. Based on the goodness-of-fit primary model statistics (coefficient of determination, mean square error, bias factor, and accuracy factor), the modified Gompertz model was a better fit than the logistic model to V. alginolyticus growth in foods. Growth kinetic parameters of V. alginolyticus had a higher μmax and shorter λ in the following order: briny tilapia > shrimp > freshwater fish > egg fried rice > scallop > oyster > chicken > pork. V. alginolyticus levels were similar at the stationary phase, with no significant growth difference between raw and cooked foods. Significantly higher thermostable direct hemolysin activity (P < 0.05) was found for V. alginolyticus in the following order: briny tilapia > freshwater fish > shrimp > chicken > egg fried rice > scallop > oyster > pork. However, the hemolytic titer was not consistent with the thermostable direct hemolysin activity and was significantly higher (P < 0.05) in the following order: briny tilapia > egg fried rice > shrimp > freshwater fish > chicken > scallop > oyster > pork. Contrary to current belief, V. alginolyticus produced more hemolysin in some nonseafoods (freshwater fish, egg fried rice, and chicken) than in scallops or oysters. This report is the first on the growth and toxicity of V. alginolyticus in different food matrices and confirms that some nonseafoods can be contaminated with pathogenic V. alginolyticus. These results should increase awareness of nonseafood safety issues and improve the accuracy of V. alginolyticus risk assessments.

HIGHLIGHTS

Nitrite reduction in fermented meat products and its impact on aroma

Fermented meat products are important not only for their sensory characteristics, nutrient content and cultural heritage, but also for their stability and convenience. The aroma of fermented meat products is unique and its formation mechanisms are not completely understood; however, the presence of nitrite and nitrate is essential for the development of cured aroma. The use of nitrite and nitrate as curing agents in meat products is based on its preservation activity. Even though their presence has been associated with several risks due to the formation of nitrosamines, their use is guarantee due to their antimicrobial action against Clostridium botulinum. Recent trends and recommendations by international associations are directed to use nitrite but at the minimum concentration necessary to provide the antimicrobial activity against Clostridium botulinum. This chapter discuss the actual limits of nitrite and nitrite content and their role as curing agents in meat products with special impact on dry fermented products. Regulatory considerations, antimicrobial mechanisms and actual trends regarding nitrite reduction and its effect on sensory and aroma properties are also considered.

Cardinal parameter growth and growth boundary model for non-proteolytic Clostridium botulinum - Effect of eight environmental factors

A new cardinal parameter growth and growth boundary model for non-proteolytic C. botulinum was developed and validated for fresh and lightly preserved seafood and poultry products. 523 growth rates in broth were used to determine cardinal parameter values and terms for temperature, pH, NaCl/water activity, acetic, benzoic, citric, lactic and sorbic acids. The new growth and growth boundary model included the inhibiting interactive effect between these factors and it was calibrated using growth curves from 10 challenge tests with unprocessed seafood. For model evaluation, 40 challenge tests with well characterized fresh and lightly preserved seafood were performed. Comparison of these observed growth curves and growth rates (μ_max-values) predicted by the new model resulted in a bias factor (B_f) of 1.12 and an accuracy factor (A_f) of 1.40. Furthermore, the new model was evaluated with 94 growth rates and 432 time to toxin formation data extracted from the scientific literature for seafood, poultry, meat, pasta and prepared meals. These data included responses for 36 different toxigenic strains of non-proteolytic C. botulinum. The obtained B_f-/A_f-values were 0.97/2.04 for μ_max-values and 0.96/1.80 for time to toxin formation. The model correctly predicted 93.8% of the growth responses with 5.6% being fail-safe and <1% fail-dangerous. A cocktail of four non-toxin producing Clostridium spp. isolates was used to develop the new model and these isolates had more than 99.8% 16S rRNA gene similarity to non-proteolytic C. botulinum (Group II). The high number of environmental factors included in the new model makes it a flexible tool to facilitate development or reformulation of seafood and poultry products that do not support the growth of non-proteolytic C. botulinum. Further, evaluation of the new model with well characterized products is desirable particularly for meat, vegetables, pasta and prepared meals as well as for dairy products that was not included in the present study.

Evaluation of storage methods of beef by microbiological and chemical indicators

Meat and meat products are a major part of a person's ration. However, due to their high nutritional value, they are a favorable environment for the development of microorganisms and require refrigerated storage. The purpose of this work was to evaluate the storage methods for refrigerated and frozen beef by microbiological and chemical parameters and to suggest criteria for evaluating beef by the content of psychrotrophic microorganisms. It was found out that the storage of beef meat with an initial mesophilic bacterial content of about 4.88 log CFU.cm-2 of surface and psychrotrophic bacteria 3.79 log CFU.cm-2 at temperature 0 °C is only possible for 8 days, further, the microbiological indices exceed the acceptable standards. Investigation of the dynamics of microflora reproduction during the storage of beef in the frozen state at temperature -2 to -3 °C for 20 days established a decrease in 1.3 times the number of mesophilic bacteria in 10 days of storage. At the same time, the number of psychrotrophic microorganisms during this storage time was increased in 4.5 times, and 20 days in 7.9 times and amounted to 5.3 log CFU.cm-2 of surface area. This indicates that the storage of meat in the frozen state inhibits or completely stops the development of mesophilic microorganisms for 20 days. It was found out that storing of beef in the cooled state at a temperature of 0 ±0.5 °C for more than eight days is impractical, as its biochemical indices are worsening and signs of spoilage are appearing. At the same time, storing of beef in the frozen state at a temperature of -2 to -3 °C for 20 days does not cause such significant biochemical changes as in beef stored in the cooled state at a temperature of 0 ±0.5 °C for 16 days. Therefore, we have experimentally substantiated the quantitative indicators of the content of psychrotrophic microorganisms on the surface of beef intended for storage in a cooled or frozen state. The proposed microbiological criteria will improve the safety of beef.

Staphtox predictor - A dynamic mathematical model to predict formation of Staphylococcus enterotoxin during heating and fermentation of meat products

Existing growth models for S. aureus predict growth in relation to temperature, a_w/NaCl and pH, and the assessment of probable Staphylococcus enterotoxin (SE) formation is based solely on the number of S. aureus. However, during the production of meat products such as fermented sausages and semi-processed hams, growth of S. aureus is a critical control point in HACCP plans. There is a need to develop a model that evaluates the safety of the product regarding SE formation in relation to the product composition, changes in pH or temperature during the processing and the number of S. aureus in the final product. The objective of the present work is to develop a mathematical model that predicts both the increase in the number of S. aureus and whether SE formation is possible in different meat product processes. A total of 78 experiments were carried out in a meat model system. The experiments covered a range of different temperatures (10-40 °C), pH (4.6-6.0), water phase salt (WPS) (2.2-5.6%) and Sodium nitrite concentrations (0-150 ppm). The meat model system was inoculated with approximately 10³ CFU/g of a multi-strain cocktail and incubated at the different temperatures. The cocktail consisted of three strains of S. aureus producing the Staphylococcus enterotoxins A to D (SEA to SED) and a methicillin-resistant strain producing SEG, SEI, SEM, SEN, SEO and SEU. Enumeration of S. aureus was performed several times during the incubation, SE was extracted from samples with >5 log CFU/g, and the SEA-E content was analysed by an ELISA method. Maximum growth rates and lag times calculated from microbiological data, together with temperature, pH, WPS and Sodium nitrite, were used to develop a SE and a growth model. The growth model was developed by training a neural network and the SE model based on logistic regression. The SE and growth models were validated on separate data sets (N = 200 SE model, N = 63 growth model) including both dynamic and static conditions. The SE model predicted all occurrences of toxin formation in the validation data sets. The growth model is a fail-safe model and the prediction errors are comparable to laboratory reproducibility. In conclusion, the models are applicable for predicting the increase in S. aureus and for evaluating if SE formation is likely during processing of meat products. The models are available to producers and other interested parties at www.dmripredict.dk.

Mathematical modelling of growth of Listeria monocytogenes in raw chilled pork

The aim of this study was to analyse the growth kinetics of Listeria monocytogenes in naturally contaminated chilled pork. A cocktail of 26 meat-borne L. monocytogenes was inoculated to raw or sterile chilled pork to observe its growth at 4, 10, 16, 22 and 28°C respectively. The growth data were fitted by the Baranyi model and Ratkowsky square-root model. Results showed that the Baranyi model and Ratkowsky square-root model could describe the growth characteristics of L. monocytogenes at different temperatures reasonably well in raw chilled pork (1·0 ≤ Bf ≤ Af ≤ 1·1). Compared with the growth of L. monocytogenes in sterile chilled pork, the background microflora had no impact on the growth parameters of L. monocytogenes, except for the lag phase at low temperature storage. The microbial predictive models developed in this study can be used to predict the growth of L. monocytogenes during natural spoilage, and construct quantitative risk assessments in chilled pork.

SIGNIFICANCE AND IMPACT OF THE STUDY

This study simulated the actual growth of Listeria monocytogenes in chilled pork to the maximum extent, and described its growth characteristics of L. monocytogenes during natural spoilage. This study showed that the background microflora had no impact on the growth parameters of L. monocytogenes, except for the lag phase at low temperature storage. The models developed in this study can be used to predict the growth of L. monocytogenes during refrigerated storage.

Modelling of multi-nutrient interactions in growth of the dinoflagellate microalga Protoceratium reticulatum using artificial neural networks

This study examines the use of artificial neural networks as predictive tools for the growth of the dinoflagellate microalga Protoceratium reticulatum. Feed-forward back-propagation neural networks (FBN), using Levenberg-Marquardt back-propagation or Bayesian regularization as training functions, offered the best results in terms of representing the nonlinear interactions among all nutrients in a culture medium containing 26 different components. A FBN configuration of 26-14-1 layers was selected. The FBN model was trained using more than 500 culture experiments on a shake flask scale. Garson's algorithm provided a valuable means of evaluating the relative importance of nutrients in terms of microalgal growth. Microelements and vitamins had a significant importance (approximately 70%) in relation to macronutrients (nearly 25%), despite their concentrations in the culture medium being various orders of magnitude smaller. The approach presented here may be useful for modelling multi-nutrient interactions in photobioreactors.