Modeling the effects of temperature and pH on Listeria monocytogenes growth in Mexican-style pork chorizo

Gutiérrez-Chocoza, Mario A.; López-Romero, Julio C.; García-Galaz, Alfonso; González-Ríos, Humberto; Peña-Ramos, Aida; Juneja, Vijay K.; Pérez-Báez, Anna J.; Valenzuela-Melendres, Martín

doi:10.1016/j.afres.2023.100336

Cited by 3 publications

(2 citation statements)

References 17 publications

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“…Listeria monocytogenes is a facultative anaerobe foodborne pathogen found in a wide range of environments, including water, soil, faeces, food processing environments, and food [1]. This pathogen, when ingested, is the causative agent for listeriosis, a very severe foodborne illness with high mortality rate between 20 and 30%, making L. monocytogenes one of the most significant pathogens encountered in food [1,2]. Ready-to-eat (RTE) products (e.g., deli meats, soft cheeses, and seafood) are the main source of listeriosis outbreaks.…”

Section: Introductionmentioning

confidence: 99%

“…Previous RSM studies have shown reliable inferences when testing the influence of ingredients and additives used in RTE food on the growth and inhibition of Listeria spp. [2,33,34]. The optimal application of factors promoting the production of antimicrobials (e.g., bacteriocins and organic acids) and inhibition of pathogens can be used as a tool to improve food safety.…”

Section: Introductionmentioning

confidence: 99%

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The Antilisterial Effect of Latilactobacillus sakei CTC494 in Relation to Dry Fermented Sausage Ingredients and Temperature in Meat Simulation Media

Ferrer-Bustins,

Costa,

Pérez-Rodríguez

et al. 2024

Fermentation

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Listeria monocytogenes, the causative agent of listeriosis, is a relevant pathogen in dry fermented sausages (DFSs), and the application of antilisterial starter cultures is an effective intervention strategy to control the pathogen during DFS production. The effect of factors in relation to DFS formulation and production, NaCl (0–40 g/L), Mn (0.08–0.32 g/L), glucose (0–40 g/L) and temperature (3–37 °C), on the behaviour of L. monocytogenes when cocultured with Latilactobacillus sakei 23K (non-bacteriocinogenic) and CTC494 (bacteriocinogenic) strains was studied through a central composite design in meat simulation media. L. sakei and L. monocytogenes counts, pH, lactic acid production and bacteriocin activity were determined in mono and coculture. The pH decrease and lactic acid production were highly influenced by glucose, while production of sakacin K by L. sakei CTC494 was observed at moderate (10 and 20 °C), but not at the lowest (3 °C) and highest (37 °C), temperatures. Coculture growth had no effect on the acidification and bacteriocin production but inhibited and inactivated L. monocytogenes when L. sakei 23K entered the early stationary phase and when L. sakei CTC494 produced sakacin K. Optimal conditions for achieving a 5-log units reduction of L. monocytogenes were at 20 °C, 20 g/L of NaCl, 0.20 g/L of Mn and 40 g/L of glucose, those highlighting the importance of considering product formulation and fermentation conditions for bioprotective starter cultures application.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

The Antilisterial Effect of Latilactobacillus sakei CTC494 in Relation to Dry Fermented Sausage Ingredients and Temperature in Meat Simulation Media

Ferrer-Bustins,

Costa,

Pérez-Rodríguez

et al. 2024

Fermentation

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Growth of Listeria monocytogenes in fresh vegetables and vegetable salad products: An update on influencing intrinsic and extrinsic factors

Alegbeleye,

Rhee

2024

Comp Rev Food Sci Food Safe

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The ability of foodborne pathogens to grow in food products increases the associated food safety risks. Listeria monocytogenes (Lm) is a highly adaptable pathogen that can survive and grow under a wide range of environmental circumstances, including otherwise inhibitory conditions, such as restrictive cold temperatures. It can also survive long periods under adverse environmental conditions. This review examines the experimental evidence available for the survival and growth of Lm on fresh vegetables and ready‐to‐eat vegetable salads. Published data indicate that, depending on certain intrinsic (e.g., nutrient composition) and extrinsic factors (e.g., storage temperature, packaging atmosphere), Lm can survive on and in a wide variety of vegetables and fresh‐cut minimally processed vegetable salads. Studies have shown that temperature, modified atmosphere packaging, relative humidity, pH, water activity, background microbiota of vegetables, microbial strain peculiarities, and nutrient type and availability can significantly impact the fate of Lm in vegetables and vegetable salads. The influence of these factors can either promote its growth or decline. For example, some studies have shown that background microbiota inhibit the growth of Lm in vegetables and minimally processed vegetable salads, but others have reported a promoting, neutral, or insignificant effect on the growth of Lm. A review of relevant literature also indicated that the impact of most influencing factors is related to or interacts with other intrinsic or extrinsic factors. This literature synthesis contributes to the body of knowledge on possible strategies for improving food safety measures to minimize the risk of Lm‐associated foodborne outbreaks involving vegetables and vegetable salads.

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Predictive Model for Listeria monocytogenes in RTE Meats Using Exclusive Food Matrix Data

Gowda,

Singh,

Lommerse

et al. 2024

Foods

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Post-processing contamination of Listeria monocytogenes has remained a major concern for the safety of ready-to-eat (RTE) meat products that are not reheated before consumption. Mathematical models are rapid and cost-effective tools to predict pathogen behavior, product shelf life, and safety. The objective of this study was to develop and validate a comprehensive model to predict the Listeria growth rate in RTE meat products as a function of temperature, pH, water activity, nitrite, acetic, lactic, and propionic acids. The Listeria growth data in RTE food matrices, including RTE beef, pork, and poultry products (731 data sets), were collected from the literature and databases like ComBase. The growth parameters were estimated using the logistic-with-delay primary model. The good-quality growth rate data (n = 596, R2 > 0.9) were randomly divided into 80% training (n = 480) and 20% testing (n = 116) datasets. The training growth rates were used to develop a secondary gamma model, followed by validation in testing data. The growth model’s performance was evaluated by comparing the predicted and observed growth rates. The goodness-of-fit parameter of the secondary model includes R2 of 0.86 and RMSE of 0.06 (μmax) during the development stage. During validation, the gamma model with interaction included an RMSE of 0.074 (μmax), bias, and accuracy factor of 0.95 and 1.50, respectively. Overall, about 81.03% of the relative errors (RE) of the model’s predictions were within the acceptable simulation zone (RE ± 0.5 log CFU/h). In lag time model validation, predictions were 7% fail-dangerously biased, and the accuracy factor of 2.23 indicated that the lag time prediction is challenging. The model may be used to quantify the Listeria growth in naturally contaminated RTE meats. This model may be helpful in formulations, shelf-life assessment, and decision-making for the safety of RTE meat products.

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Modeling the effects of temperature and pH on Listeria monocytogenes growth in Mexican-style pork chorizo

Cited by 3 publications

References 17 publications

The Antilisterial Effect of Latilactobacillus sakei CTC494 in Relation to Dry Fermented Sausage Ingredients and Temperature in Meat Simulation Media

The Antilisterial Effect of Latilactobacillus sakei CTC494 in Relation to Dry Fermented Sausage Ingredients and Temperature in Meat Simulation Media

Growth of Listeria monocytogenes in fresh vegetables and vegetable salad products: An update on influencing intrinsic and extrinsic factors

Predictive Model for Listeria monocytogenes in RTE Meats Using Exclusive Food Matrix Data

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