Antimicrobial effect of nisin in processed cheese - Quantification of residual nisin by LC-MS/MS and development of new growth and growth boundary model for Listeria monocytogenes

Martinez-Rios, Veronica; Pedersen, Michael; Pedrazzi, Monica; Gkogka, Elissavet; Smedsgaard, Jørn; Dalgaard, Paw

doi:10.1016/j.ijfoodmicro.2020.108952

Cited by 16 publications

(14 citation statements)

References 42 publications

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“…Inactivation of L. monocytogenes increases by increasing the sorbic acid concentration from 0 to 1000 ppm in the water phase in Cottage cheese [73]. Increasing concentrations of acetic (568-3483 ppm) and citric (518-38,282 ppm) acids have also been shown to reduce the growth potential of the pathogen on processed cheese [5,96]. The mechanisms of growth suppression by these acids seem to be similar to those of lactic acid.…”

Section: Organic Acids and Saltsmentioning

confidence: 94%

“…Increasing nisin residual concentrations from 0.56 to 5.28 ppm extended L. monocytogenes lag times in processed cheeses, at temperatures lower than 15 • C [96]. The antimicrobial efficacy of nisin has been shown to be higher at higher pH values and at lower temperatures [95,96]. Moreover, increasing nisin concentrations from 0 to 240 ppm, reduced the potassium sorbate and sodium chloride (NaCl) concentrations required to achieve the same probability of growth of C. sporogenes in a processed cheese analogue [97].…”

Section: Starter Cultures and Their Bacteriocinsmentioning

confidence: 95%

“…The mechanisms of action of bacteriocins include the increase in permeability of the membranes of microbial cells, weakening of cell walls, collapse of proton motive force, which lead to the leakage of intracellular substances and result in bacterial inactivation [92,93]. Increasing nisin residual concentrations from 0.56 to 5.28 ppm extended L. monocytogenes lag times in processed cheeses, at temperatures lower than 15 • C [96]. The antimicrobial efficacy of nisin has been shown to be higher at higher pH values and at lower temperatures [95,96].…”

Section: Starter Cultures and Their Bacteriocinsmentioning

confidence: 99%

“…This study highlights the important role of salts against spore-forming bacteria. Moreover, the increase of phosphates salt concentrations reduced the growth of L. monocytogenes in a spreadable processed cheese [5,96]. The presence of salts reduces the a w of cheeses, which, therefore, may not be considered as an isolated entity.…”

Section: Organic Acids and Saltsmentioning

confidence: 99%

“…Although fitting a primary model followed by fitting a secondary model using the parameters estimated through primary modeling, i.e., two-step modeling approach, has been extensively applied in the context of cheese production and storage, different approaches have also been performed and will be discussed in the following sections. A comparison between the one-step procedure with the classical two-step procedure was performed by Martinez-Rios et al [96]. In the one-step procedure the parameters of both primary and secondary models are estimated through one global regression.…”

Section: Models Of Microbial Behavior During Cheese Production and Storagementioning

confidence: 99%

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From Cheese-Making to Consumption: Exploring the Microbial Safety of Cheeses through Predictive Microbiology Models

Possas

Bonilla-Luque

Valero

2021

Foods

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Cheeses are traditional products widely consumed throughout the world that have been frequently implicated in foodborne outbreaks. Predictive microbiology models are relevant tools to estimate microbial behavior in these products. The objective of this study was to conduct a review on the available modeling approaches developed in cheeses, and to identify the main microbial targets of concern and the factors affecting microbial behavior in these products. Listeria monocytogenes has been identified as the main hazard evaluated in modelling studies. The pH, aw, lactic acid concentration and temperature have been the main factors contemplated as independent variables in models. Other aspects such as the use of raw or pasteurized milk, starter cultures, and factors inherent to the contaminating pathogen have also been evaluated. In general, depending on the production process, storage conditions, and physicochemical characteristics, microorganisms can grow or die-off in cheeses. The classical two-step modeling has been the most common approach performed to develop predictive models. Other modeling approaches, including microbial interaction, growth boundary, response surface methodology, and neural networks, have also been performed. Validated models have been integrated into user-friendly software tools to be used to obtain estimates of microbial behavior in a quick and easy manner. Future studies should investigate the fate of other target bacterial pathogens, such as spore-forming bacteria, and the dynamic character of the production process of cheeses, among other aspects. The information compiled in this study helps to deepen the knowledge on the predictive microbiology field in the context of cheese production and storage.

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Section: Organic Acids and Saltsmentioning

confidence: 94%