Microbial decontamination assisted by ultrasound-based processing technologies in food and model systems: A review.

Ultrasound (US) technology is recognized as one of the emerging technologies that arise from the current trends for improving nutritional and organoleptic properties while providing food safety. However, when applying the US alone, higher power and longer treatment times than conventional thermal treatments are needed to achieve a comparable level of microbial inactivation. This results in risks, damaging food products' composition, structure, or sensory properties, and can lead to higher processing costs. Therefore, the US has often been investigated in combination with other approaches, like heating at mild temperatures and/or treatments at elevated pressure, use of antimicrobial substances, or other emerging technologies (e.g., high-pressure processing, pulsed electric fields, nonthermal plasma, or microwaves). A combination of US with different approaches has been reported to be less energy and time consuming. This manuscript aims to provide a broad review of the microbial inactivation efficacy of US technology in different food matrices and model systems. In particular, emphasis is given to the US in combination with the two most industrially viable physical processes, that is, heating at mild temperatures and/or treatments at elevated pressure, resulting in techniques known as thermosonication, manosonication, and manothermosonication. The available literature is reviewed, and critically discussed, and potential research gaps are identified. Additionally, discussions on the US's inactivation mechanisms and lethal effects are included. Finally, mathematical modeling approaches of microbial inactivation kinetics due to US-based processing technologies are also outlined. Overall, this review focuses only on the uses of the US and its combinations with other processes relevant to microbial food decontamination.

Clostridium sporogenes as surrogate for proteolytic C. botulinum - Development and validation of extensive growth and growth-boundary model.

An extensive cardinal parameter growth and growth boundary model for C. sporogenes, as a surrogate for proteolytic C. botulinum, was developed to include the inhibitory effect of 11 environmental factors. 626 maximum specific growth rates (µmax) in broth were generated to determine cardinal parameter values for the growth inhibiting effect of temperature, pH, NaCl/water activity (aw), organic acids (acetic, benzoic, citric, lactic, sorbic) and phosphate melting salts (ortho-, di- and tri-phosphates). µmax-values for C. sporogenes growing in well-characterized processed cheeses were used for product calibration (n = 10) and for product evaluation of the developed broth-model (n = 29). 112 growth/no-growth responses and including 104 µmax-values from the scientific literature for 58 different isolates of proteolytic and toxigenic C. botulinum (Group I) were used for further model evaluation. The developed model had less bias and a higher percentage of correct predictions than available models and was acceptable for processed cheese and good for meat products. The new and extensive model can predict combinations of environmental factors that prevent growth of C. sporogenes and of proteolytic C. botulinum. These predictions are expected to facilitate development or re-formulation of processed cheese and meat products where growth is prevented.

Guidance on validation of lethal control measures for foodborne pathogens in foods.

Food manufacturers are required to obtain scientific and technical evidence that a control measure or combination of control measures is capable of reducing a significant hazard to an acceptable level that does not pose a public health risk under normal conditions of distribution and storage. A validation study provides evidence that a control measure is capable of controlling the identified hazard under a worst-case scenario for process and product parameters tested. It also defines the critical parameters that must be controlled, monitored, and verified during processing. This review document is intended as guidance for the food industry to support appropriate validation studies, and aims to limit methodological discrepancies in validation studies that can occur among food safety professionals, consultants, and third-party laboratories. The document describes product and process factors that are essential when designing a validation study, and gives selection criteria for identifying an appropriate target pathogen or surrogate organism for a food product and process validation. Guidance is provided for approaches to evaluate available microbiological data for the target pathogen or surrogate organism in the product type of interest that can serve as part of the weight of evidence to support a validation study. The document intends to help food manufacturers, processors, and food safety professionals to better understand, plan, and perform validation studies by offering an overview of the choices and key technical elements of a validation plan, the necessary preparations including assembling the validation team and establishing prerequisite programs, and the elements of a validation report.

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.

This study tested the hypothesis that growth of Listeria monocytogenes in processed cheese with added nisin can be predicted from residual nisin A concentrations in the final product after processing. A LC-MS/MS method and a bioassay were studied to quantify residual nisin A concentrations and a growth and growth boundary model was developed to predict the antilisterial effect in processed cheese. 278 growth rates were determined in broth for 11 L. monocytogenes isolates and used to determine 13 minimum inhibitory concentration (MIC) values for nisin between pH 5.5 and 6.5. To supplement these data, 67 MIC-values at different pH-values were collected from the scientific literature. A MIC-term was developed to describe the effect of pH on nisin MIC-values. An available growth and growth boundary model (doi: https://doi.org/10.1016/j.fm.2019.103255) was expanded with the new MIC-term for nisin to predict growth in processed cheese. To generate data for model evaluation and further model development, challenge tests with a total of 45 growth curves, were performed using processed cheese. Cheeses were formulated with 11.2 or 12.0 ppm of nisin A and heat treated to obtain residual nisin A concentrations ranging from 0.56 to 5.28 ppm. Below 15 °C, nisin resulted in extended lag times. A global regression approach was used to fit all growth curves determined in challenge tests. This was obtained by combining the secondary growth and growth boundary model including the new term for the inhibiting effect of nisin on µmax with the primary logistic growth model with delay. This model appropriately described the growth inhibiting effect of residual nisin A and showed that relative lag times depended on storage temperatures. With residual nisin A concentrations, other product characteristics and storage temperature as input the new model correctly predicted all observed growth and no-growth responses for L. monocytogenes. This model can support development of nisin A containing recipes for processed cheese that prevent growth of L. monocytogenes. Residual nisin A concentrations in processed cheese were accurately quantified by the developed LC-MS/MS method with recoveries of 83 to 110% and limits of detection and quantification being 0.04 and 0.13 ppm, respectively. The tested bioassay was less precise and nisin A recoveries varied for 53% to 94%.

Predicting growth of Listeria monocytogenes at dynamic conditions during manufacturing, ripening and storage of cheeses - Evaluation and application of models.

Mathematical models were evaluated to predict growth of L. monocytogenes in mould/smear-ripened cheeses with measured dynamic changes in product characteristics and storage conditions. To generate data for model evaluation three challenge tests were performed with mould-ripened cheeses produced by using milk inoculated with L. monocytogenes. Growth of L. monocytogenes and lactic acid bacteria (LAB) in the rind and in the core of cheeses were quantified together with changes in product characteristics over time (temperature, pH, NaCl/aw, lactic- and acetic acid concentrations). The performance of nine available L. monocytogenes growth models was evaluated using growth responses from the present study and from literature together with the determined or reported dynamic product characteristics and storage conditions (46 kinetics). The acceptable simulation zone (ASZ) method was used to assess model performance. A reduced version of the Martinez-Rios et al. (2019) model (https://doi.org/10.3389/fmicb.2019.01510) and the model of Østergaard et al. (2014) (https://doi.org/10.1016/j.ijfoodmicro.2014.07.012) had acceptable performance with a ASZ-score of 71-70% for L. monocytogenes growth in mould/smear-ripened cheeses. Models from Coroller et al. (2012) (https://doi.org/10.1016/j.ijfoodmicro.2011.09.023) had close to acceptable performance with ASZ-scores of 67-69%. The validated models (Martinez-Rios et al., 2019; Østergaard et al., 2014) can be used to facilitate the evaluation of time to critical L. monocytogenes growth for mould/smear-ripened cheeses including modification of recipes with for example reduced salt/sodium or to support exposure assessment studies for these cheeses.

Growth and growth boundary model with terms for melting salts to predict growth responses of Listeria monocytogenes in spreadable processed cheese.

The aim of this study was to develop and validate a growth and growth boundary model with terms for melting salts to predict growth of Listeria monocytogenes in spreadable processed cheese. Cardinal parameter terms for phosphate salts and citric acid were developed in broth studies and used to expand an available growth and growth boundary model. The expanded model includes the effect of nine environmental factors (temperature, pH, aw, lactic acid, acetic acid, citric acid, orthophosphate, di-phosphate and tri-phosphate). To generate growth data for model evaluation challenge tests with inoculated commercial (n = 10) and customized (n = 10) spreadable processed cheeses were performed. Evaluation of the new model by comparison of observed and predicted µmax-values resulted in a bias factor of 1.12 and an accuracy factor of 1.33 (n = 42). Prediction of growth and no-growth responses in processed cheese (n = 60) were 89% correct with 11% fail-safe and 0% fail-dangerous predictions. The developed model can be used to support product development, reformulation or risk assessment for spreadable processed cheese.

New Term to Quantify the Effect of Temperature on pH min -Values Used in Cardinal Parameter Growth Models for Listeria monocytogenes.

The aim of this study was to quantify the influence of temperature on pH min -values of Listeria monocytogenes as used in cardinal parameter growth models and thereby improve the prediction of growth for this pathogen in food with low pH. Experimental data for L. monocytogenes growth in broth at different pH-values and at different constant temperatures were generated and used to determined pH min -values. Additionally, pH min -values for L. monocytogenes available from literature were collected. A new pH min -function was developed to describe the effect of temperatures on pH min -values obtained experimentally and from literature data. A growth and growth boundary model was developed by substituting the constant pH min -value present in the Mejlholm and Dalgaard (2009) model (J. Food. Prot. 72, 2132-2143) by the new pH min -function. To obtain data for low pH food, challenge tests were performed with L. monocytogenes in commercial and laboratory-produced chemically acidified cheese including glucono-delta-lactone (GDL) and in commercial cream cheese. Furthermore, literature data for growth of L. monocytogenes in products with or without GDL were collected. Evaluation of the new and expanded model by comparison of observed and predicted µ max -values resulted in a bias factor of 1.01 and an accuracy factor of 1.48 for a total of 1,129 growth responses from challenge tests and literature data. Growth and no-growth responses of L. monocytogenes in seafood, meat, non-fermented dairy products, and fermented cream cheese were 90.3% correctly predicted with incorrect predictions being 5.3% fail-safe and 4.4% fail-dangerous. The new pH min -function markedly extended the range of applicability of the Mejlholm and Dalgaard (2009) model from pH 5.4 to pH 4.6 and therefore the model can now support product development, reformulation or risk assessment of food with low pH including chemically acidified cheese and cream cheese.

Foodborne viruses: Detection, risk assessment, and control options in food processing.

In a recent report by risk assessment experts on the identification of food safety priorities using the Delphi technique, foodborne viruses were recognized among the top rated food safety priorities and have become a greater concern to the food industry over the past few years. Food safety experts agreed that control measures for viruses throughout the food chain are required. However, much still needs to be understood with regard to the effectiveness of these controls and how to properly validate their performance, whether it is personal hygiene of food handlers or the effects of processing of at risk foods or the interpretation and action required on positive virus test result. This manuscript provides a description of foodborne viruses and their characteristics, their responses to stress and technologies developed for viral detection and control. In addition, the gaps in knowledge and understanding, and future perspectives on the application of viral detection and control strategies for the food industry, along with suggestions on how the food industry could implement effective control strategies for viruses in foods. The current state of the science on epidemiology, public health burden, risk assessment and management options for viruses in food processing environments will be highlighted in this review.

Modelling and predicting growth of psychrotolerant pseudomonads in milk and cottage cheese.

Mathematical models were developed and evaluated for growth of psychrotolerant pseudomonads in chilled milk and in cottage cheese with cultured cream dressing. The mathematical models include the effect of temperature, pH, NaCl, lactic acid and sorbic acid. A simplified cardinal parameter growth rate model was developed based on growth in broth. Subsequently, the reference growth rate parameter µref25°C-broth of 1.031/h was calibrated by fitting the model to a total of 35 growth rates from cottage cheese with cultured cream dressing. This resulted in a µref25°C-cottage cheese value of 0.621/h. Predictions from both growth rate models were evaluated by comparison with literature and experimental data. Growth of psychrotolerant pseudomonads in heat-treated milk (n=33) resulted in a bias factor (Bf) of 1.08 and an accuracy factor (Af) of 1.32 (µref25°C-broth), whereas growth in cottage cheese with cultured cream dressing and in non-heated milk (n=26) resulted in Bf of 1.08 and Af of 1.43 (µref25°C-cottage cheese). Lag phase models were developed by using relative lag times and data from both the present study and from literature. The acceptable simulation zone method showed the developed models to successfully predict growth of psychrotolerant pseudomonads in milk and cottage cheese at both constant and dynamic temperature storage conditions. The developed models can be used to predict growth of psychrotolerant pseudomonads and shelf life of chilled cottage cheese and milk at constant and dynamic storage temperatures. The applied methodology and the developed models seem likely to be applicable for shelf life assessment of other types of products where psychrotolerant pseudomonads are important for spoilage.

Risk-based estimate of effect of foodborne diseases on public health, Greece.

The public health effects of illness caused by foodborne pathogens in Greece during 1996-2006 was quantified by using publicly available surveillance data, hospital statistics, and literature. Results were expressed as the incidence of different disease outcomes and as disability-adjusted life years (DALY), a health indicator combining illness and death estimates into a single metric. It has been estimated that each year ≈370,000 illnesses/million inhabitants are likely caused because of eating contaminated food; 900 of these illnesses are severe and 3 fatal, corresponding to 896 DALY/million inhabitants. Ill-defined intestinal infections accounted for the greatest part of reported cases and 27% of the DALY. Brucellosis, echinococcosis, salmonellosis, and toxoplasmosis were found to be the most common known causes of foodborne illnesses, being responsible for 70% of the DALY. Overall, the DALY metric provided a quantitative perspective on the impact of foodborne illness that may be useful for prioritizing food safety management targets.