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Invasive listeriosis is a potentially fatal foodborne disease that according to this study may affect up to 32.9 % of the US population considered as increased risk and including people with underlying conditions and co-morbidities. Listeria monocytogenes has been scrutinized in research and surveillance programs worldwide in Ready-to-Eat (RTE) food commodities (RTE salads, deli meats, soft/semi-soft cheese, seafood) and frozen vegetables in the last 30 years with an estimated overall prevalence of 1.4-9.9 % worldwide (WD) and 0.5-3.8 % in the United States (US). Current L. monocytogenes control efforts have led to a prevalence reduction in the last 5 years of 4.9-62.9 % (WD) and 12.4-92.7 % (US). A quantitative risk assessment model was developed, estimating the probability of infection in the US susceptible population to be 10-10,000× higher than general population and the total number of estimated cases in the US was 1044 and 2089 cases by using the FAO/WHO and Pouillot dose-response models. Most cases were attributed to deli meats (90 % of cases) followed by RTE salads (3.9-4.5 %), soft and semi-soft cheese and RTE seafood (0.5-1.0 %) and frozen vegetables (0.2-0.3 %). Cases attributed to the increased risk population corresponded to 96.6-98.0 % of the total cases with the highly susceptible population responsible for 46.9-80.1 % of the cases. Removing product lots with a concentration higher than 1 CFU/g reduced the prevalence of contamination by 15.7-88.3 % and number of cases by 55.9-100 %. Introducing lot-by-lot testing and defining allowable quantitative regulatory limits for low-risk RTE commodities may reduce the public health impact of L. monocytogenes and improve the availability of enumeration data.

There has been an increasing demand for fresh fruit and vegetables in recent years. Along the processing line in fresh-cut vegetable production, disinfection is one of the most important processing steps affecting the quality and safety, and the shelf-life of the end produce. Although a range of antimicrobial compounds commonly termed biocides or disinfectants are available, chlorine has long been used to disinfect washing waters of fresh-cut vegetables. However, since chlorine reactions with organic matter lead to the production of by-products, alternative disinfectants to chlorine must be evaluated. A synthetic washing water formula has been developed to determine the antimicrobial efficiency of different families of potential disinfectants: quaternary ammonium compounds (QACs) as benzalkonium chloride (BZK), and didecyldimethylammonium chloride (DDAC); isothiazolinones (mixture of methylchloroisothiazolinone and methylisothiazolinone, CMIT:MIT 3:1 and 1:1); and essential oils (carvacrol, CAR). The twin configuration and higher length of the chains of alkyl groups of DDAC compared to BZK have led to a higher antimicrobial efficiency. In both cases, Gram-positive bacteria seemed to be much more sensitive to the QAC attack than Gram-negative. The opposite happened for CMIT:MIT. The chloro-substituted isothiazolinone (CMIT) has been proven to be much more effective than its unsubstituted form (MIT). In addition, in contrast to chlorine, its antimicrobial activity together with that of DDAC was not decreased when increasing the organic matter content of the water. Synergetic antimicrobial effects have been confirmed when combining BZK and CAR. MBC values were determined in SWW, during 90 s of contact time and Salmonella concentration of 103 CFU/mL, corresponding to: 100 (BZK), 30 (DDAC), 50 (CMIT:MIT 3:1), 100 (CMIT:MIT 1:1), 300 (CAR), 75 (BZK)-200 (CAR), and 9 (free chlorine) mg/L. MBC values for inactivating similar concentration of E. faecalis corresponded to: 50 (BZK), and 10 (DDAC) mg/L. Increasing contact times up to 5 min did not lead to higher antimicrobial efficiencies. CMIT:MIT 3:1 together with DDAC, and combinations of BZK-CAR seem to be a plausible alternative to chlorine.

Traditionally, predictive growth models for food pathogens are developed based on experiments in broth media, resulting in models which do not incorporate the influence of food microstructure. The use of model systems with various microstructures is a promising concept to get more insight into the influence of food microstructure on microbial dynamics. By means of minimal variation of compositional and physicochemical factors, these model systems can be used to study the isolated effect of certain microstructural aspects on microbial growth, survival and inactivation. In this study, the isolated effect on microbial growth dynamics of Listeria monocytogenes of two food microstructural aspects and one aspect influenced by food microstructure were investigated, i.e., the nature of the food matrix, the presence of fat droplets, and microorganism growth morphology, respectively. To this extent, fish-based model systems with various microstructures were used, i.e., a liquid, a second more viscous liquid system containing xanthan gum, an emulsion, an aqueous gel, and a gelled emulsion. Growth experiments were conducted at 4 and 10 °C, both using homogeneous and surface inoculation (only for the gelled systems). Results regarding the influence of the growth morphology indicated that the lag phase of planktonic cells in the liquid system was similar to the lag phase of submerged colonies in the xanthan system. The lag phase of submerged colonies in each gelled system was considerably longer than the lag phase of surface colonies on these respective systems. The maximum specific growth rate of planktonic cells in the liquid system was significantly lower than for submerged colonies in the xanthan system at 10 °C, while no significant differences were observed at 4 °C. The maximum cell density was higher for submerged colonies than for surface colonies. The nature of the food matrix only exerted an influence on the maximum specific growth rate, which was significantly higher in the viscous systems than in the gelled systems. The presence of a small amount of fat droplets improved the growth of L. monocytogenes at 4 °C, resulting in a shorter lag phase and a higher maximum specific growth rate. The obtained results could be useful in the determination of a set of suitable microstructural parameters for future predictive models that incorporate the influence of food microstructure on microbial dynamics. ispartof: International Journal Of Food Microbiology vol:283 pages:7-13 ispartof: location:SPAIN, Cordoba status: published

The aim of this study was to evaluate the behaviour of Salmonella Enteritidis during the storage of yoghurt at different temperatures (4, 12, 20, and 25 °C), and to develop mathematical models to predict the behaviour of this bacterium as a function of storage temperature. Results indicated that Salmonella was able to survive longer during storage when temperature was low (e.g. 304 h at 4 °C, 60 h at 25 °C). The Geeraerd model with log-decrease and tailing was selected as the most suitable model to describe survival. To evaluate the effect of storage temperature on kinetic parameters such as death rate (kmax) secondary models were developed. The kmax was maximum at 25 °C and minimum at 4 °C with kmax = 0.28 and 0.039 h−1, respectively. The residual population (Nres) ranged 0.5 and 1.8 log CFU/g but there was no temperature dependency of this parameter. A probabilistic example was conduced based on the developed model to assess the exposure to Salmonella by consumption of traditional Turkish yoghurt.

Consumers' demand for ready-to-eat (RTE) turkey meat is attributed to its convenience and healthy properties. However, as cooked meat product it is subjected to post-process contamination, thus allowing presence and growth of microbial pathogens, such as Salmonella spp.. The aim of this study was to include a natural antimicrobial, thyme essential oil (TEO), on RTE turkey products in order to evaluate its effectiveness throughout the shelf life. To do so, the effect of four different formulations of cooked RTE turkey products on Salmonella Enteritidis behaviour was investigated. Products' slices were surface inoculated with S. Enteritidis (ca. 4 to 5logcfu/g), subsequently stored at 10 and 25°C and microbiologically analysed during 18 and 12days, respectively. Predictive microbiology models fitted to count data were used to evaluate microbial behaviour. Results showed that S. Enteritidis behaviour on RTE turkey products slices during storage was strongly dependent on temperature. The pathogen was able to grow on slices at all tested conditions during storage at 25°C and no statistical differences were detected (p>0.05) between growth parameters. At 10°C, different behaviour patterns were observed. The application of TEO led to higher Salmonella inactivation rates on a product exempt of chemical preservatives. The addition of this novel antimicrobial on meat products or its incorporation on meat active packaging systems as a part of hurdle technology could increase RTE turkey products safety while satisfying the demand of more natural foods.

A tool able to quantitatively assess the fate of potential pathogenic microorganisms in foods along the food chain and their impact on public health is highly valuable for food safety decision-makers. The aim of this work was to present an overview of the Predictive Microbiology software MicroHibro, which is able to assess the evolution of potential pathogens and spoilage microorganisms along the food chain, providing estimates for the exposure level and risk associated with a food product. The application is built on an extensive Predictive Microbiology Model Data Base (PMDB) including kinetic processes like growth, inactivation, transfer as well as dose-response models. PMDB can be populated with new models by using an on-line tool in combination with a standardized method for describing Predictive Microbiology models. This enables MicroHibro to be easily updated, increasing its applicability and use. Estimation of microbial risk associated with a food product can be achieved, in MicroHibro, by describing steps in any food chain using four different microbial processes (growth, inactivation, transfer and partitioning). As a result, an estimate of the concentration and prevalence of microorganisms in the food of interest as well as attendant risk are provided. Also, MicroHibro allows comparing different predictive models and validate them by introducing user's data. In this paper, examples are provided to illustrate how predictive models can be incorporated in MicroHibro, and then, used to develop a Quantitative Microbial Risk Assessment model. The use of expert computational systems is a powerful tool for supporting food safety and quality activities by Health Authorities and the food industry. They represent a breakthrough in the assessment and management of food safety based on scientific evidence.

Human noroviruses (NoV) are recognized worldwide as important pathogens and the primary cause of foodborne disease outbreaks from contaminated food in the U.S. They are often transmitted by infected food handlers manipulating foods during preparation, such as fresh fruits and vegetables. This paper provides a study to model the transfer of NoV between food handlers and vegetables during salad preparation in school food services based on direct observation data. Three transfer pathways were modeled by considering different initial contamination sources (environment, handlers and contaminated produce). The probability of infection by NoV was also estimated based on the NoV levels at consumption obtained from each simulated transfer pathway. A scenario analysis ranging a wide concentration from 102 to 107 NoV infective particles was performed to represent different levels of NoV in the initial contamination sources. In addition, a sensitivity analysis was applied to identify the most important model inputs and determine the safest handling practices to be implemented in school food service operations. The pathway describing transfer from contaminated surfaces or handlers to foods indicated that initial levels of ≤104 NoV particles/fomite resulted in 0.2). In the pathway modeling cross contamination from contaminated vegetables to non-contaminated vegetables, all scenarios could lead to infected individuals, although number of cases of infection were lower (

Over the last couple of decades, several studies have evaluated growth dynamics of L. monocytogenes in lightly processed and ready-to-eat (RTE) fishery products mostly consumed in Nordic European countries. Other fish species from aquaculture production are of special interest since their relevant consumption patterns and added value in Mediterranean countries, such as sea bream and sea bass. In the present study, the growth of L. monocytogenes was evaluated in fish-based juice (FBJ) by means of optical density (OD) measurements in a temperature range 2-20 °C under different atmosphere conditions (i.e. reduced oxygen and aerobic). The Baranyi and Roberts model was used to estimate the maximum growth rate (μmax) from the observed growth curves. The effect of storage temperature on μmax was modelled using the Ratkowsky square root model. The developed models were validated using experimental growth data for L. monocytogenes in sea bream and sea bass fillets stored under static and dynamic temperature conditions. Overall, models developed in FBJ provided fail-safe predictions for L. monocytogenes growth. For the model generated under reduced oxygen conditions, bias and accuracy factor for growth rate predictions were 1.15 and 1.25, respectively, showing good performance to adequately predict L. monocytogenes growth in Mediterranean fish products. The present study provides validated predictive models for L. monocytogenes growth in Mediterranean fish species to be used in microbial risk assessment and shelf-life studies.

The present work aimed at studying the cross contamination of apples by Salmonella during the processing of commercial fresh apples and its survival capacity on apple at room temperature. For the first study, the typical process of fresh apples was simulated at laboratory scale in which an apple that was artificially contaminated by Salmonella at different concentration levels (8, 6 and 5 log cfu/apple) was introduced in one batch and processed including a simulated transport/washing step and drying step using sponges to simulate the porous material used in the industry. Results indicated that at 8 log cfu/apple, 50% fresh apples were contaminated after processing, with all analysed environmental samples being positive for the pathogen, consisting of washing water and sponges. However, at lower inoculum levels (5–6 log cfu/apple) no cross contamination was detected in apples, and only environmental samples showed contamination by Salmonella after processing including both water and sponges. Experiments on the survival of Salmonella on apple showed that the pathogen was capable to survive for 12 days, only showing a significant drop at the end of the experiment. Finally, two-class attribute sampling plans were assessed as tool to detect Salmonella in different contamination scenarios in fresh apple. This analysis indicated that with the highest inoculum level, a total of 16 apples would be needed to reach 95% of detecting Salmonella (i.e. lot rejection). In turn, when low levels were assessed (5–6 log cfu/apple), a large number of apples ( n = 1021) would have to be sampled to obtain the same confidence level (95%). If the environment is sampled (i.e. water and sponges), a lower number of samples would be needed to detect the pathogen. However, the feasibility of environmental sampling has not been assessed from a practical point of view. Overall, the results in this study evidenced that cross contamination by Salmonella might occur during processing of fresh apples and subsequently, the pathogen might survive for a noticeable period of time.

The purpose of this study was to evaluate and model the growth of Escherichia coli O157:H7 in fresh-cut lettuce submitted to a neutral electrolyzed water (NEW) treatment, packaged in passive modified atmosphere and subsequently stored at different temperatures (4, 8, 13, 16°C) for a maximum of 27 days. Results indicated that E. coli O157:H7 was able to grow at 8, 13, and 16°C, and declined at 4°C. However at 8°C, the lag time lasted 19 days, above the typical shelf-life time for this type of products. A secondary model predicting growth rate as a function of temperature was developed based on a square-root function. A comparison with literature data indicated that the growth predicted by the model for E. coli O157:H7 was again lower than those observed with other disinfection treatments or packaging conditions (chlorinated water, untreated product, NEW, etc.). The specific models here developed might be applied to predict growth in products treated with NEW and to improve existing quantitative risk assessments.

The recent Commission Regulation (EC) No 2073/2005 establishes microbiological criteria in foods. For the pathogen Listeria monocytogenes in the category ready-to-eat foods able to support its growth, other than those intended for infants and for special medical purposes, two different microbiological criteria are proposed: (i) L. monocytogenes levels should be < 100 cfu/g throughout the shelf-life of the product, (ii) absence in 25 g of the product at the stage before the food has left the immediate control of the food business operator, who has produced it. The application of either the first or the second of these criteria depends on whether or not the manufacturer is able to demonstrate that the level of L. monocytogenes in the food product will not exceed 100 cfu/g throughout its shelf-life. This demonstration should be based on physico-chemical characteristics of the target product and consultation of scientific literature, and, when necessary, on quantitative models and/or challenge tests. Once the characteristics of the product as well as scientific literature show that the pathogen has potential to grow on a specific food commodity, it seems adequate to use quantitative models and/or perform challenge tests to study the extent to which L. monocytogenes could grow. In this study, we aim to illustrate with an example in cooked ham the application of quantitative models as a tool to manage the compliance with these criteria. Two approaches were considered: deterministic and probabilistic, in three different commercial brands (A, B, and C). The deterministic approach showed that the limit 100 cfu/g was exceeded largely at the end of the shelf-life of all three; however, when reducing the storage time, the level of L. monocytogenes remained below 100 cfu/g in B. The probabilistic approach demonstrated very low percentiles corresponding to 100 cfu/g; when reducing the storage time, percentiles for three products increased, especially in products B and C (from 4.92% to 75.90%, and from 0.90% to 73.90%, respectively). This study shows how different storage times influence the level of L. monocytogenes at the end of the shelf-life of cooked ham, and, depending on the level reached, the microbiological criterion applied should be different, as stated above. Beside this, the choice of either point-estimate or probabilistic approach should be determined by the competent sanitary authority, and, in case of selecting the second approach, a certain percentile for the level 100 cfu/g should be established.

Prevalence and concentration of Listeria monocytogenes, Salmonella spp. and enteric pathogenic viruses (namely Hepatitis A-HAV, and noroviruses genogroup I-NoVGI and genogroup II-NoVGII) were determined in raw and RTE lettuce from a Spanish processing premise. Fifteen samplings were made from September 2010 to February 2012 (n=600 samples). Sampling strategies for pathogen detection were suggested by the characterization of the uncertainty in prevalence associated with the performance of two-class attributes sampling plans (c=0). A probabilistic model was run (1000 iterations) using a Bayesian approach with a conjugate beta distribution considering the impact of taking different number of samples on the proportion of positive samples and lots (within- and between-lot prevalence). No enumeration results were obtained for the pathogens tested. Presence of L. monocytogenes and NoVGII in RTE lettuce (10%) and NoVGI and NoVGII in unprocessed lettuce (10%) was obtained in the tested lots during cold season. Results evidenced that, as the number of samples increased, the probability of rejecting a contaminated lot became higher, yielding right-skewed distributions with values close to 1. According to our results, 25 samples would result in 80% of rejected lots, while 95% confidence level would be reached with n>100. However, although those levels would imply a unrealistic high number of samples making the application of the sampling plan unfeasible, these results might be useful for food operators and risk managers to know the underlying distributions of microbial contamination together with potential control measures to be applied to assure a safer production of minimally processed vegetables.

Fecal pathogen distributions in fresh-cut leafy vegetables are essential to develop suitable sampling plans so as to detect pathogen contaminations. In this study, a typical fresh-cut lettuce process was reproduced at pilot scale with different initial inoculum levels of Salmonella on lettuce (6–7, 4 and 1 log CFU/g). The pathogen was determined in all processed lettuce samples (n ≥ 50) and obtained count data were used to fit different probability distributions. The study showed that Salmonella is homogenously distributed on fresh-cut leafy vegetables as a result of processing (mainly washing) at all contamination levels. Negative binomial and Poisson-lognormal distributions were suitable to describe pathogen distribution at the high and medium levels. coefficient of variation modified ( CV *) indicated no overdispersion (i.e. clustering). Nevertheless, further research will be needed to assess the effect of using disinfectants in washing water on the final distribution pattern of pathogens in processed fresh-cut leafy vegetables.