Search

This study aims to evaluate the effectiveness of inactivating Salmonella enteritidis in fresh chicken breast by irradiation using a combination of short-wave UV (0, 3, 6, 9, 12, and 15 J/cm 2 ) and a natural antimicrobial such as caffeine (0, 5, 10, 15, and 20 nM/g) at 14 °C as alternative proposals to conventional techniques to reduce pathogens in food. The effect of temperature was studied in an initial phase (2 to 22 °C). The most suitable models were double Weibull in 60% of cases, with an adjustment of R 2 0.9903-0.9553, and Weibull + tail in 46.67%, with an adjustment of R 2 of 0.9998-0.9981. The most effective combination for the reduction in Salmonella was 12 J/cm 2 of UV light and 15 nM/g of caffeine, with a reduction of 6 CFU/g and an inactivation rate of 0.72. The synergistic effect was observed by increasing caffeine and UV light. Furthermore, the physico-chemical characteristics of the food matrix were not affected by the combination of both technologies. Therefore, these results suggest that this combination can be used in the food industry to effectively inactivate Salmonella enteritidis without deteriorating product quality.

The consumption of fisheries and aquaculture products has been increasing in recent decades, and it is necessary to strike a balance between production and sustainability in aquaculture; this is essential homework to support the demand for human food. This study aimed to investigate the sensory and nutritional characteristics of a sausage made from the fillet of the native fish Old Blue ( Andinoacara rivulatus ) to stimulate the local economy. A multifactorial A*B*C design was used, with Factor A being rearing systems (wild and farmed), Factor B being types of protein (quinoa meal and soybean meal), and Factor C being lipids of animal (pork fat) and vegetable (sunflower oil) origin. Highly significant differences were observed in all formulas, according to Tukey ( p < 0.05). The highest protein percentage was with soybean flour at 11.24%, while quinoa flour had 10.80% of the product. In sensory characteristics, the best attributes were for texture in the mouth with a hedonic scale from 0 to 5, with 4.2 firmness being mostly acceptable, odor at 4.5, the aromatic attribute with the highest and best value, and color was the clearest at 4.3 acceptability. The flavor was 4.3, mostly more pleasant according to the tasters. The yield of farmed fillets was 23.16% compared to wild 13.89%, and the balance of sausage yield was 393 g with a yield of 76.33% of the total weight. Microbiological analysis of the sausage with the native species showed the absence of pathogenic microorganisms. A commercial shelf life of 30 days was also established for the sausage, demonstrating an added value through this processing, allowing its exploitation in areas further away from the fishing sites and, thus, a greater possibility of social development in the area.

"Turrialba cheese" is a Costa Rican fresh cheese highly appreciated due to its sensory characteristics and artisanal production. As a ready-to-eat dairy product, its formulation could support Listeria monocytogenes growth. L. monocytogenes was isolated from 14.06% of the samples and the pathogen was able to grow under all tested conditions. Due to the increasing demand for low-salt products, the objective of this study was to determine the effect of salt concentration on the growth of pathogen isolates obtained from local cheese. Products from retail outlets in Costa Rica were analyzed for L. monocytogenes . These isolates were used to determine growth at 4 °C for different salt concentration (0.5-5.2%). Kinetic curves were built and primary and secondary models developed. Finally, a validation study was performed using literature data. The R 2 and Standard Error of fit of primary models were ranked from 0.964-0.993, and 0.197-0.443, respectively. An inverse relationship was observed between growth rate and salt concentration. A secondary model was obtained, with R 2 = 0.962. The model was validated, and all values were B f > 1, thus providing fail-safe estimations. These data were added to the free and easy-to-use predictive microbiology software "microHibro" which is used by food producers and regulators to assist in decision-making.

The presence of Vibrio species in table olive fermentations has been confirmed by molecular biology techniques in recent studies. However, there has been no report of any foodborne outbreak caused by Vibrio due to the consumption of table olives, and their role as well as the environmental conditions allowing their survival in table olives has not been elucidated so far. The aims of this work were to model the behavior of an inoculated Vibrio cocktail in diverse table olive environments and study the possible behavior of an inoculated Vibrio cocktail in table olives. First, an in vitro study has been performed where the microbial behavior of a Vibrio cocktail was evaluated in a laboratory medium and in olive brines using predictive models at different NaCl concentrations (2-12%) and pH levels (4.0-9.0). Afterward, a challenge testing was done in lye-treated olives inoculated at the beginning of fermentation with the Vibrio cocktail for 22 days. The Vibrio cocktail inoculated in table olives has not been detected in olive brines during fermentation at different pH levels. However, it was observed that this microorganism in a laboratory medium could reach an optimal growth at pH 9 and 2% salt, without time of constant absorbance ( t A ), and the maximum absorbance value ( y end ) observed was at pH 8 and 2% salt conditions. The statistical analysis demonstrated that the effect of salt concentration was higher than pH for the kinetic growth parameters (μ max , t A , and y end ). On the other hand, it was confirmed that no growth of the Vibrio cocktail on any sample was noticed in lye-treated olive fermentations. Thus, it was concluded that the presence of olive compounds (unknown) did not allow the development of Vibrio strains, so it is a very safety product as it has a natural antimicrobial compound, but the possibility that a native Vibrio sp. is able to acquire the capacity to adapt to this compound should be considered in further studies., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Posada-Izquierdo, Valero, Arroyo-López, González-Serrano, Ramos-Benítez, Benítez-Cabello, Rodríguez-Gómez, Jimenez-Diaz and García-Gimeno.)

The Clostridium sp. is a large group of spore-forming, facultative or strictly anaerobic, Gram-positive bacteria that can produce food poisoning. The table olive industry is demanding alternative formulations to respond to market demand for the reduction of acidity and salt contents in final products. while maintaining the appearance of freshness of fruits. In this work, logistic regression models for non-adapted and acid-adapted Clostridium sp. strains were developed in laboratory medium to study the influence of pH, NaCl (%) and time on the probability of germination of their spores. A Clostridium sporogenes cocktail was not able to germinate at pH < 5.0, although the adaptation of the strains produced an increase in the probability of germination at 5.0-5.5 pH levels and 6% NaCl concentration. At acidic pH values (5.0), the adapted strains germinated after 10 days of incubation, while those which were non-adapted required 15 days. At pH 5.75 and with 4% NaCl, germination of the adapted strains took place before 7 days, while several replicates of the non-adapted strains did not germinate after 42 days of storage. The model was validated in natural green olive brines with good results (>81.7% correct prediction cases). The information will be useful for the industry and administration to assess the safety risk in the formulation of new processing conditions in table olives and other fermented vegetables.

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., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Table olives are one of the most representatives and consumed fermented vegetables in Mediterranean countries. However, there is an evident lack of standardization of production processes and HACCP systems thus implying the need of establishing decision-making tools allowing their commercialization and shelf-life extension. The present work aims at developing a decision-making scoring system by means of a probabilistic assessment to standardize production process of Aloreña de Málaga table olives based on the identification of potential hazards or deficiencies in hygienic processes for the subsequent implementation of corrective measures. A total of 658 microbiological and physico-chemical data were collected over three consecutive olive campaigns (2014-2016) to measure the variability and relative importance of each elaboration step on total hygienic quality and product safety. Three representative companies were visited to collect samples from food-contact surfaces, olive fruits, brines, air environment, olive dressings, water tanks, and finished/packaged products. A probabilistic assessment was done based on the establishment of Performance Hygiene and Safety Scores (PHSS 0-100%) through a standardized system for evaluating product acceptability. The mean value of the global PHSS for the Aloreña de Málaga table olives processing (PHHS FTOT ) was 64.82% (90th CI: 52.78-76.39%) indicating the high variability among facilities in the evaluated processing steps on final product quality and safety. Washing and cracking, and selection and addition of olive dressings were detected as the most deficient ones in relation to PHSS Fi values ( p < 0.05) (mean = 53.02 and 56.62%, respectively). The relative contribution of each processing step was quantified by different experts ( n = 25) from the Aloreña de Málaga table olive sector through a weighted PHSS (PHSS w ). The mean value of PHSS w was 65.53% (90th CI: 53.12-77.52%). The final processing steps obtained higher values for PHSS w being the finished product the most relevant one (mean = 18.44%; 90% CI: 10.34-25.33%). Sensitivity analysis concluded that intervention measures focused on reducing the contamination of washing brines could lead to an improvement of PHSS FTOT value to 67.03%. The present work can be potentially applied in the Aloreña de Málaga table olive food sector for improving food quality and safety assurance.

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., (Copyright © 2016 Elsevier B.V. All rights reserved.)

The increased demand for low-sodium ready-to-eat (RTE) meat products highlights the need for new strategies to ensure food safety. The application of essential oils (EOs) as natural antimicrobials in the meat industry has been suggested to prevent or control cross-contamination during meat processing operations. This work aims to quantify and model the transfer of Salmonella Enteritidis during the slicing procedure of RTE turkey products treated with thyme essential oil (TEO) at a concentration of 0.1% (v/w). Two products were subjected to the slicing procedure with slicer blades inoculated with S. Enteritidis at 10 8 cfu/mL. The Weibull and modified Weibull predictive models were fitted to the transfer data. Twenty slices were sampled and showed positive with bacteria, indicating cross-contamination. The number of cells transferred per slice decreased logarithmically during the assays. The transfer models, based on the Weibull model, were suitable to describe the bacterial transfer trend on slices in most cases. TEO treatment reduced the transfer of Salmonella on a preservative free RTE turkey product. The predictive models obtained in this study can help food-quality staff and managers on the design and assessment of processes to guard RTE turkey products against Salmonella. This work supports the addition of EOs to reduce microbial risk in RTE meat products., (© 2016 Institute of Food Technologists®.)

The microbiological standard for detection of Salmonella relies on several cultural steps and requires more than 5 days for final confirmation, and as consequence there is a need for an alternative rapid methodology for its detection. The aim of this study was to compare different detection strategies based on real-time PCR for a rapid and sensitive detection in an ample range of food products: raw pork and poultry meat, ready to eat lettuce salad and raw sheep milk cured cheese. Three main parameters were evaluated to reduce the time and cost for final results: the initial sample size (25 and 50 g), the incubation times (6, 10 and 18 h) and the bacterial DNA extraction (simple boiling of the culture after washing the bacterial pellet, the use of the Chelex resin, and a commercial silica column). The results obtained demonstrate that a combination of an incubation in buffered peptone water for 18 h of a 25 g-sample coupled to a DNA extraction by boiling and a real-time PCR assay detected down to 2-4 Salmonella spp.CFU per sample in less than 21 h in different types of food products. This RTi-PCR-based method is fully compatible with the ISO standard, providing results more rapidly and cost-effectively. The results were confirmed in a large number of naturally contaminated food samples with at least the same analytical performance as the reference method., (Copyright © 2014 Elsevier B.V. All rights reserved.)

The aim of this paper was to provide suitable microbiological criteria (MC) for Campylobacter in broiler carcasses and a sampling plan to verify compliance with such criteria. Data were gathered in the presence and concentration of Campylobacter in broiler carcasses collected in three different Italian slaughterhouses, labelled as A, B and C. The sampling plan to be validated in each slaughterhouse included the analysis of three different carcasses collected immediately after chilling from 30 different lots, for a total of 90 samples per slaughterhouse. The number of positive samples containing above 100 CFU/g and above 1,000 CFU/g throughout the 30 tested lots was determined to estimate between-lot variability. Based on this information, the performance of four MC was evaluated for lot compliance: i) n=3; c=0; m=100 CFU/g; ii) n=3; c=0; m=1,000 CFU/g; iii) n=3; c=1; m=1,000 CFU/g and iv) n=3; c=2; m=1,000 CFU/g. Positive Campylobacter samples were found in 60% of the lots tested in slaughterhouses A and C and in 73.3% of lots from slaughterhouse B. The differences among the three slaughterhouses in the mean Campylobacter levels found in positive samples were not significant and were used to evaluate the performance of the MC. The level of lot compliance to different MC was calculated and for the most stringent one (n=3; c=0; m=100 CFU/g) was 40% at slaughterhouses A and C but only 26.7% at slaughterhouse B. The results of this study show an alternative approach to establish MC for Campylobacter in broilers. According to (1) Campylobacter prevalence and concentration in Italy, (2) applied experimental plan and (3) selected slaughterhouses, the number of compliant lots to the suggested MC ranged between 26.7 and 100%. The selection of the fit for purpose MC is a risk manager decision, based on a reasonable balance between public health and cost for poultry industries., (Copyright © 2014 Elsevier B.V. All rights reserved.)

In the present study, prevalence and concentration of Salmonella spp. and Listeria monocytogenes in fresh pork cuts were determined through the analysis of twelve lots for one year. Five samples were analyzed at retail and after storage at 4 and 12°C up to the end of shelf-life (7 days). Results obtained for Salmonella spp. indicated that a total of 15 samples (8.33%) were positive, which represents 4 (25%) sampling events positive (i.e. at least one sample was positive in at least one of the sampling scenarios). Salmonella was randomly distributed and direct correlation with storage time and temperature was not obtained. For L. monocytogenes, 26 samples (14.44%) were positive, which represents 5 (41.67%) positive sampling lots. For this pathogen, a group of samples were only positive at the end of the shelf-life but not immediately after purchasing indicating clearly that the contamination was not only heterogeneously distributed but also close to the levels of detection, and in all the cases below the limit of contamination. As neither Salmonella spp. nor L. monocytogenes was enumerated by direct plating (<10 cfu/g) a probabilistic approach basing on Binomial and Poisson distributions was subsequently performed to estimate microbial concentration from presence/absence data. Estimated concentration values were below 40 cfu/kg for both pathogens in more than 80% of the tested lots. The data collected in this study add new knowledge on this very important and difficult to control segment of the farm-to-fork chain., (Copyright © 2014 Elsevier B.V. All rights reserved.)

The objective of this work was to study the effect of post-packaging pasteurization on the sensory quality and growth of natural microorganisms during refrigerated storage (6 °C) of a cooked meat product considering two packaging atmospheres based on mixture of typical gases (CO(2)/N(2) (22/78%) and novel gases (CO(2)/Ar (17/83%)). Growth of lactic acid bacteria was significantly different between samples with and without post-packaging pasteurization, showing a growth rate >0.44 and equal to 0.28 log cfu/day, respectively. For samples with post-packaging pasteurization, atmosphere CO(2)/Ar resulted in a lower growth of lactic acid bacteria and a better sensory quality. Overall, samples without post-packaging pasteurization did not show a significant reduction of sensory quality during storage time (121 days) while samples with post-packaging pasteurization showed deterioration in their sensory quality. Further investigation is needed to obtain more definitive conclusions about the effect of post-packaging pasteurization and argon-based packaging atmospheres on cooked meat products.

The survival of Escherichia coli O157:H7 and Staphylococcus aureus on stainless steel surfaces with Saline Solution (SS), Tryptone Soy Broth (TSB) and meat purge was studied, and based on results, mathematical models describing survival of pathogens as a function of time were proposed. Results indicated that S. aureus was able to survive longer than E. coli O157:H7 in all substrates. The type of substrate had a greater impact on the survival of E. coli O157:H7. This microorganism only remained viable for 8 and 50 h (hours) on surfaces with SS and TSB, respectively while on meat purge, the microorganism could be recovered after 200 h. For S. aureus, SS and TSB led to similar survival times (250 h) whereas on meat purge, survival capacity increased to 800 h. Survival data for S. aureus could be well described by a log-linear model or a Weibull model depending on the type of substrate (R(2) > 0.85). E. coli O157:H7 displayed an evident tail zone which made the Weibull model more appropriate (R(2) > 0.94). These survival models may be used in quantitative risk assessment to produce more accurate risk estimates. Finally, the results highlight the importance of performing effective cleaning procedures to prevent cross contamination., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

In this work, the effect of pre-incubation conditions (temperature: 10, 15, 37 °C; pH 5.5, 6.5 and water activity, a(w): 0.997, 0.960) was evaluated on the subsequent growth, survival and enterotoxin production (SE) of Staphylococcus aureus in cooked chicken breast incubated at 10 and 20 °C. Results showed the ability of S. aureus to survive at 10 °C when pre-incubated at low a(w) (0.960) what could constitute a food risk if osmotic stressed cells of S. aureus which form biofilms survive on dried surfaces, and they are transferred to cooked meat products by cross-contamination. Regarding growth at 20 °C, cells pre-incubated at pH 5.5 and a(w) 0.960 had a longer lag phase and a slower maximum growth rate. On the contrary, it was highlighted that pre-incubation at optimal conditions (37 °C/pH 6.5/a(w) 0.997) produced a better adaptation and a faster growth in meat products what would lead to a higher SE production. These findings can support the adoption of management strategies and preventive measures in food industries leading to avoid growth and SE production in meat products., (Copyright © 2012 Elsevier Ltd. All rights reserved.)

Ready-to-eat lettuce is a food commodity prone to contamination by pathogenic microorganisms if processing and distribution conditions as well as handling practices are not effective. A challenge testing protocol was applied to ready-to-eat iceberg-lettuce samples by inoculating different initial contamination levels (4.5, 3.5 and 2.5 log cfu/g) of Escherichia coli strain (serotype O158:H23) subsequently stored at 8, 12, 16, 20 and 24°C for 6h. A polynomial regression model for log difference (log(diff)) was developed at each inoculum level studied through the calculation of the effective static temperature (T(eff)). Furthermore, the developed model was integrated within a risk-based approach with real time/Temperature (t/T) data collected in three Spanish foodservice centers: school canteens, long-term care facilities (LTCF) and hospitals. Statistical distributions were fitted to t/T data and estimated log(diff) values were obtained as model outputs through a Monte Carlo simulation (10,000 iterations). The results obtained at static conditions indicated that the maintenance of the lettuce at 8°C slightly reduced the E. coli population from -0.4 to -0.5 log cfu/g. However, if chill chain is not maintained, E. coli can grow up to 1.1 log cfu/g at temperatures above 16°C, even at low contamination levels. Regarding log(diff) estimated in foodservice centers, very low risk was obtained (log(diff)<1.0 log cfu in all cases). Mean T(eff) values obtained in hospitals were the lowest ones (11.1°C) and no growth of E. coli was predicted in >92% of simulated cases. The results presented in this study could serve food operators to set time/Temperature requirements for ready-to-eat foods in foodservice centers, providing a scientific basis through the use of predictive modeling. These findings may also serve to food safety managers to better define the control measures to be adopted in foodservice centers in order to prevent food-borne infections., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Background: This study was conducted in eight Spanish school canteens during the period 2008-2009. Food handlers' practices, kitchen equipment, hygiene/sanitation conditions and handling practices were evaluated using checklists. In parallel, the microbiological quality and safety of ready-to-eat (RTE) vegetable salads were assessed. In addition, food contact surfaces and environmental air quality of different areas were analysed. The study determined the relationship between the microbiological quality of RTE foods and food handling practices, together with the degree of contamination of working surfaces and environmental contamination of processing and distribution areas., Results: Some deficiencies were found regarding the use and change of gloves, hand-washing and cleanliness of working surfaces. The microbial levels detected in the foods examined indicated the absence of pathogens in the samples analysed. Surface counts were higher on cutting boards and faucets, showing insufficient cleanliness procedures., Conclusion: This study constitutes a descriptive analysis of the hygiene/sanitation conditions implemented in food service systems in eight Spanish school canteens. The results should help risk managers to better define control measures to be adopted in order to prevent foodborne infections., (Copyright © 2012 Society of Chemical Industry.)

Cooked meat ready-to-eat products are recognized to be contaminated during slicing which, in the last years, has been associated with several outbreaks. This work aimed to find out possible relation between the hygiene practice taking place at retail point during slicing of cooked meat products in small and medium-sized establishments (SMEs) and large-sized establishments (LEs) and the microbiological quality of sliced cooked meat products. For that, a checklist was drawn up and filled in based on scoring handling practice during slicing in different establishments in Cordoba (Southern Spain). In addition, sliced cooked meats were analyzed for different microbiological indicators and investigated for the presence of Listeria spp. and Listeria monocytogenes. Results indicated that SMEs showed a more deficient handling practices compared to LEs. In spite of these differences, microbiological counts indicated similar microbiological quality in cooked meat samples for both types of establishments. On the other hand, Listeria monocytogenes and Listeria inocua were isolated from 7.35% (5/68) and 8.82% (6/68) of analyzed samples, respectively. Positive samples for Listeria spp. were found in establishments which showed acceptable hygiene levels, though contamination could be associated to the lack of exclusiveness of slicers at retail points. Moreover, Listeria spp presence could not be statistically linked to any microbiological parameters; however, it was observed that seasonality influenced significantly (P<0.05) L. monocytogenes presence, being all samples found during warm season (5/5). As a conclusion, results suggested that more effort should be made to adequately educate handlers in food hygiene practices, focused specially on SMEs., (Copyright (c) 2010 Elsevier B.V. All rights reserved.)

Foodborne diseases constitute a major concern in societies, and their causes are aimed to be identified and minimized. Only in the last few years, this is encouraged by the application of risk assessment, management, and communication. This work presents a probabilistic quantitative microbiological risk assessment and management of Listeria monocytogenes in ready-to-eat lettuce salads in Spain. For risk assessment, a guideline provided by Codex Alimentarius was followed. Food chain was modeled from processing of raw material at the factory up to consumption. Different assumptions were made to describe the variables of the model by probability distributions or mathematical models. Monte Carlo simulations of the model were run to estimate the number of cases in low-risk and high-risk populations. Although results deviated from the number of cases observed in Spain, given an ideal situation of 100% compliance of the microbiological criterion ≤100 cfu/g throughout the shelf-life of the product, the resulting number of cases was near the real situation. From the 4 risk management measures simulated, the injection of a mixture of gases into packages at manufacture (CO 2 about 5.5%, O 2 about 3%, and N 2 for the balance) was the most effective in reducing the number of cases, followed by 4 d of storage at home and prevention of high-risk consumers from consumption of ready-to-eat lettuce salads. More research and cooperation between different stakeholder organizations are needed in order to progressively improve the model. With this work, a breakthrough has been made with regards to risk assessment and management procedures and implementation., (© 2010 Institute of Food Technologists®.)

The presence of Escherichia coli in contaminated food products is commonly attributed to faecal contamination when they are improperly handled and/or when inactivation treatments fail. Adaptation of E. coli at low pH and a(w) levels can vary at different temperatures depending on the serotype, thus more detailed studies are needed. In this work, a screening to assess the growth of four pathogenic serotypes of E. coli (O55:H6; O59:H21; O158:H23 and O157:H7) was performed. Subsequently, boundary models were elaborated with the fastest serotype selected at different temperatures (8, 12 and 16 degrees C), and inoculum levels (2, 3 and 4log cfu/mL) as function of pH (7.00-5.00) and a(w) (0.999-0.960). Finally, the growth kinetics of E. coli was described in the conditions that allowed growth. Results obtained showed that the serotypes O157:H7 and O59:H21 did not grow at more stringent conditions (8 degrees C; pH 5.50), while the E. coli O158:H23 was the best adapted, resulting in faster growth. The logistic regression models presented a good adjustment to data observed since more than 96.7% of cases were correctly classified. The growth interface was shifted to more limited conditions as the inoculum size was higher. Detection times (t(d), h) and their variability were higher at low levels of the environmental factors studied. This work provides insight on the growth kinetics of E. coli at various environmental conditions., (Copyright 2010 Elsevier Ltd. All rights reserved.)

Boundary models have been recognized as useful tools to predict the ability of microorganisms to grow at limiting conditions. However, at these conditions, microbial behaviour can vary, being difficult to distinguish between growth or no growth. In this paper, the data from the study of Valero et al. [Valero, A., Pérez-Rodríguez, F., Carrasco, E., Fuentes-Alventosa, J.M., García-Gimeno, R.M., Zurera, G., 2009. Modelling the growth boundaries of Staphylococcus aureus: Effect of temperature, pH and water activity. International Journal of Food Microbiology 133 (1-2), 186-194] belonging to growth/no growth conditions of Staphylococcus aureus against temperature, pH and a(w) were divided into three categorical classes: growth (G), growth transition (GT) and no growth (NG). Subsequently, they were modelled by using a Radial Basis Function Neural Network (RBFNN) in order to create a multi-classification model that was able to predict the probability of belonging at one of the three mentioned classes. The model was developed through an over sampling procedure using a memetic algorithm (MA) in order to balance in part the size of the classes and to improve the accuracy of the classifier. The multi-classification model, named Smote Memetic Radial Basis Function (SMRBF) provided a quite good adjustment to data observed, being able to correctly classify the 86.30% of training data and the 82.26% of generalization data for the three observed classes in the best model. Besides, the high number of replicates per condition tested (n=30) produced a smooth transition between growth and no growth. At the most stringent conditions, the probability of belonging to class GT was higher, thus justifying the inclusion of the class in the new model. The SMRBF model presented in this study can be used to better define microbial growth/no growth interface and the variability associated to these conditions so as to apply this knowledge to a food safety in a decision-making process., (2010. Published by Elsevier B.V. All rights reserved.)

The microbial behaviour of five enterotoxigenic strains of Staphylococcus aureus was studied in the growth/no growth domain. A polynomial logistic regression equation was fitted using a stepwise method to study the interaction of temperature (8, 10, 13, 16 and 19 degrees C), pH (4.5; 5.0; 5.5; 6.0; 6.5 7.0 and 7.5) and water activity (A(w)) (19 levels ranging from 0.867 to 0.999) on the probability of growth. Out of the 284 conditions tested, 146 were chosen for model data and 138 intermediate conditions for validation data. A growth/no growth transition was obtained by increasing the number of replicates per condition (n=30) in comparison to other published studies. The logistic regression model showed a good performance since 96.6% (141 out of 146 conditions) of the conditions for model data and 92.0% (127 out of 138 conditions) for validation data were correctly classified. The predictions indicated an abrupt growth/no growth interfaces occurred at low levels of temperature, pH and A(w). At 8 degrees C, S. aureus grew only at optimum levels of pH and A(w) while at temperatures above 13 degrees C, growth of S. aureus was observed at pH=4.5 and A(w)=0.96 (13 degrees C), 0.941 (16 degrees C) and 0.915 (19 degrees C). The optimal pH at which growth of S. aureus was detected earlier was 6.5. However, a slight decrease of the probability of growth was noticed in the pH interval of 7.0-7.5 at more stringent conditions. The ability of S. aureus to grow at low A(w) was shown since growth was detected at A(w)=0.867 (T=19 degrees C; pH=7.0). Finally, a comparison of model predictions with literature data on growth/no growth responses of S. aureus in culture media and cooked meat was made. Model predictions agreed with published data in 94% of growth cases and in 62% of no growth cases. The latter discordance is highly associated to other environmental factors (such as other preservatives, strains etc.) included in published models that did not match the ones included in our study. This study can help manufacturers in making decision on the most appropriate formulations for food products in order to prevent S. aureus growth and enterotoxin production along their shelf-life.

Increasing demand for fresh-cut or ready-to-eat fruits and vegetables, developed to meet the consumer need for quick and convenient products, has prompted extensive research into their microbiological quality, safety, processing, and packaging. The microbial ecology of Listeria monocytogenes is recognized as a major safety concern for fresh-cut produce. A survey was performed to collect information on consumption patterns of fresh-cut leafy green salads and the temperature of domestic refrigerators. Salad consumption was low-moderate: 24.3% of respondents never purchased fresh-cut leafy green salads; of those who reported buying these products, 7.41% did so more than twice a week, 17.28% once or twice a week, 29.63% once or twice a month, and 45.68% occasionally. Saving time and convenience were the advantages most widely reported by consumers. A total of 9.9% of respondents did not always respect the "use-by" date of fresh-cut salads, a negative practice that could contribute to the risk of listeriosis. Temperatures reported in domestic refrigerators were compatible with the growth of L. monocytogenes on ready-to-eat salads. Variations in average temperature followed a normal distribution, N(6.62, 2.56), while the variability of temperature variance was described by a gamma distribution, G(2.00, 1.00). As expected, when a time of day-temperature profile was plotted over a 24-h period, changes corresponding to the transition between day and night were observed. Knowledge of consumption patterns and consumer hygiene practices is essential, first in assessing the risk of listeriosis (risk assessment) and second in taking measures to manage that risk (risk management).

A new approach to predict the growth/no growth interface of Listeria monocytogenes as a function of storage temperature, pH, citric acid (CA) and ascorbic acid (AA) is presented. A linear logistic regression procedure was performed and a non-linear model was obtained by adding new variables by means of a Neural Network model based on Product Units (PUNN). The classification efficiency of the training data set and the generalization data of the new Logistic Regression PUNN model (LRPU) were compared with Linear Logistic Regression (LLR) and Polynomial Logistic Regression (PLR) models. 92% of the total cases from the LRPU model were correctly classified, an improvement on the percentage obtained using the PLR model (90%) and significantly higher than the results obtained with the LLR model, 80%. On the other hand predictions of LRPU were closer to data observed which permits to design proper formulations in minimally processed foods. This novel methodology can be applied to predictive microbiology for describing growth/no growth interface of food-borne microorganisms such as L. monocytogenes. The optimal balance is trying to find models with an acceptable interpretation capacity and with good ability to fit the data on the boundaries of variable range. The results obtained conclude that these kinds of models might well be very a valuable tool for mathematical modeling.

Cross contamination is one of the most important contributing factors in foodborne illnesses originating in household environments. The objective of this research was to determine the transfer coefficients between a contaminated domestic slicing machine and a cooked meat product, during slicing. The microorganisms tested were Staphylococcus aureus (Gram positive) and Escherichia coli O157:H7 (Gram negative). The results showed that both microorganisms were able to transfer to all slices examined (20 successively sliced) and at different inoculum levels on the blade (10(8), 10(6) and 10(4)cfu/blade). The results also showed that the number of log cfu transferred per slice, during slicing, decreased logarithmically for both microorganisms at inoculum levels of 8 and 6log cfu/blade. The type of microorganism significantly influenced transfer coefficients (p<0.05) and there was an interaction between inoculum level and transfer coefficient for S. aureus (p<0.05), but not E. coli O157:H7. Finally, to describe bacterial transfer during slicing, two models (log-linear and Weibull) were fitted to concentration on slice data for both microorganisms (at 6 and 8 log cfu/blade), obtaining a good fit to data (R(2)⩾0.73).

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.

Growth of Listeria monocytogenes in pasteurized white asparagus was monitored at different storage temperatures (4, 10, 20, and 30 degrees C). Among the main microbial kinetic parameters, growth rate (mu) per hour was calculated at each temperature using the Baranyi-Roberts model. L. monocytogenes was able to grow at all temperatures, although at 4 degrees C only a slight increment of the microbial population was observed (approximately 1 log CFU/g) after 300 h of storage. Subsequently, two different secondary modeling approaches were proposed to study the relationship between mu and storage temperature: the Arrhenius and Ratkowsky models. Although both models properly described the data observed, smaller values of root mean square error (RMSE) and standard error of prediction (SEP) were obtained with the Ratkowsky model, providing a better goodness of fit (Ratkowsky model: RMSE = 0.010, SEP = 21.23%; Arrhenius model: RMSE = 0.026, SEP = 54.37%). The maximum population density (MPD) was calculated at each temperature studied. A clear dependence between MPD and temperature was found; lower temperatures produced lower values of MPD. This finding confirmed the Jameson effect, indicating that multiple hurdles in the food-processing chain plus lower temperatures reduced L. monocytogenes growth. Predicting the growth of L. monocytogenes along the food chain will help to reduce microbial risks associated with consumption of pasteurized white asparagus.

The impact of precultural temperature and pH on the distribution of the lag phase of individual Listeria monocytogenes cells was assessed during preincubation at 7 degrees C, using a dilution protocol to obtain single cells, and optical density measurements to estimate the individual lag phase. Firstly, the pure temperature effect (37, 15, 10, 7, 4 and 2 degrees C) was investigated on a subsequent growth at 7 degrees C and pH 7.4. Secondly, low precultural temperatures (10, 7 and 4 degrees C) were combined with a controlled pH at 7.4 and 5.7 with a subsequent growth at 7 degrees C and at different pH values (7.4, 6.0 and 5.5). For all temperature-pH combinations, the individual cell lag phase was determined using a three-phase linear growth model. It was observed that at low precultural temperatures (2, 4 and 7 degrees C), a high proportion of L. monocytogenes cells were able to grow at 7 degrees C with almost no lag phase, consequently, the resulting distributions were positively skewed. Beside this, the variability observed was lower than at higher precultural temperatures. Regarding the precultural pH effect, at pH 7.4 the mean values of the lag phases were shorter at lower preincubation temperatures; while at pH 5.7 small pH transitions produced shorter individual lag phases at all precultural temperatures. The quantification of the effect of precultural conditions on the individual cell lag phase duration would improve the accuracy of the existing growth models, especially when a series of processing and storage steps are linked together in a process model or exposure assessment. Distributions will be fitted to the data for every set of conditions, generating useful tools for further risk assessment purposes.

Different secondary modeling approaches for the estimation of Listeria monocytogenes growth rate as a function of temperature (4 to 30 degrees C), citric acid (0% to 0.4% w/v), and ascorbic acid (0% to 0.4% w/v) are presented. Response surface (RS) and square-root (SR) models are proposed together with different artificial neural networks (ANN) based on product functions units (PU), sigmoidal functions units (SU), and a novel approach based on the use of hybrid functions units (PSU), which results from a combination of PU and SU. In this study, a significantly better goodness-of-fit was obtained in the case of the ANN models presented, reflected by the lower SEP values obtained (< 24.23 for both training and generalization datasets). Among these models, the SU model provided the best generalization capacity, displaying lower RMSE and SEP values, with fewer parameters compared to the PU and PSU models. The bias factor (B(f)) and accuracy factor (A(f)) of the mathematical validation dataset were above 1 in all cases, providing fail-safe predictions. The balance between generalization properties and the ease of use is the main consideration when applying secondary modeling approaches to achieve accurate predictions about the behavior of microorganisms.

The combined effect of temperature (10.5 to 24.5 degrees C), pH level (5.5 to 7.5), sodium chloride level (0.25% to 6.25%) and sodium nitrite level (0 to 200 ppm) on the predicted specific growth rate (Gr), lag-time (Lag) and maximum population density (yEnd) of Leuconostoc mesenteroides under aerobic and anaerobic conditions, was studied using an Artificial Neural Network-based model (ANN) in comparison with Response Surface Methodology (RS). For both aerobic and anaerobic conditions, two types of ANN model were elaborated, unidimensional for each of the growth parameters, and multidimensional in which the three parameters Gr, Lag, and yEnd are combined. Although in general no significant statistical differences were observed between both types of model, we opted for the unidimensional model, because it obtained the lowest mean value for the standard error of prediction for generalisation. The ANN models developed provided reliable estimates for the three kinetic parameters studied; the SEP values in aerobic conditions ranged from between 2.82% for Gr, 6.05% for Lag and 10% for yEnd, a higher degree accuracy than those of the RS model (Gr: 9.54%; Lag: 8.89%; yEnd: 10.27%). Similar results were observed for anaerobic conditions. During external validation, a higher degree of accuracy (Af) and bias (Bf) were observed for the ANN model compared with the RS model. ANN predictive growth models are a valuable tool, enabling swift determination of L. mesenteroides growth parameters.

The combined effect of different temperatures (7 to 19 degrees C), pH levels (4.5 to 8.5), sodium chloride levels (0 to 8%), and sodium nitrite levels (0 to 200 ppm) on the predicted growth rate and lag time of Staphylococcus aureus under aerobic and anaerobic conditions was studied. The two predictive models developed, response surface (RS) and the Davey model, provided reliable estimates of the two kinetic parameters studied. The RS provided better predictions of maximum specific growth rate, with bias factors of 1.06 and 1.31 and accuracy factors of 1.17 and 1.37, respectively, in aerobic and anaerobic conditions. The Davey model performed more accurately for lag time, with a bias factor of 1.12 and an accuracy factor of 1.49, for both aerobic and anaerobic conditions. Predictive growth models are a valuable tool, enabling swift determination of Staphylococcus aureus growth rate and lag time. These data are essential for ensuring staphylococcus-related quality and safety of food products.

The application of Artificial Neural Networks (ANN) in predictive microbiology is presented in this paper. This technique was used to build up a predictive model of the joint effect of NaCl concentration, pH level and storage temperature on kinetic parameters of the growth curve of Lactobacillus plantarum using ANN and Response Surface Model (RSM). Sigmoid functions were fitted to the data and kinetic parameters were estimated and used to build the models in which the independent variables were the factors mentioned above (NaCl, pH, temperature), and in some models, the values of the optical densities (OD) vs. time of the growth curve were also included in order to improve the error of estimation. The determination of the proper size of an ANN was the first step of the estimation. This study shows the usefulness of an ANN pruning methodology. The pruning of the network is a process consisting of removing unnecessary parameters (weights) and nodes during the training process of the network without losing its generalization capacity. The best architecture has been sought using genetic algorithms (GA) in conjunction with pruning algorithms and regularization methods in which the initial distribution of the parameters (weights) of the network is not uniform. The ANN model has been compared with the response surface model by means of the Standard Error of Prediction (SEP). The best values obtained were 14.04% of SEP for the growth rate and 14.84% for the lag estimation by the best ANN model, which were much better than those obtained by the RSM, 35.63% and 39.30%, respectively. These were very promising results that, in our opinion, open up an extremely important field of research.

The shelf-life of ready-to-eat vegetable salads established by manufacturers is usually 7-14 days depending on the type of vegetable, and is determined by loss in organoleptic qualities. A more objective method to predict shelf-life and spoilage would be desirable. The present study monitored the evolution of spoilage organisms in a mixed salad of red cabbage, lettuce and carrot stored at 4 degrees C, 10 degrees C and 15 degrees C. Changes in carbon dioxide and oxygen concentrations and pH were also monitored. Predictive modelling was used to established a theoretical shelf-life time as a function of temperature. Lactic acid bacteria at levels of 10(6) cfu/g appeared to be related to both spoilage and theoretically-predicted shelf-life values.

The essential elements copper (Cu), iron (Fe), zinc (Zn) and manganese (Mn) were analyzed in fresh asparagus to determine the effects of the vegetative cycle of the plant on the micronutrient content. Asparagus samples were classified in two groups by diameter (< 11 mm and > 14 mm). Asparagus from a sample group with the same diameter were divided into two portions (apical and basal) according to distance from the tip. The concentrations of copper, iron, zinc and manganese increased during the vegetative cycle of the asparagus, mainly in the apical portion which showed significantly greater concentrations with respect to the basal portion. The > 14 mm diameter asparagus presented higher levels of copper, zinc and manganese, whereas the concentration of iron was greater in the < 11 mm diameter asparagus. The mean element levels were (mg/kg dry weight): Cu, 18.9 +/- 3.9; Fe, 91.7 +/- 33.7; Zn, 69.5 +/- 24.6 and Mn, 20.9 +/- 5.0).