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Ecuador is a country with limited nutritional information, with exception of some general studies supported by Food Agriculture Organization (FAO) Aims: to carry out a nutritional assessment of the diet of Ecuadorian immigrant population in Southern Spain to determine differences in food patterns and possible nutritional deficiencies.the nutritional assessment was based on a 24-h food recall survey applied to the Ecuadorian population residing in Seville and Córdoba (Spain) in combination with the application of national and international food composition data bases. Nutrient intake levels and fulfillment of Dietary Reference Intakes (DRIs) were estimated and statistically tested for social, sex, age and geographical factors.macronutrient distributions and nutrient intake levels in relation with DRIs were adequate in most cases. Importantly, Ecuadorian food habits were still present in immigrant population, with rice being the main energy source. Intakes levels were significantly different for several nutrients depending on age group, sex, place of residence and professional occupation. Comparison with previous nutritional data from Ecuador revealed a better nutritional status of immigrant population in Spain, though deficiencies in fiber, vitamin E, I and Se were detected in the diet of both populations. Nevertheless, data for these deficiencies were insufficient to be conclusive given both limitations in the food composition data bases (e.g. Se) and the lack of more adequate information tools for its assessment (e.g. long-term studies for vitamin E).the results in the present study evidenced that Ecuadorian immigrants in Spain showed more adequate food patterns that those reported for Ecuador. These data can be helpful to get further insight into the nutritional value of Ecuadorian diet and develop suitable nutrition intervention.Introducción: ecuador es un país con limitada información nutricional con la excepción de algunos estudios de carácter general realizados por FAO (Food Agriculture Organization). Objetivos: realizar una evaluación nutricional de la dieta de la población inmigrante ecuatoriana en el sur de España para determinar diferencias en los patrones alimentarios y posibles deficiencias nutricionales. Métodos: la evaluación nutricional se basa en un estudio de recordatorio de alimentos de 24 horas llevado acabo sobre la población ecuatoriana residente en Sevilla y Córdoba (España) en combinación con la aplicación de bases de datos nacionales e internacionales de composición de alimentos. Se estimaron los niveles de ingesta de nutrientes y el cumplimiento de las ingestas dietéticas de referencia (IDR) que se analizaron estadísticamente para los factores, genero, edad, profesión y ciudad. Resultados: según las IDR utilizadas, la distribución de macronutrientes y los niveles de ingesta de nutrientes fueron, en la mayoría de los casos, adecuadas. De manera destacada, se constató que los hábitos alimentarios ecuatorianos permanecieron en la población inmigrante, con el arroz como fuente principal de energía. Los niveles de ingesta fueron significativamente diferentes para diferentes nutrientes dependiendo del grupo de edad, sexo, lugar de residencia y ocupación profesional. Comparando estos datos con un estudio previo en Ecuador reveló que la población inmigrante en España presenta un mejor estado nutricional, si bien en ambas poblaciones se detectaron deficiencias en fibra, vitamina E, I y Se. En cuanto a estas deficiencias, los resultados no pueden considerarse concluyentes debido a limitaciones propias de las bases de datos (por ej. Se) y a la carencia de estudios adecuados que permitan una evaluación más precisa (por ej. estudios de larga duración para vitamina E). Conclusiones: estos resultados evidencian que la población inmigrante ecuatoriana presenta un patrón alimentario más adecuado que el documentado para la población Ecuador. Estos resultados pueden ser útiles para determinar el valor nutricional de la dieta ecuatoriana y desarrollar estrategias adecuadas de intervención nutricional.

En este trabajo se ha estudiado la evolucion de la biomasa y del carbono acumulado en los arboles de Quercus robur presentes en Galicia (noroeste de Espana). Se desarrollaron ecuaciones de estimacion de biomasa para arbol individual, las cuales utilizan como variable independiente el diametro normal. Se realizo un ajuste simultaneo para garantizar la aditividad, y se empleo la metodologia GMM (generalized method of moments) debido a la presencia de heterocedasticidad. Para estimar la evolucion de la biomasa de Q. robur en Galicia, las ecuaciones desarrolladas se aplicaron a los datos del numero de arboles por clase diametrica de los cuatro inventarios forestales nacionales (IFN) realizados hasta el momento. La concentracion media de carbono en los diferentes componentes arboreos considerados permitio estimar el carbono acumulado a partir de la biomasa. Aunque en Galicia ha disminuido la superficie de bosques puros de Q. robur, la evolucion del numero de arboles ha sido positiva en el periodo considerado (1972-2009). La evolucion de la biomasa y del carbono acumulado por esta especie tambien ha sido positiva en este periodo, pasando de 12.209.663 Mg de biomasa arborea en 1972 a 40.333.571 Mg en 2009, que se corresponde con 5.878.971 Mg y 19.415.955 Mg de carbono, respectivamente.

The influence of environmental conditions (temperature and pH) on the relationship between growth data expressed by absorbance (ABS) and data transformed to cell count (CC) measurements was studied, using calibration curves for predicting Listeria monocytogenes growth rate. With this aim, 19 calibration curves at different stress conditions were performed. A shift in the calibration curves was observed for the most stringent conditions, which affected cell viability. Subsequently, a Baranyi model was fitted to ABS and CC data to obtain growth rate (GRABS and GRCC) and a linear regression was performed. Absorbance was found to be a reliable technique for measuring microbial growth, as a strong relationship between GRABS and GRCC (R2= 0.9717) was observed. Furthermore, 2 different response surface models were developed to link GRABS and GRCC data with temperature, citric acid, and ascorbic acid. The goodness of fit of both ABS and CC models to the data was observed (RMSE = 0.0223 and 0.0221; SEP [%]= 29 and 25, respectively). Mathematical validation was carried out by calculating bias and accuracy factors, providing reasonably acceptable values for both absorbance and cell count models (Bf= 1.11 and 1.09, Af= 1.44 and 1.41, respectively). Predictions for GRCC were compared to data taken from Growth Predictor software at different temperatures and pH. Response surface model predictions showed that a suitable combination of preservative factors can inhibit L. monocytogenes growth. These results highlight accurate predictions of growth parameters of L. monocytogenes.

A linear logistic regression model was built to describe the growth/no growth boundaries of Listeria monocytogenes as a function of temperature (4–30 °C), pH (4.5–6), citric acid (0–0.4%) and ascorbic acid (0–0.4%). A fractional factorial design was followed among the factors considered and an inoculum size of 105 CFU/ml was used. Evaluation of growth was performed by optical density measurements in Bioscreen C (Labsystems, Finland), during 21 days. Data of optical density were transformed to log CFU/ml by using a calibration curve. Among the 232 combinations of factors tested, growth was observed in 133 and no growth in 99. The degree of agreement between predictions and observations was 97.8% concordant and 2.2% discordant. An internal validation with additional data within the interpolation region of the model was performed. The predictions were concordant in 94% of the cases, and all the wrong cases failed to the safe side of the boundary region. The probability of growth was strongly influenced at low temperatures (

Changes in sensory quality and proliferation of pathogenic and spoilage microorganisms in pasteurized white asparagus were measured as a function of storage temperature. The main sensorial attributes studied with regard to storage time were the general appearance of the product, turgidity and package swelling. There was a significant correlation between the deterioration in sensorial quality and microbial evolution, which was even more marked at higher temperatures. After 13 days at 4°C, 6 days at 10°C, 5 days at 20°C and 84 h at 30°C organoleptic deterioration and, consequently, the end of shelf life were detected. A significant growth of spoilage flora was observed, which might be responsible for the drop in pH levels during the final period of analysis (from 6.3 to 3.5–4 until 148 h). There was greater lactic acid bacteria (LAB) growth as the temperature and CO2 concentration increased, reaching a final concentration of approximately 108 CFU g−1 at all temperatures. We found no positive samples of Clostridium spp at 10 and 4°C. Among the species isolated at 20–30°C Clostridium septicum and in lower proportions Clostridium perfringens were encountered. The possible presence of Listeria monocytogenes was analyzed, but there were no positive samples in the final product. Pasteurized white asparagus maintains good organoleptic characteristics with a relatively long shelf-life at low temperatures, which leads to an adequate acceptance among consumers. Copyright © 2006 Society of Chemical Industry

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.

Temperature abuse during commercial transport and retail sale of leafy greens negatively impacts both microbial safety and product quality. Consequently, the effect of fluctuating temperatures on Escherichia coli O157:H7 and Listeria monocytogenes growth in commercially-bagged salad greens was assessed during transport, retail storage, and display. Over a 16-month period, a series of time-temperature profiles for bagged salads were obtained from five transportation routes covering four geographic regions (432 profiles), as well as during retail storage (4,867 profiles) and display (3,799 profiles). Five different time-temperature profiles collected during 2 to 3 days of transport, 1 and 3 days of retail storage, and 3 days of retail display were then duplicated in a programmable incubator to assess E. coli O157:H7 and L. monocytogenes growth in commercial bags of romaine lettuce mix. Microbial growth predictions using the Koseki-Isobe and McKellar-Delaquis models were validated by comparing the root mean square error (RMSE), bias, and the acceptable prediction zone between the laboratory growth data and model predictions. Monte Carlo simulations were performed to calculate the probability distribution of microbial growth from 8,122,127,472 scenarios during transport, cold room storage, and retail display. Using inoculated bags of retail salad, E. coli O157:H7 and L. monocytogenes populations increased a maximum of 3.1 and 3.0 log CFU/g at retail storage. Both models yielded acceptable RMSEs and biases within the acceptable prediction zone for E. coli O157:H7. Based on the simulation, both pathogens generally increased2 log CFU/g during transport, storage, and display. However, retail storage duration can significantly impact pathogen growth. This large-scale U.S. study-the first using commercial time/temperature profiles to assess the microbial risk of leafy greens-should be useful in filling some of the data gaps in current risk assessments for leafy greens.

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Obtaining data for improving food safety management systems is often required to assist decision making in a short timeframe, potentially allowing decisions to be made and practices to be implemented in real time. Collection, storage, and retrieval of new data regarding microbial responses in foods gain insight on the achievement of food safety management measures (i.e., food safety objectives, performance objectives), avoiding the increase of fail-dangerous events. The role of data bases in predictive microbiology has been widely demonstrated as useful tools for the development of computing software or tertiary models, which allow users to estimate growth, survival, or inactivation of food-borne pathogens and spoilage microorganisms in different food matrices. Additionally, the fast development of information and communication technologies (ICTs) has increased the software tools available in predictive microbiology. These tools, named tertiary models, are created for a wide range of applications and types of users: scientists, food operators, risk managers, etc. Although early versions were designed as standalone systems, nowadays on-line software is a major trend making tools available everywhere to everyone through the Internet. In this chapter, descriptive examples of data bases and software tools used in predictive microbiology are explained.

Food-borne pathogens associated with food products are a major concern of both industries and governments; thus, design of proper risk mitigation and elimination strategies is required. Currently, the great development showed by the scientific method and the tendency to optimize processes through its systematization has led to the necessity to unify and standardize food safety management processes. With this, it is not intended to abandon the approach that has prevailed historically, based on consultations of experts and use of ‘default values’ (conservative control limits and measures which establish the guarantee of the safety of a process or food), but complete foundations to improve its result through a structured approach based on scientific facts. In this respect, the World Trade Organization (WTO) (The WTO agreement on the application of sanitary and phytosanitary measures (SPS Agreement), 1995), according to the agreements of the General Agreement on Tariffs and Trade (GATT) and Sanitary and Phytosanitary Measures (SPS), proposes that to ensure fair and safe international trade, standards and harmonized food regulation need to be established, based on a scientific and rigorous approach, recommending for that the application of methods of risk assessment. Application of predictive models within a risk assessment framework is presented throughout this chapter.

New methodologies have been proposed to be incorporated in predictive microbiology in foods and quantitative microbial risk assessment (QMRA) to achieve more reliable models and facilitate predictive model applications. The meta-analysis is one of the proposed strategies focused on a systematic analysis of a large collection of data with the intention of generating standardized and summarized information to produce a global estimate. This data analysis approach can be applied to better understand the relationship between environmental factors and kinetic parameters or to input QMRA studies to assess the effect of a particular intervention or treatment concerning food safety. The emergence of systems biology is also affecting predictive microbiology, offering new and more mechanistic approaches to yield more reliable and robust predictive models. The so-called genomic-scale models are built on a molecular and genomic basis supported by experimental data obtained from the genomic, proteomic, and metabolomic research areas. Although the existing gene-scale models are promising regarding prediction capacity, they are still few and limited to specific model microorganisms and situations. Further research is needed, in the coming decades, to complete omics information and thus to produce more suitable models to be applied to real-world situations in food safety and quality.

Predictive models have been initially focused on the estimation of kinetic parameters, as described in the preceding chapter. However, other modeling approaches are often requested, especially when considering the transmission of a pathogen along the food chain or the probability that this pathogen can grow or survive at certain environmental conditions. This is the underlying reason why transfer and growth/no growth models presented a relevant development in predictive microbiology. These models can be effectively applied when presence/absence data are required, or in specific food processes. Alternatively, survival and transmission of microorganisms through food contact surfaces, environment and between different foods can be also estimated. Additional advantages, such as the extent of shelf life, or the effect of novel preservation methods in minimally processed foods provide a wider application of predictive microbiology. Bacterial transfer models and growth/no growth models are described in this chapter.

According to their structure, predictive models can be primary, secondary, or tertiary. This classification mainly depends on the final purpose and type of prediction generated. There has been a significant evolution in the past few years toward better understanding of microbial behavior in foods. Therefore, models that describe the biological process of microbial growth and inactivation have been subsequently developed. Also, fitting methods for linear and nonlinear regression together with goodness-of-fit indexes give us useful information about how the model is able to explain the observed data. Finally, models cannot be applied if a validation process is not previously accomplished, which typically consists of confirming the predictions experimentally by using any quantitative method. In this chapter, a comprehensive review of the most popular validation methods is provided.

One of the most critical steps when generating a predictive model is to correctly design an experiment and collect suitable microbial data. Experimental design will influence model structure and validation conditions. The survival and growth of microorganisms in foods is affected not only by the chemical composition of the food and its storage conditions but also by the food matrix. In this sense, a better quantification of the food structure effect has been studied throughout these years. Regarding the method of data collection, although plating count has been widely used (and still is used), there are rapid methods to obtain reliable and cost-effective data. These achievements were primarily based on turbidimetry, although other methods (microscopy, image analysis, flow cytometry, etc.) have arisen as novel approaches in the predictive microbiology field. These aspects are further discussed in this chapter.

En este trabajo se presenta el software MPC2.0©, diseñado para facilitar la aplicación de la metodologíade toma de decisiones AHP (Analytic Hierarchy Process),basada en la comparación por pares. El programa resultaespecialmente útil en las decisiones en las que seanecesario considerar numerosos y diferentes tipos decriterios (cuantificables o no) y/o muchas posiblesalternativas, así como también cuando sea preciso tener encuenta diferentes repeticiones de la decisión de uno odiferentes usuarios. MPC 2.0© facilita las comparacionespor pares de los criterios (primera fase de la metodología) yde las alternativas bajo cada criterio (segunda fase),minimizando los sesgos implícitos a las mismas. Permiteestablecer un esquema de criterios en dos niveles (criteriosy subcriterios, con la posibilidad de 40 elementos en cadauno) y la realización independiente de la comparación de loscriterios y de las alternativas. MPC 2.0© automatiza todoslos cálculos matriciales posteriores para asignar el peso decada alternativa y calcula el grado de inconsistencia de ladecisión (indica si la calificación establecida es lógica o no).MPC 2.0© integra un interface gráfico para facilitar laexposición de los resultados, así como un análisis desensibilidad, que ofrece al usuario información de lavariación de los resultados al modificar los pesos de loscriterios.

The Central Limit Theorem (CLT) is proposed as a means of understanding microbial risk in foods from a Public Health perspective. One variant of the CLT states that as the number of random variables, each with a finite mean and variance, increases (→∞), the distribution of the sum (or mean) of those variables approximates a normal distribution. On the basis of the CLT, the hypothesis introduced by this paper states that the Coefficient of Variation (CV) of the annual number of food-borne illness cases decreases as a result of a larger number of exposures (or servings) (n). Second-order Monte-Carlo analysis and classical statistics were used to support the hypothesis, based on existing risk models on Listeria monocytogenes in deli meat products focused on elderly people in the United States. Likewise, the hypothesis was tested on epidemiological data of annual incidence of salmonellosis and listeriosis in different countries (i.e. different n). Although different sources of error affected the accuracy of the results, both the Monte-Carlo analysis (in silico) and epidemiological data (in vivo), especially for salmonellosis, demonstrated that the CV of the annual number of cases decreased as n increased as stated by the CLT. Furthermore, results from this work showed that classical statistical methods can be helpful to provide reliable risk estimates based on simple and well-established statistical principles.

We present an example of the application of the AHP decision-making approach to forest management, by use of MPC© 2.0 software. The example considered is that of a forest services company interested in buying a timber harvester. The company had preselected four different machines as possible alternatives, and established 11 different criteria involved in the decision, grouped into four categories (economic, environmental, social and technical). The decision-making process was undertaken using MPC© 2.0 software tools, which enable establishment of criteria on two levels, independent pairwise comparison of criteria (first phase) and of alternatives under each criterion (second phase), repetition of the decision-making process by the same or different users, graphical display of the results on the computer screen, and sensitivity analysis En este trabajo se presenta un ejemplo de aplicación a la gestión forestal del método AHP de toma de decisiones mediante el software MPC© 2.0. Se considera el ejemplo de una empresa de servicios forestales interesada en adquirir una procesadora para la corta de madera, habiendo preseleccionado cuatro diferentes máquinas como posibles alternativas, y estableciendo 11 diferentes criterios implicados en la decisión, agrupados a su vez en cuatro categorías: económicos, ambientales, sociales y técnicos. Se presentan con el ejemplo las utilidades del programa MPC© 2.0, entre las que destacan la posibilidad de establecer un esquema de criterios en dos niveles, la realización independiente de la comparación por pares de criterios (primera fase) y de alternativas bajo cada criterio (segunda fase), la posibilidad de incluir diferentes repeticiones de la decisión por un mismo o diferentes usuarios, un interface gráfico para la exposición de los resultados y el análisis de sensibilidad de los mismos This study was financed by the Spanish Ministerio de Ciencia e Innovación (Project PSE-310000-2009-4 “Restauración y gestión forestal”, Subproject PSS310000-2009-23 “Decide”) and by the Xunta de Galicia (“Programa de Consolidación y Estructuración de Unidades de Investigación Competitivas 2011”), both cofunded through the European Union ERDF programme SI

The presence of heavy metals in big game meat may pose a risk to human health. The main objective of this paper is to carry out a risk assessment study (using a probabilistic and point-estimate approach) of lead intake by consumption of red deer and wild boar meat in Southern Spain based on Spanish data collected in the period 2003-2006. In general, the concentration levels found for wild boar meat (mean = 1291 µg kg(-1)) were much higher than those observed in red deer meat (mean = 326 µg kg(-1)). The results from a point-estimate risk assessment showed that the estimated average intake of lead among different exposure scenarios varied from 0.1 to 6.5 and from 0.3 to 38 µg kg(-1) week(-1) for red deer and wild boar meat, respectively; and from 0.3 to 35 µg kg(-1) week(-1) for individuals consuming both red deer and wild boar meat, and that the estimated intake of lead by consumption of big game meat differed significantly between hunters and non-hunters, it being higher for hunters. Besides this, results from the probabilistic risk assessment study corroborated the fact that risk is greater in hunter populations, reaching a maximum in individuals consuming only wild boar and both types of meat, with 0.4% and 0.2% of the population above the provisional tolerable weekly intake (PTWI), respectively. Likewise, the hunter populations consuming wild boar and both types of big game meat (red deer and wild boar meat) were exposed to the maximum lead level (56 µg kg(-1) week(-1)), which corresponded approximately to 224% of the PTWI. Further data and studies will be needed to give a complete risk estimation in which it will be crucial to consider the contribution to the lead intake level of other foods in the diet of both population groups.

The efficacy of an electrochemical treatment in water disinfection, using boron-doped diamond electrodes, was studied and its suitability for the fresh-cut produce industry analyzed. Tap water (TW), and tap water supplemented with NaCl (NaClW) containing different levels of organic matter (Chemical Oxygen Demand (COD) around 60, 300, 550 ± 50 and 750 ± 50 mg/L) obtained from lettuce, were inoculated with a cocktail of Escherichia coli O157:H7 at 10 5 cfu/mL. Changes in levels of E. coli O157:H7, free, combined and total chlorine, pH, oxidation–reduction potential, COD and temperature were monitored during the treatments. In NaClW, free chlorine was produced more rapidly than in TW and, as a consequence, reductions of 5 log units of E. coli O157:H7 were achieved faster (0.17, 4, 15 and 24 min for water with 60, 300, 500 and 750 mg/L of COD, respectively) than in TW alone (0.9, 25, 60 min and 90 min for water with 60, 300, 600 and 800 mg/L of COD, respectively). Nonetheless, the equipment showed potential for water disinfection and organic matter reduction even without adding NaCl. Additionally, different mathematical models were assessed to account for microbial inactivation curves obtained from the electrochemical treatments.

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 °C), and inoculum levels (2, 3 and 4 log 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 °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.

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 °C), pH (4.5; 5.0; 5.5; 6.0; 6.5 7.0 and 7.5) and water activity (Aw) (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 Aw. At 8 °C, S. aureus grew only at optimum levels of pH and Aw while at temperatures above 13 °C, growth of S. aureus was observed at pH = 4.5 and Aw = 0.96 (13 °C), 0.941 (16 °C) and 0.915 (19 °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 Aw was shown since growth was detected at Aw = 0.867 (T = 19 °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., This work was partly financed by MICINN AGL2008-03298/ALI, the Excellence Project AGR-01879 (Junta de Andalucía) and by European ERDF funding.

A practical approach was used to achieve specified food safety objectives (FSOs) by incorporating risk assessment methodology. A series of cross-contamination scenarios at the retail level were evaluated in a spreadsheet and ranked according to their level of risk, and the degree to which they exceeded an FSO for Listeria monocytogenes (100 CFU/g) was determined. Percentiles and analyses of variance were used to identify which scenarios would be most likely not to achieve the FSO. It was also possible to incorporate into the model the effect of additional risk management interventions (e.g., hand washing method) by using "what if" scenarios analysis. The highest risk corresponded to the use of the same gloves to handle contaminated meat and then sliced ham compared with the safer method of using different gloves to handle each product. Nevertheless, in all scenarios bacterial concentrations could be higher than 10(8) CFU/g. A significant lack of knowledge regarding the transfer rates of L. monocytogenes was revealed, which provided the model with an important uncertainty component. The "what if" scenarios analysis based on the scenario representing handling food with bare hands followed by hand washing (scenario 2) revealed that the hand washing procedure had less impact than expected. This study illustrates the use of scenarios to model the most effective food processes and thus provide risk managers with appropriate information on which to base their decisions.

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 ,1 0 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 6 log 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 P 0.73).

Corrigendum to “Modelling growth of Escherichia coli O157:H7 in fresh-cut lettuce submitted to commercial process conditions: Chlorine washing and modified atmosphere packaging” [YFMIC 33 (2013) 131e138] Guiomar D. Posada-Izquierdo *, Fernando Perez-Rodriguez , Francisco Lopez-Galvez , Ana Allende , Maria V. Selma , Maria I. Gil , Gonzalo Zurera a Department of Food Science and Technology, University of Cordoba, International Campus of Excellence in the Agri Food Sector ceiA3, Campus Rabanales, Edificio Darwin e C1, 14014 Cordoba, Spain Research Group on Quality, Safety and Bioactivity of Plant Foods, Department of Food Science and Technology, CEBAS-CSIC, 30100 Murcia, Spain

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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.

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).