Polytechnic Institute of Braganza

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von Westerholt F.,University College Dublin | Gonzales-Barron U.,Polytechnic Institute of Braganza | Butler F.,University College Dublin
Microbial Risk Analysis | Year: 2016

The application of microbiological criteria related to foods has become well established for the protection of public health. Sampling plans will more likely detect a microorganism when the level of contamination is high. However, as the concentration of the microorganism drops, detection becomes more and more infrequent. Cronobacter spp. is an opportunistic pathogen that can occur infrequently and in low concentrations in powdered infant formula (PIF) with a distribution that is typically heterogeneous. This paper developed a Bayesian approach to quantify the uncertainty in the concentration of Cronobacter spp. clusters that may be present in a batch of PIF depending on the outcome of a sampling plan. Two approaches were developed. The first was a Bayesian methodology using a spreadsheet approach to develop the appropriate likelihood and posterior distributions based on an uninformed prior distribution. The second approach was similar but used an algebraic approach rather than a spreadsheet numerical approximation to characterise the uncertainty. Different sampling plans were considered based on the EC Microbiological Criteria for Cronobacter spp. When a zero positive test was the outcome of the sampling plans considered, the Bayesian analysis indicated that while the most likely outcome for all the sampling plans considered was zero clusters present, the analysis indicated that the true number of clusters present could be as high as several thousand clusters per tonne of powder depending on the sampling plan. The algebraic approach demonstrated that for zero or one positive tests, the uncertainty distribution could be approximated by a gamma distribution. Choice of the prior distribution influenced the level of uncertainty. The Bayesian approach demonstrates that even when zero positives are detected for a given sampling plan, there remains a considerable uncertainty in the true number of microorganisms that may be present undetected in a consignment of powder. © 2016 Elsevier B.V.


Xavier C.,Polytechnic Institute of Braganza | Gonzales-Barron U.,Polytechnic Institute of Braganza | Cadavez V.,Polytechnic Institute of Braganza | Muller A.,University of Porto
9th International Conference on Simulation and Modelling in the Food and Bio-Industry 2016, FOODSIM 2016 | Year: 2016

During beef carcass chilling, the eating quality of meat can be severely affected by either hot- or cold-shortening. With basis on previous knowledge that meat of optimal tenderness can be produced when rigor mortis (pH=6.0) is attained when carcass temperature falls between 12-35°C, the objective of this study was to predict meat quality from modelled pH/temperature decay descriptors and informative animal/carcass characteristics. Temperature and pH from a total of 103 beef carcasses were logged during 24 h post mortem, and subsequently modelled by exponential decay equations that estimated temperature (kT) and pH (kpH) decay rates. In addition, a number of pH/temperature decay descriptors were estimated from the fitted models. From linear models adjusted to each of these descriptors, it was found that, generally, hot carcass weight, age, gender and class (male, female, young animals) had significant influence on pH/temperature decay. Thus, bringing together the orthogonal variables kT and kpH, and the aforementioned animal/carcass characteristics as linear predictors of discriminant functions, a classification analysis was performed. While cold-shortened and hot-shortened carcasses were classified correctly for all samples, optimal quality carcasses were correctly classified in 87.5% of the samples.


Juneja V.K.,U.S. Department of Agriculture | Cadavez V.,Polytechnic Institute of Braganza | Gonzales-Barron U.,Polytechnic Institute of Braganza | Mukhopadhyay S.,U.S. Department of Agriculture | Friedman M.,U.S. Department of Agriculture
Food Control | Year: 2016

Health concerns have led to a search for natural plant-based antimicrobials. Ellagic acid has been shown to have antimicrobial activity against foodborne pathogens. The objective of this study was to assess the effect of a high-ellagic acid commercial pomegranate on the heat resistance of Escherichia coli O104:H4 in ground chicken. A full 24 factorial design was used, consisting of temperature treatment with four levels (55.0, 57.5, 60.0, and 62.5 °C) and pomegranate with four levels (0.0, 1.0, 2.0, and 3.0 wt/wt. % containing 70% ellagic acid). Experiments were conducted twice, providing a total of 32 survival curves. A three-parameter Weibull primary model was used to describe survival kinetics. Secondary models were then developed to estimate the shape parameter β (i.e., curvature representing susceptibility of cells to stress), scale parameter γ (i.e., time to reach the first decimal reduction) and the 5.0-log lethality time t5.0 (i.e., time to reach a 5.0-log reduction), all as polynomial functions of temperature and pomegranate powder concentration. The positive effect of pomegranate concentration on both β and γ demonstrated that the phenolic-rich pomegranate powder causes E. coli O104:H4 cells to become more susceptible to heat, increasing the steepness and concavity of the isothermal survival curves. It was estimated that the 5.0-log reduction time would reach a minimum at a pomegranate powder concentration of 1%, producing a 50% decrease in lethality time, in comparison to that without added pomegranate powder. Nonetheless, a mixed-effect omnibus regression further confirmed that the greatest difference in the thermal resistance of E. coli O104:H4 happened between tests with and without pomegranate powder. In fact, adding more than 1.0% pomegranate powder, at a constant temperature, resulted only in a marginal decrease in thermal resistance. Meat processors can use the model to design lethality treatments in order to achieve specific reductions of E. coli O104:H4 in ground chicken. © 2016.


Gonzales-Barron U.,University College Dublin | Gonzales-Barron U.,Polytechnic Institute of Braganza | Cadavez V.,Polytechnic Institute of Braganza | Sheridan J.J.,University College Dublin | Butler F.,University College Dublin
International Journal of Food Microbiology | Year: 2013

The effect of chilling on the occurrence of Salmonella on pig carcasses was investigated at study, abattoir and batch level by meta-analysis. Both the fixed-effects and random-effects model confirmed (p<0.05) the significant effect of chilling in decreasing Salmonella occurrence on pig carcasses; although the random-effects solution was preferred to account for the significant variability in effect size (p<0.001) estimated from the 13 primary studies considered, the 32 abattoirs surveyed, and the 51 sampled batches. Conservatively, it can be said that chilling reduces the Salmonella incidence on pig carcasses by a mean ratio of ~1.6 (95% CI: 1.0-2.6). Multilevel meta-analysis models investigating study characteristics that could explain the heterogeneity (τ2) in the true effect size among primary studies (τ2=0.578), among surveyed abattoirs (τ2=0.431), and among sampled batches (τ2=0.373), revealed that study size (represented by the moderating variables of 'total sample size' and 'number of batches sampled in an abattoir') and 'carcass swabbed area' have a significant impact (p<0.05) on the measured effect size of chilling. The fact that swabbed area explained between 56 and 62% and total sample size between 23 and 38% of the total heterogeneity in the chilling true effect size, indicates that differences in experimental design greatly affect our substantive conclusion about the effect of chilling on Salmonella occurrence. This inconsistency to elucidate the effect of chilling arises because of the many factors influencing both the performance of the chilling operation and the measurement itself. Meta-analysis was not only instrumental to show that small-size studies (i.e., only one batch sampled per abattoir, total number of sampled carcasses per batch<50) and small swabbed areas (<100cm2) lead to imprecise and even conflicting conclusions, but most importantly, enabled definition of the characteristics of a well-designed study having a minimum statistical power to produce precise results. A sound experimental design derived by multilevel meta-analysis consists of swabbing carcass areas of at least 500cm2 from 25 pre-chill and 25 post-chill carcasses from a single production batch, with a minimum of two batches sampled per surveyed abattoir. If the survey were to be conducted in more than one abattoir, the total sample size should not be less than 400. Two methods to test for publication bias, a common problem in meta-analysis, suggested that whilst the presence of unpublished small-size studies is probable, it is not likely that this would significantly bias the overall chilling effect estimated in this study. © 2013 Elsevier B.V.


Mussida A.,University College Dublin | Gonzales-Barron U.,University College Dublin | Gonzales-Barron U.,Polytechnic Institute of Braganza | Butler F.,University College Dublin
Food Control | Year: 2013

As in many cases, pathogenic microorganisms contaminate the food material as clusters or group of individual cells; the effectiveness of sampling plans based on mixture distributions representing bacterial agglomeration was assessed. In general, sampling plans that do not take into account such consideration lead to higher probabilities of accepting defective lots. Since quite often no scientific data are available in order to determine the degree of over-dispersion or clustering of the target microorganisms, in this theoretical study we compare the variance-to-mean ratio and the reciprocal of the exponent k of the negative binomial distribution (NB) as measures of dispersion. The mixture Poisson-logarithmic (Plog) model is proposed as a special case of the NB distribution, where the bacterial clusters are Poisson distributed while the individuals in each cluster follow a logarithmic distribution. In order to describe microbial data characterised by an excess of zero counts (1-π), we assess the zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) distributions as alternative statistical models. The Operating Characteristic (OC) curves generated on the basis of the zero-inflated distributions were compared for fixed values of the variance-to-mean ratio and the parameter π at any mean level of contamination and sample weight adopted. The results show that assuming fixed 1/. k and π for the NB and ZIP distributions, respectively, both models converge to a Poisson distribution at the producer's quality level. In contrast, the consumer's quality level is highly affected by assuming fixed values of 1/. k and π since it increases. The OC curves generated for the NB and ZIP distributions assuming fixed values of the variance-to-mean ratio at any mean level of contamination and sample weight adopted, reveal that both the consumer's and producer's quality level are affected, as they both increase. Within the ZINB distribution, a separate investigation is conducted to determine which parameters are mostly responsible for describing microbial over-dispersion. As a general conclusion, for the design of sampling plans based on any statistical distribution, OC curves that reflect microbial agglomeration should be constructed considering that variance is not constant but dependant on the level of microbial concentration of the lot. •The negative binomial (NB) distribution describes bacterial clustering in food.•The Poisson-logarithmic (Plog) is a negative binomial distribution.•The zero-inflated models describe proportions of food material free of contamination.•The degree of over-dispersion described by I affects both the PQL and CQL.•The sample weight affects the parameters of the statistical distribution employed. © 2013 Elsevier Ltd.


Gonzales-Barron U.,Polytechnic Institute of Braganza | Cadavez V.,Polytechnic Institute of Braganza | Butler F.,University College Dublin
Food Control | Year: 2014

Mixed Poisson distributions have been shown to be able to represent low microbial counts more efficiently than the lognormal distribution because of its greater flexibility to model microbial clustering even when data consist of a large proportion of zero counts. The objective of this study was to develop an alternative modelling framework for low microbial counts based on heterogeneous Poisson regressions. As an illustration, Poisson-gamma regression models were used to assess the effect of chilling on the concentration of total coliforms from beef carcasses (n=600) sampled at eight large Irish abattoirs. Three Poisson-gamma and three zero-modified (hurdle and zero-inflated) models were appraised with a series of random-effects variants in order to extract any variability in microbial mean concentration, dispersion and/or proportion of zero counts. Models were compared and validated in their ability to predict the coliforms counts on carcasses after chilling. In all five test batches, the hurdle Poisson-gamma distributions predicted the observed post-chill counts closer than the Poisson-gamma distributions. This is justified by the better capacity of the hurdle model to represent a higher proportion of zero counts, which were in fact observed in the post-chill batches. Thus, with a coded variable (pre-chill/post-chill) as treatment, and extracting the significant variability of batches nested in abattoirs for the coliforms mean concentration (σ2 u=2.68), the dispersion measure (σ2 v=2.39) and the probability of zero counts (σ2 w=0.89), the validated hurdle Poisson-gamma model confirmed that chilling has a decreasing effect on the viability of coliforms from beef carcasses, and that the concentration is reduced by an average (pre-chill to post-chill) factor of 2.2 (95% CI: 2.15-2.24) at batch level. The model also indicated that chilling increases the odds of producing a zero count from a carcass swab in about 13.5 times, and that the higher the coliforms concentration in a batch, the weaker the effect that chilling has to reduce such contamination on the beef carcasses. © 2013 Elsevier Ltd.


Juneja V.K.,U.S. Department of Agriculture | Gonzales-Barron U.,Polytechnic Institute of Braganza | Gonzales-Barron U.,University College Dublin | Butler F.,University College Dublin | And 2 more authors.
International Journal of Food Microbiology | Year: 2013

We investigated the combined effect of three internal temperatures (60, 65 and 71.1°C) and four concentrations (0.0, 0.1, 0.5 and 1% vol/wt) of two natural antimicrobials on the heat resistance of an eight-strain cocktail of Salmonella serovars in chicken meat. A complete factorial design (3×4×4) was used to assess the effects and interactions of heating temperature and the two antimicrobials, carvacrol and cinnamaldehyde. The 48 variable combinations were replicated to provide a total of 96 survivor curves from the experimental data. Mathematical models were then developed to quantify the combined effect of these parameters on heat resistance of starved Salmonella cells. The theoretical analysis shows that the addition of plant-derived antimicrobials overcomes the heat resistance of starvation-stressed Salmonella in ground chicken meat. The influence of the antimicrobials allows reduced heat treatments, thus reducing heat-induced damage to the nutritional quality of ground-chicken products. Although the reported omnibus log-linear model with tail and the omnibus sigmoid model could represent the experimental survivor curves, their discrepancy only became apparent in the present study when lethality times (D-values and t7.0) from each of the models were calculated. Given the concave nature of the inactivation curves, the log-linear model with tail greatly underestimates the times needed to obtain 7.0 log lethality. Thus, a polynomial secondary model, based on the sigmoid model, was developed to accurately predict the 7.0-log reduction times. The three-factor predictive model can be used to estimate the processing times and temperatures required to achieve specific log reductions, including the regulatory recommendation of 7.0-log reduction of Salmonella in ground chicken. © 2013.


Juneja V.K.,U.S. Department of Agriculture | Cadavez V.,Polytechnic Institute of Braganza | Gonzales-Barron U.,Polytechnic Institute of Braganza | Mukhopadhyay S.,U.S. Department of Agriculture
Food Research International | Year: 2015

The objective of this study was to assess the combined effects of temperature, pH, sodium chloride (NaCl), and sodium pyrophosphate (SPP) on the heat resistance of Escherichia coli O157:H7 in minced beef meat. A fractional factorial design consisted of four internal temperatures (55.0, 57.5, 60.0 and 62.5. °C), five concentrations of NaCl (0.0, 1.5, 3.0, 4.5 and 6.0. wt/wt.%) and SPP (0.0, 0.1, 0.15, 0.2 and 0.3. wt/wt.%), and five levels of pH (4.0, 5.0, 6.0, 7.0 and 8.0). The 38 variable combinations were replicated twice to provide a total of 76 survivor curves, which were modelled by a modified three-parameter Weibull function as primary model. The polynomial secondary models, developed to estimate the time to achieve a 3-log and a 5-log reduction, enabled the estimation of critical pH, NaCl and SPP concentrations, which are values at which the thermo-tolerance of E. coli O157:H7 reaches it maximum. The addition up to a certain critical concentration of NaCl (~. 2.7-4.7%) or SPP (~. 0.16%) acts independently to increase the heat resistance of E. coli O157:H7. Beyond such critical concentrations, the thermo-resistance of E. coli O157:H7 will progressively diminish. A similar pattern was found for pH with a critical value between 6.0 and 6.7, depending upon temperature and NaCl concentration. A mixed-effects omnibus regression model further revealed that the acidity of the matrix and NaCl concentration had a greater impact on the inactivation kinetics of E. coli O157:H7 in minced beef than SPP, and both are responsible for the concavity/convexity of the curves. When pH, SPP or NaCl concentration is far above or below from its critical value, the temperatures needed to reduce E. coli O157:H7 up to a certain log level are much lower than those required when any other environmental condition is at its critical value. Meat processors can use the model to design lethality treatments in order to achieve specific log reductions of E. coli O157:H7 in ready-to-eat beef products. © 2014 Elsevier Ltd.


Alves D.,Polytechnic Institute of Braganza | Costa A.F.,Polytechnic Institute of Braganza | Custodio D.,Polytechnic Institute of Braganza | Natario L.,Polytechnic Institute of Braganza | And 2 more authors.
Heroin Addiction and Related Clinical Problems | Year: 2011

Forty-nine heroin addicts in methadone maintenance treatment were evaluated with the aim of studying the anthropometric, nutritional and sociodemographic characteristics of these individuals. The BMI of heroin addicts who live with their spouse/partner is significantly higher compared with other housing situations. Most of the heroin addicts evaluated do not consume the minimum servings of fruits, vegetables and grains recommended by the food pyramid, and their consumption of sweets is high. This study reinforced the need for intervention programmes specifically designed to correct the poor nutritional status and diet of drug users, while considering this to be a major public health issue.


Xavier C.,Polytechnic Institute of Braganza | Gonzales-Barron U.,Polytechnic Institute of Braganza | Paula V.,Polytechnic Institute of Braganza | Estevinho L.,Polytechnic Institute of Braganza | Cadavez V.,Polytechnic Institute of Braganza
Food Research International | Year: 2014

Meat and meat products are the main vehicles of foodborne diseases in humans caused by pathogens such as Salmonella spp., Campylobacter spp., Listeria monocytogenes, Yersinia enterocolitica, verotoxigenic Escherichia coli (VTEC) and Staphylococcus aureus. In order to prioritise research on those microbial hazards, a meta-analysis study was conducted to summarise available information on the presence of such pathogens in meats produced in Portugal. By using a logit-transformed proportion as effect size parameterisation, a number of multilevel random-effect meta-analysis models were fitted to estimate mean occurrence rates of pathogens, and to compare them among meat categories (i.e., bovine meat, broiler meat, pork, minced beef and minced pork), and among meat product categories (i.e., intended to be eaten cooked, to be eaten raw and cured meats). The mean occurrence rate of Campylobacter in Portuguese broiler meat (40%; 95% CI: 22.0-61.4%) was about ten times higher than that of Salmonella (4.0%; 95% CI: 1.4-10.8%); although these levels were comparable to current EU ranges. Nevertheless, in the other meat categories, the meta-analysed incidences of Salmonella were slightly to moderately higher than EU averages. A semi-quantitative risk ranking of pathogens in Portuguese-produced pork pointed Salmonella spp. as critical (with a mean occurrence of 12.6%; 95% CI: 8.0-19.3%), and Y. enterocolitica as high (6.8%; 95% CI: 2.2-19.3%). In the case of the Portuguese meat products, the non-compliance to EU microbiological criteria for L. monocytogenes (8.8%; 95% CI: 6.5-11.8%) and Salmonella spp. (9.7%; 95% CI: 7.0-13.4%) at sample units level, in the categories 'intended to be eaten cooked' and 'to be eaten raw', were considerably higher than EU levels for ready-to-eat products in comparable categories. S. aureus was the pathogen of greatest concern given its high occurrence (22.6%; 95% CI: 15.4-31.8%) in meat products. These results emphasised the necessity of Portuguese food safety agencies to take monitoring, and training actions for the maintenance of good hygiene practices during the production of the great variety of traditional meat products. This meta-analysis study also highlighted important gaps of knowledge, and may assist food safety authorities in the prioritisation of microbiological hazards, and the implementation of essential food safety assurance systems at primary production. © 2013 Elsevier Ltd.

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