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ABSTRACT: The predominant species in maize in temperate climates is Fusarium graminearum, which produces the mycotoxins deoxynivalenol and zearalenone. Projected climate change is expected to affect Fusarium incidence and thus the occurrence of these mycotoxins. Predictive models may be helpful in determining trends in the levels of these mycotoxins with expected changing climatic conditions. The aim of this study was to develop a model describing fungal infection and subsequent growth as well as the formation of deoxynivalenol and zearalenone in maize in The Netherlands. For this purpose, a published Italian model was used as a starting point. This model is a mixed empiric-mechanistic model that describes fungal infection during silking (based on wind speed and rainfall) and subsequent germination, growth and toxin formation (depending on temperature and water availability). Model input uses weather parameters and crop management factors, such as maize hybrid, sowing date, flowering period and harvest date. Model parameter values were obtained by fitting these parameters to deoxynivalenol and zearalenone measurements in Dutch maize, using national mycotoxin data from the years 2002-2007. The results showed that the adapted model is capable of describing the trend in average deoxynivalenol and zearalenone levels over these years. Validation with external data is needed to verify model outcomes. It is expected that the current model can be used to estimate the effect of projected climate change on trends in deoxynivalenol and zearalenone levels in the coming years.
Food Additives and Contaminants - Part A Chemistry, Analysis, Control, Exposure and Risk Assessment 06/2012; 29(10):1572-80.
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ABSTRACT: The aim of this study was to investigate farm-level economic and technical factors that are associated with the use of antibiotics on pig farms. Identification of such factors, like farm size and net farm result, may help to increase epidemiological knowledge and to specify farm advice and policy making to reduce inappropriate use of antibiotics. The study used over 300 farm-year records collected during 2004 to 2007 from pig farms in the Netherlands. Data included economic and technical factors as well as antibiotic administration. Data were statistically analyzed for factors associated with antibiotic use, both for fattening pig and sow farms (piglets only), separately. The response variable was the average number of daily dosages per average pig year. Statistical analysis was performed on 16 and 19 potential explanatory factors for the fattening pig and sow farms, respectively. The results showed that, both on the fattening pig and sow farms, the average use of antibiotics increased from 2004 to 2006, but decreased during 2007, but the effect of year was not significant (P > 0.05). Use of antibiotics varied between individual farms. Large farm repeatability for the use of antibiotics in the different years was found. Factors associated (P < 0.05) with the use of antibiotics included: farm system, number of pigs, and population density in the region of the farm (for sow farms only). As these factors are easy to collect and to register, they can be used to specify farm advice and investigation, as well as for policy making. The majority of the technical and economic factors were not significantly (P > 0.05) related to the on-farm use of antibiotics. Therefore, it is recommended to focus future research on the potential role of socioeconomic factors associated with antibiotic use on pig farms.
Journal of Animal Science 06/2011; 89(6):1922-9. · 2.10 Impact Factor
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ABSTRACT: Salmonella serotype distribution can give insight in contamination routes and persistence along a production chain. Therefore, it is important to determine not only Salmonella prevalence but also to specify the serotypes involved at the different stages of the supply chain. For this purpose, data from a national monitoring program in the Netherlands were used to estimate the serotype distribution and to determine whether this distribution differs for the available sampling points in the broiler supply chain. Data covered the period from 2002 to 2005, all slaughterhouses (n = 22), and the following 6 sampling points: departure from hatchery, arrival at the farm, departure from the farm, arrival at the slaughterhouse, departure from the slaughterhouse, and end of processing. Furthermore, retail data for 2005 were used for comparison with slaughterhouse data. The following serotypes were followed throughout the chain: Salmonella Enteritidis, Salmonella Typhimurium, Salmonella Paratyphi B var. Java (Salmonella Java), Salmonella Infantis, Salmonella Virchow, and Salmonella Mbandaka. Results showed that serotype distribution varied significantly throughout the supply chain (P < 0.05). Main differences were found at the farm and at the slaughterhouse (within one stage), and least differences were found between departure from one stage and arrival at the next stage. The most prominent result was the increase of Salmonella Java at farm level. This serotype remained the most prominent pathogen throughout the broiler supply chain up to the retail phase.
Poultry Science 12/2009; 88(12):2695-701. · 1.73 Impact Factor
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ABSTRACT: This article presents detailed information on Salmonella prevalence throughout the broiler supply chain in The Netherlands, based on results from a national monitoring program. Data were collected during the period 2002 through 2005 and from six sampling points in the chain, covering hatchery up to and including processing. Trends in Salmonella prevalence over years and seasons were analyzed as well as the effect of slaughterhouse capacity on these trends. In addition, correlations between the occurrence of Salmonella at the various sampling points were calculated. The results showed a decreasing trend of Salmonella prevalence from 2002 through 2005 at all sampling points. A seasonal effect on the occurrence of Salmonella was found at the broiler farm, with a higher prevalence during the third and fourth quarter of the year (July through December). The higher the capacity of the slaughterhouse, the lower Salmonella prevalence on arrival at the slaughterhouse and the higher the prevalence at the end of slaughter and the end of processing. The detailed insights obtained in this study could be used to focus future field and experimental research on the prevention and control of Salmonella in the broiler supply chain. Results presented could also be used in risk assessment studies.
Journal of food protection 11/2008; 71(10):1974-80. · 1.94 Impact Factor
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ABSTRACT: After a national control program, data on Campylobacter prevalence in the broiler supply chain in the Netherlands were gathered for 3 sampling points: departure of broiler farm and arrival and departure of the slaughterhouse. Monitoring data from this control program for 2002 to 2005 were analyzed to find correlations and possible trends in the data. As expected, the greatest correlations were found between adjacent sampling points. A high correlation was expected between number of animals slaughtered and Campylobacter prevalence, because it is assumed that larger companies will have greater hygiene standards due to better implication of food safety regulations. However, statistical analysis showed that there was no clear correlation between company size and Campylobacter prevalence. Data analysis further identified an increasing trend in Campylobacter prevalence at departure of slaughterhouse from 2002 to 2005 with strong seasonality at all 3 sampling points. Measures to control Campylobacter, therefore, need to be reconsidered and possibly intensified to achieve a reduction in Campylobacter positives.
Poultry Science 11/2008; 87(10):2166-72. · 1.73 Impact Factor
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ABSTRACT: To quantify cross-contamination in the home from chicken to ready-to-eat salad.
Based on laboratory scenarios performed by de Jong et al. (2008), transfer rates were estimated for Campylobacter jejuni and Lactobacillus casei as a tracer organism. This study showed that transfer characteristics for both micro-organisms were comparable when washing regimes and transfer via items (cutting board, hands and knives) were compared. Furthermore, the study showed that the use of separate transfer rates for transfer from chicken to items and from items to salad will lead to an overestimation of campylobacteriosis risk. Applying good hygienic practices resulted in final levels of bacteria in the salad below the detection limit. Our study showed that it is important to include these data points in model fitting.
Results obtained in observational studies with Lact. casei can be translated to Camp. jejuni using the transfer rates obtained in this study. Cross-contamination by hands, cutting boards and knives was equally important.
Cross-contamination should be incorporated in microbiological risk assessments. The present study contributes to this by quantifying transfer of Camp. jejuni and Lact. casei from raw chicken via various contact surfaces into the ready-to-eat product.
Journal of Applied Microbiology 09/2008; 105(5):1392-401. · 2.34 Impact Factor
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ABSTRACT: The aim of the present study was to demonstrate how Performance Objectives (POs) for Salmonella at various points in the broiler supply chain can be estimated, starting from pre-set levels of the PO in finished products. The estimations were performed using an analytical transmission model, based on prevalence data collected throughout the chain in The Netherlands. In the baseline (current) situation, the end PO was set at 2.5% of the finished products (at end of processing) being contaminated with Salmonella. Scenario analyses were performed by reducing this baseline end PO to 1.5% and 0.5%. The results showed the end PO could be reduced by spreading the POs over the various stages of the broiler supply chain. Sensitivity analyses were performed by changing the values of the model parameters. Results indicated that, in general, decreasing Salmonella contamination between points in the chain is more effective in reducing the baseline PO than increasing the reduction of the pathogen, implying contamination should be prevented rather than treated. Application of both approaches at the same time showed to be most effective in reducing the end PO, especially at the abattoir and during processing. The modelling approach of this study proved to be useful to estimate the implications for preceding stages of the chain by setting a PO at the end of the chain as well as to evaluate the effectiveness of potential interventions in reducing the end PO. The model estimations may support policy-makers in their decision-making process with regard to microbiological food safety.
International Journal of Food Microbiology 08/2008; 128(1):22-7. · 3.33 Impact Factor
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ABSTRACT: The risk assessment study of Listeria monocytogenes in ready-to-eat foods conducted by the U.S. Food and Drug Administration is an example of an extensive quantitative microbiological risk assessment that could be used by risk analysts and other scientists to obtain information and by managers and stakeholders to make decisions on food safety management. The present study was conducted to investigate how detailed sensitivity analysis can be used by assessors to extract more information on risk factors and how results can be communicated to managers and stakeholders in an understandable way. The extended sensitivity analysis revealed that the extremes at the right side of the dose distribution (at consumption, 9 to 11.5 log CFU per serving) were responsible for most of the cases of listeriosis simulated. For concentration at retail, values below the detection limit of 0.04 CFU/g and the often used limit for L. monocytogenes of 100 CFU/g (also at retail) were associated with a high number of annual cases of listeriosis (about 29 and 82%, respectively). This association can be explained by growth of L. monocytogenes at both average and extreme values of temperature and time, indicating that a wide distribution can lead to high risk levels. Another finding is the importance of the maximal population density (i.e., the maximum concentration of L. monocytogenes assumed at a certain temperature) for accurately estimating the risk of infection by opportunistic pathogens such as L. monocytogenes. According to the obtained results, mainly concentrations corresponding to the highest maximal population densities caused risk in the simulation. However, sensitivity analysis applied to the uncertainty parameters revealed that prevalence at retail was the most important source of uncertainty in the model.
Journal of food protection 06/2007; 70(5):1137-52. · 1.94 Impact Factor
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ABSTRACT: Epidemiological data indicate that cross-contamination during food preparation in the home contributes noticeably to the occurrence of foodborne diseases. To help prevent such occurrences, the inclusion of a cross-contamination model in exposure assessments would aid in the development and evaluation of interventions used to control the spread of pathogenic bacteria. A quantitative analysis was carried out to estimate the probability of contamination and the levels of Salmonella and Campylobacter spp. on salads as a result of cross-contamination from contaminated chicken carcasses via kitchen surfaces. Data on the prevalence and numbers of these bacteria on retail chicken carcasses and the use of unwashed surfaces to prepare foods were collected from scientific literature. The rates of bacterial transfer were collected from laboratory experiments and literature. A deterministic approach and Monte Carlo simulations that incorporated input parameter distributions were used to estimate the contamination of the product. The results have shown that the probability of Campylobacter spp. contamination on salads is higher than that of Salmonella spp., since both the prevalence and levels of Campylobacter spp. on chicken carcasses are higher than those of Salmonella spp. It is realistic to expect that a fraction of the human exposure to Campylobacter spp., in particular, originates from cross-contamination in private kitchens during food handling. The number of human campylobacteriosis cases could be reduced either by reducing the degree of Campylobacter spp. contamination on chicken carcasses or by improving the hygiene in private kitchens. To eliminate the cross-contamination route, it is important to use separate surfaces or to properly wash the surfaces during the preparation of raw and cooked foods or ready-to-eat foods.
Journal of food protection 10/2004; 67(9):1892-903. · 1.94 Impact Factor
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ABSTRACT: Worldwide biofuel products have rapidly entered the market and consequently so did the availability of their by-products for feed production. A pro-active emerging risk system for biofuel by-products is essential in order to prevent the occurrence of emerging hazards in feed and livestock production. In the current study, two biofuel by-products were elaborated upon, namely Dried Distillers Grains with Solubles (DDGS) resulting from bioethanol production and microalgae slurry resulting from biodiesel production. A holistic approach was used in which both factors from within the feed chain as well as outside the feed chain were incorporated. A list of critical factors linking dynamics in the biofuel production chain with possible feed safety risks was established after consultation of experts in in-depth interviews. Subsequently, a workshop was organized to determine the most important critical factors. Indicators (signals that indicate a change in critical factors) and information sources were linked to these factors for the individual cases. Based on expert judgment, the most important critical factors identified for the two selected cases were: chain complexity, composition of the feed product, origin of raw materials and climate change. Ranking of the indicators showed that in both cases the number of chain stages was the most important general indicator for feed safety risks. The study showed that following this approach resulted in the selection of critical factors and indicators for emerging feed safety risks related to the use of biofuel by-products. Once critical values (upper and/or lower limits) are assigned to the indicators, the system can support decisions to take actions in an early stage in order to prevent emerging risks in feed due to the use of DDGS or microalgae slurry.
Food Policy. 36(3):421-429.
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ABSTRACT: A pro-active emerging risk identification system starts with the selection of critical factors related to the occurrence of emerging hazards. This paper describes a method to derive the most important factors in dynamic production chains starting from a gross list of critical factors. The method comprised the semi-quantitative evaluation of the critical factors for a relatively novel product on the Dutch market and a related traditional product. This method was tested in an expert study with three case studies. The use of group discussion followed by individual ranking in an expert study proved to be a powerful tool in identifying the most important factors for each case. Human behaviour (either producers’ behaviour or human knowledge) was the most important factor for all three cases. The expert study showed that further generalization of critical factors based on product characteristics may be possible.
Food Control.
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ABSTRACT: The aim of the present study was to demonstrate how Performance Objectives (POs) for Salmonella at various points in the broiler supply chain can be estimated, starting from pre-set levels of the PO in finished products. The estimations were performed using an analytical transmission model, based on prevalence data collected throughout the chain in The Netherlands. In the baseline (current) situation, the end PO was set at 2.5% of the finished products (at end of processing) being contaminated with Salmonella. Scenario analyses were performed by reducing this baseline end PO to 1.5% and 0.5%. The results showed the end PO could be reduced by spreading the POs over the various stages of the broiler supply chain. Sensitivity analyses were performed by changing the values of the model parameters. Results indicated that, in general, decreasing Salmonella contamination between points in the chain is more effective in reducing the baseline PO than increasing the reduction of the pathogen, implying contamination should be prevented rather than treated. Application of both approaches at the same time showed to be most effective in reducing the end PO, especially at the abattoir and during processing. The modelling approach of this study proved to be useful to estimate the implications for preceding stages of the chain by setting a PO at the end of the chain as well as to evaluate the effectiveness of potential interventions in reducing the end PO. The model estimations may support policy-makers in their decision-making process with regard to microbiological food safety.
International Journal of Food Microbiology.
