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Improving the Microbial Safety and Quality in Fresh Produce and Processed Products


The overall goal of this project is to provide data related to the microbial safety and spoilage risks associated with fresh produce production, packing and handling practices, fresh cut, processing, retail and consumer practices. This knowledge will enable the fruit, vegetable and nut industries to provide scientific backing to risks of contamination in their production practices and facilities and documentation for methods used to reduce these risks. Additionally, results from this work will allow the the food service industry and consumers to determine appropriate responses to reduce risks from consuming these products.<P>

Specific objectives include: <OL> <LI> To conduct surveillance, epidemiological and transfer studies in order to determine the points and sources during production and processing of specific fruits, vegetables and nuts where foodborne pathogens may be introduced and the effect that varying production, processing, and environmental factors may have on the contamination event <LI>To characterize microbial survival, growth and contamination mechanisms of foodborne pathogens on specific commodities of importance to Florida, the environment in which they are grown/processed, including microbial interactions within populations <LI>To develop and test mitigation and management strategies to control foodborne pathogen on these products and there surfaces they may come into contact with during production, packing or processing <LI> To evaluate the microbial causes and consequences of spoilage in processed fruit and vegetable products, and potential mitigation strategies to alleviate these causes </ol>

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NON-TECHNICAL SUMMARY: The US has seen a dramatic increase in the number of foodborne illnesses attributed to contaminated produce from 0.7% of all foodborne outbreaks in the 1970?s to 6% in the 1990?s (Sivapalasingam, 2004). The top five produce items associated with 75% of produce outbreaks are lettuce and leafy greens, tomatoes, melons, green onions and leafy herbs such as basil, cilantro and parsley (Ackers et al., 2998; Campbell et al., 2001; Cummings et al., 2001; Mohle-Boetani et al., 1999). With the exception of tomatoes (CDC, 2005; Toth et al., 2002), most of these outbreaks have not originated from Florida-grown products; however, each commodity is produced commercially in Florida. <P>

APPROACH: Bacterial recovery from the environment: Physical parameters at the sampling site including temperature (air and water), turbidity, pH and other appropriate will be recorded at each site. Isolates will be confirmed by growth on selective agar and by species-specific PCR. If appropriate, isolates will be further typed by conventional methods including phage typing, serotyping or sequencing. Bacterial cultures: Salmonella, Escherichia coli O157:H7, and Listeria monocytogenes strains that have been isolated from fresh produce, production environments, juice or other outbreaks associated sources are available in the PI laboratory and will be used for all experiments. If necessary, pathogens will be requested from outside sources Pathogen recovery from fresh produce: Fresh-cut produce will be placed in a Whirl-Pak filter bag with Dey-Engley (DE) neutralizing broth and stomached at the high-speed setting. When appropriate, a rinse method will be used. In this case the produce will be placed in a stomacher bag containing DE broth and the surface of the fruit will be rubbed by hand from outside of the bag for 60 s. Dilutions will be plated on non-selective and selective agar. Plates will be incubated at the appropriate time and temperature prior to enumeration. Microscopic evaluation of dye and bacteria penetration: GFP labeled bacteria will be grown in broth medium and prepared for inoculation as described above. An aliquot of inoculum preparation used to inoculate produce that will then be left to dry as appropriate. The depth of penetration will be observed and measured using fluorescent microscopy or confocal scanning electron microscopy. Microbiological modeling and risk assessment. Growth curves data can be fit to the model of Baranyi et al (1993) using the software DMFIT to obtain growth rates and lag times. Models to predict growth rate and lag time as a function of temperature will be developing using the square root model popularized by Ratkowsky et al (1991). Models will be fit to data using Microsoft Excel. Data for Quantitative Microbial Risk Assessment (QMRA) will be collected into Excel spread sheets to perform a QMRA. It will be translated into simple probability distribution functions, and combined using reasonable assumptions in Monte Carlo simulation software (@RISK, Palisades Decision, Newfield NY, or Analytica, Lumina, Los Gatos, CA). Following completion of the model, a sensitivity analysis can be performed to identify what factors exert the greatest influence on the model. Due to the important influence these factors have on the outcomes of the model, the uncertainty in them may need to be further refined.

Wright, Anita; Danyluk, Michelle
University of Florida
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