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The long term goal of this Science Delivery Project (SDP) is the development of an integrated sentinel system that will be used to monitor agricultural water used in vegetable production (irrigation and processing water) for the presence of pathogenic microorganisms (Eschericha coli O157, and Salmonella spp.) indicator chemicals (total organic carbon) and organisms (Escherichia coli, fecal coliform bacteria, FRNA bacteriophages), and chemicals used to disinfect harvested produce (chlorine). This proposal is directly relevant to the following SCRI legislatively mandated focus area: 5. Methods to prevent, detect, monitor, control, and respond to potential food safety hazards in the production and processing of specialty crops, including fresh produce. The proposal is also applicable to the second category of SDP in the following area: (2) automation, robotics, sensor technology and precision agriculture for specialty crops. <BR> These focus areas will be addressed through the following research aims:<BR> Aim 1. To develop a sentinel based system using real-time testing of chemical indicators to monitor the quality of agricultural water; <BR> Aim 2. To develop sample preparation methods to allow large volumes of agricultural water to be tested; <BR> Aim 3. To develop testing methodology for rapid detection of vegetable associated indicator organisms and foodborne pathogens; <BR> Aim 4. To develop a risk assessment model to evaluate the types of processing water samples to test for the presence of pathogens and indicators. Outreach will include opportunities, with measurable outcomes, to educate end user groups traditionally under-represented in science delivery efforts and for small and medium sized producers.
NON-TECHNICAL SUMMARY: Protection of the US food system during the 21st century is becoming an increasing challenge. The CDC estimates that 76 million illnesses, 325,000 hospitalizations, and 5,000 deaths occur annually due to foodborne pathogens (Mead et al. 1999). The USDA projects the resulting economic burden at more than $7 billion/yr (USDA 2008). Fresh fruits and vegetables have increasingly become responsible for many cases of foodborne illness. For example, between 1990 and 2003, there were at least 554 foodborne outbreaks associated with vegetables, and these outbreaks resulted in approximately 28,000 illnesses and several deaths (CSPI 2006). Clearly, there is an acute need to develop effective solutions to reduce the burden of foodborne disease related to the production of fresh produce. Currently, sampling methodologies and diagnostic testing of fresh produce to determine the presence of foodborne bacterial pathogens is accomplished using a "haphazard" approach in which a multitude of environmental samples is tested using a variety of methods, to ascertain the presence of the target organisms. In some cases (i.e. leafy greens) the product itself is tested, but standardized parameters such as what determines a lot of product, sampling size (especially from fields that contain hundreds of acres of product), and sampling methods (when, where, and how to sample), are nonexistent. Transformative technologies are needed to address the foodborne outbreaks associated with produce. These technologies should be designed such that they will be useful to prevent, detect, monitor and control potential food safety hazards during the growth, harvest and processing of fresh produce. During this proposal, methodologies that allow for rapid, sensitive, and reliable detection of produce-borne contamination will be developed. The objective of this project is to develop and validate a suite of sample preparation and diagnostics that will be capable of detecting foodborne pathogens and indicators (biological and chemical) of fecal contamination. A risk assessment model will be developed that will determine the types of agricultural water samples that are most likely to contain the pathogens (E. coli O157 and Salmonella spp.), and/or indicator organisms (fecal coliforms, E. coli, FRNA phages) of interest. As part of the sample preparation aspect of the proposal, we will develop methodology to allow for large volumes of sample (i.e. 10 to 50 L of water) to be tested (i.e. we will develop methods to concentrate microorganisms from large volumes of water, in a manner that allows for subsequent detection of the microorganisms), followed by methodology to effect rapid testing of the indicators and pathogens, and real time detection of chemical indicators (total organic carbon) of water quality. Finally, we will install the most robust large volume sampling and testing methodologies at selected producers to demonstrate the ability of the tests to effectively monitor the microbial safety of agricultural water. Communication regarding the results of this project will be accomplished through symposia, digital bulletins, peer review publications, and targeted farm visits.<P>APPROACH: The following research aims will be conducted during completion of this project. Aim 1. To develop a sentinel based system using real-time testing of chemical indicators to monitor the quality of agricultural water. Commercially available, in-line sensors will be modified to detect chemical indicators of water quality such as total organic carbon. These sensors will be designed to constantly monitor the different vegetable processing water types in real time, as an early warning system, and if any deviations from acceptable limits are detected, the sensors will be modified to deliver results immediately over a wire-less network, to a PDA or smart phone. Aim 2. To develop sample preparation methods to allow large volumes of agricultural water to be tested. The sensitivity of testing will be greatly improved if large volumes of water are sampled. Several commercially available large volume sample preparation methodologies will be evaluated for their ability to concentrate microorganisms from large volumes of water. Additional "low tech" concentration methods will be developed during this proposal. All concentration methods will be optimized to allow for integration with downstream detection assays. Aim 3. To develop testing methodology for rapid detection of vegetable associated indicator organisms and foodborne pathogens. During this aim, we will develop diagnostic methods to detect the pathogens (E. coli O157, and Salmonella spp.) and indicator organisms that are concentrated using the sampling methodology from Aim 2. Several approaches will be taken here. The first approach will entail the validation of commercially available RT-PCR assays for E. coli O157 and Salmonella spp. The second approach will entail the adaptation and validation of commercially available fluorescent, luminescent or visual, field-based assays for detection of E. coli O157, Salmonella and indicator microorganisms. These tests will be adapted to be read in handheld devices, and will give a quick yes/no answer regarding the presence of the pathogens in question. A third approach will be to design microbial detection assays based on the principle of light scattering. These assays will be designed to specifically detect viable bacteria. The final approach will entail the development of Lateral Flow Devices (LFD) for detection of indicator organisms. Validation of the sampling methods and diagnostic assays will be conducted using publically accessible water samples including feedlot and dairy runoff, and microbially impaired rivers. Aim 4. To develop a risk assessment model to evaluate the types of processing water samples to test for the presence of pathogens and indicators. During this aim, we will conduct risk assessments aimed at detection of pathogens and indicators in different water samples associated with vegetable production. Sampling sites will include producers in southern Florida, Central/Northern Florida and California. The data obtained during this aim will be used to develop risk assessment models to aid in more efficient and reliable sampling and testing of water associated with vegetable production.