Jan. 1, 2023 - Dec. 31, 2024Amount Awarded
Mohit Verma, Ph.D.
Contamination of pathogens on fresh produce can lead to serious health issues. These pathogens often originate from animal feeding operations that are in proximity to fresh produce operations. Current methods for preventing such contamination are based on guidelines of maintaining a certain distance between animal operations and fresh produce operations. However, these guidelines do not provide information that is specific to a particular site. In this project, we will test a novel growers’ risk assessment biomarker investigative tool kit in locations that have nearby animal and produce operations. The tool detects DNA from feces of animals (swine, poultry, cattle) using a paper-based device and produces a color change (like a pH strip). The tool also incorporates data from local weather conditions and air quality to determine their influence on the contamination risk. The tool kit will be tested at three different locations and at two different times of the year to illustrate versatility. As a result of this project, fresh produce operations will have a deeper understanding of the factors that affect the risk around their operation. Mitigating risk from animal operations will ultimately improve food safety and reduce foodborne illnesses.
Animal operations in proximity to fresh produce operations pose a risk of contaminating fresh produce. Current guidelines for managing risk focus on setback distances but recognize that distance alone could be insufficient to minimize risk. Dust, bioaerosols, environmental conditions, and management practices can all affect the dispersal of contaminants. Yet, it is challenging to obtain spatial information about risk (e.g., in the form of heatmaps around animal operations) because there is a lack of simple field-deployable risk-assessment tools.
In this proposal, our overall goal is to validate our novel risk-assessment tool using testbeds that show a gradient of risk of contamination. We will generate a risk heatmap of testbeds that contain animal operations in proximity to fresh produce operations by quantifying fecal bioaerosols and environmental conditions (Objective 1). We will also demonstrate that microfluidic paper-based analytical devices can rapidly measure fecal bioaerosols for in-field evaluation of risk (Objective 2).
We will use Bacteroidetes as indicator organisms of fecal contamination, which is an approach called microbial source tracking. We have demonstrated that the DNA from Bacteroidetes can be detected in feces from humans, swine, poultry, and cattle. We have also shown that the levels of Bacteroidetes DNA are extremely low in lettuce fields that are meant to be safe (away from animal operations) and three orders of magnitude higher in areas next to animal operations. In this proposal, we will measure the levels of Bacteroidetes DNA in between these two extremes. We will use quantitative polymerase chain reaction as a lab-based method and loop-mediated isothermal amplification as a field-based method. To simplify our field-based method, we will use microfluidic paper-based analytical devices to incorporate all the reagents and provide a colorimetric response. During our field-based experiments, we will implement simple collection flags that we have developed to consistently sample the bioaerosols. In addition to the biological characterization, we will use mini-weather stations and air quality monitors to characterize environmental conditions and integrate all the data together.
Within objective 1, we will collect 2400 field-based samples and characterize the levels of Bacteroidetes DNA in them. We will develop a mobile application that will incorporate the biological data with environmental data and metadata about animal and produce operations to produce a risk heatmap.
Within objective 2, we will test 150 microfluidic paper-based analytical devices in our testbeds to demonstrate that they can detect bioaerosols in a user-friendly manner within an hour.
The anticipated outcome of this project is a user-friendly growers’ risk assessment biomarkers investigative tool kit that quantifies site-specific risk at the interface of animal and fresh produce operations.