Location: Environmental Microbial & Food Safety Laboratory
Project Number: 8042-42610-001-000-D
Project Type: In-House Appropriated
Start Date: Feb 16, 2021
End Date: Feb 15, 2026
Objective:
Objective 1. Reduction of microbial contamination in pre-harvest agricultural environments through improvement of microbial water quality.
Sub-objective 1A. Develop and evaluate on-farm filtration technologies which can be implemented in a cost-effective manner to improve the microbial quality of surface irrigation water.
Sub-objective 1B. Identify and prioritize microbial, agricultural, seasonal, and spatiotemporal factors which affect the survival of enteric bacterial pathogens in soils and on plants introduced through contaminated irrigation water.
Objective 2. Develop and validate novel monitoring methods for the microbial quality of irrigation water sources.
Sub-objective 2A. Research the application of the UAV-based hyperspectral imaging to quantify lateral patterns of indicator and pathogen bacteria concentrations in irrigation ponds.
Sub-objective 2B. Quantify movement indicators and pathogens from bottom sediment to stream water column at base flow conditions.
Sub-objective 2C. Develop the microbial fate and transport modeling capabilities for APEX and the microbial index modeling method for site-specific evaluation of risks exceeding microbial water quality standards in surface water sources for irrigation.
Approach:
On-farm filtration technologies will be scaled up and modified based on previous sand and iron filtration designs. Designs will include the incorporation of the lytic bacteriophages as a pre-treatment before the filtration process or after the pre-filtration process. Survival of pathogens in water after filtration or undergoing no filtration will then be evaluated in soils amended with treated or untreated soil amendments, along with the transfer of these pathogens to growing food commodities. Hyperspectral imaging conducted by unmanned aerial vehicles will be used in conjunction with standard microbiological methods to quantify E. coli in ponds. Sensitive methods to recover bacterial fecal indicators and enteric pathogens will be used to characterize the movement of these microorganisms in ponds. Current modeling frames and software packages will then be used to model the fate and transport of these pathogens in ponds and creeks which serve as potential irrigation water sources.
