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 Environmental Microbial & Food Safety Laboratory: Beltsville, MD
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ARS Home Northeast Area Beltsville, Maryland (BARC) Beltsville Agricultural Research Center Environmental Microbial & Food Safety Laboratory Research





- Sharma, Manan
- Pachepsky, Yakov
- 2023
- 2022
- Publications
- Food Safety, (Animal and Plant Products) (108)

Research Project: Improving Pre-harvest Produce Safety through Reduction of Pathogen Levels in Agricultural Environments and Development and Validation of Farm-Scale Microbial Quality Model for Irrigation Water Sources **Location:
                            Environmental Microbial & Food Safety Laboratory** 2023 Annual Report **Objectives**
                                

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. **Progress Report**
                                

Progress was made on all objectives and their sub-objectives, which fall under National Program 108, Component 1 Foodborne Contaminants – Problem Statements 1: Characterize the Movement, Structure, and Dynamics of Microbial Populations; and 5: Develop, Validate, and Implement Intervention and Control Strategies to Reduce or Eliminate Pathogens in the Food System; and 6: Develop Predictive Microbiology Models and Informational Databases.

For Sub-objective 1A, data were analyzed examining the survival of E. coli in manure-amended soils in the Northeast, Southeast and Southwest U.S., including the application of organic amendments. Data were collected and evaluated on the survival of E. coli in manure amended soils in Georgia, Florida, and California. Data were also collected on the transfer of E. coli from soils to Romaine lettuce close to harvesting. 

For Sub-objective 1B, new prototypes of zero-valent iron sand filters were designed for inactivation of bacterial and parasitic microorganisms. Synthetic surface water formulations were designed at different turbidity levels to evaluate the performance of lytic bacteriophages and filtration on bacterial inactivation.

For Sub-objective 1B, analysis was performed to correlate the detection of Salmonella and Listeria monocytogenes in surface irrigation water by culture and by PCR methods. Results show negative PCR results are more predictive of negative culture results in ponds compared to river water.

For Sub-objective 2A, the effect of the drone flight altitude on image intensity was evaluated using narrow-band imaging of irrigation ponds. Efforts are progressing to relate ranges of bands to water quality parameters. For Sub-objective 2A, machine learning algorithms were formulated to relate imaging information to water quality data. Issues of imbalanced datasets, long-term influences, and spatial dependencies were addressed in collaborative work with domestic and international collaborators. For Sub-objective 2A, an improved quantitative monitoring technique was developed for the cyanotoxin microcystin. Persistent spatial patterns of microcystin concentrations were established for irrigation ponds in Maryland and Georgia. For the Sub-objective 2A, spatiotemporal variation of phytoplankton cell counts and photosynthetic pigment concentrations were used to observed trends which improved monitoring efforts. Pigment concentrations increased with water depth, indicating that algae should be monitored but at several water depths in ponds. 

For the Sub-objective 2C, progress was made in collaboration with University of Georgia and USDA-ARS SEWRC (Tifton, Georgia) in (a) data collection and analysis of spatiotemporal variability of E. coli concentrations in irrigation ponds (b) in monitoring the animal behavior with trail cams set near the irrigation pond to relate animal behavior to weather variables, (c) in monitoring  E. coli levels in aging cowpats as the source of E. coli in ponds. Data will be input into the APEX model for analysis. **Accomplishments**
                                

1. Improved methods for monitoring antibiotic resistant Escherichia coli in irrigation ponds. Irrigation waters may facilitate the spread of emerging antibiotic-resistant bacteria or genes to humans through contaminated fruits and vegetables. In groundbreaking work, ARS scientists from Beltsville, Maryland, researched spatiotemporal variation of tetracycline-resistant E. coli in irrigation ponds and established the existence of persistent spatial. The percentage of tetracycline-resistant E. coli levels were predicted by levels of nitrate, dissolved organic matter, and dissolved oxygen concentrations. Results of this work benefit farmers and water resource managers by indicating that antibiotic-resistant E. coli can be predicted by water quality parameters and a modified microbial testing regimen. 2. Established a database using microbial indicators for water quality monitoring. Escherichia coli and Enterococcus spp. are common indicators for microbial quality of irrigation water. ARS scientists in Beltsville, Maryland, established a unique database coupling E. coli and enterococci levels in sediment and the water column of the Conococheague creek in Pennsylvania. Results for this study emphasize that land use, seasonality, and sediment texture should be taken into account during water quality monitoring efforts. 3. Growth media does not affect persistence of Escherichia coli in soils. Examining the duration of E. coli survival in soils containing biological soil amendments of animal origin (BSAAO) is an important produce safety objective. Establishing the duration between planting of fruit and vegetable crops and harvest minimizes the transfer of pathogens from untreated BSAAO to fruit and vegetable crops. In a collaboration between ARS scientists in Beltsville, Maryland, and University of Florida scientists, it was determined that the microbiological method of preparing the E. coli culture (on agar plates, in liquid growth media, or in sterilize manure extract) did not affect the survival duration of E. coli. These findings provide flexibility to scientists in different U.S. regions looking to determine appropriate interval to minimize foodborne contamination between planting and harvest of fruits and vegetables. These efforts also support farmers in recycling nutrients from manure or composted manure in fruit and vegetable production. 4. Antibiotic resistant Escherichia coli percentages were low in surface and reclaimed waters in the Mid-Atlantic region of the U.S. Escherichia coli is a common indicator of the microbial quality of irrigation water. Extended spectrum beta-lactamase producing- (ESBL-) E. coli is an emerging pathogen. ARS scientists in Beltsville, Maryland, collaborated with scientists from multiple universities on a two-year survey conducting over 12 different sites to show that percentage of ESBL-producing E. coli was low (less than 3%) of the total E. coli recovered. These results indicate that ESBL-producing E. coli are not prominent in surface (river or pond) or reclaimed water sources, and are not currently a prominent hazard for irrigation water in the Mid-Atlantic region of the U.S. 5. Water from a first flush rainwater harvesting system did not contain bacterial foodborne pathogens. Rainwater harvesting is one of the sustainable agricultural practices that may benefit smaller or urban farmers. A first-flush system delivers water collected from rooftops into beds containing soil used to grow vegetables and produce. ARS scientists in Beltsville, Maryland, in collaboration with University of Maryland and Hood College investigators, analyzed 30 samples from this collection system at regular intervals. These results revealed that the prominent foodborne pathogens, Salmonella enterica and Listeria monocytogenes, were not detected. Results presented here indicated that harvested rainwater may be a useful source of irrigation water for small-scale growers. **Review Publications**
                            *Pyo, J., Pachepsky, Y.A., Kim, S., Abbas, A., Kim, M., Kwon, J., Ligaray, M., Cho, K. 2022. AI4Water v1.0: an open-source python package for modeling hydrological time series using data-driven methods. Geoscientific Model Development. 15(7):3021-3039.*
                                *Kim, S., Pachepsky, Y.A., Micallef, S., Rosenberg-Goldstein, R., Hashem, F., Parveen, S., Kniel, K., Sapkota, A., Sharma, M. 2023. Temporal stability of Salmonella enterica and Listeria monocytogenes in surface waters used for irrigation in the Mid-Atlantic United States. Journal of Food Protection. 86(4). Article 100058. https://doi.org/10.1016/j.jfp.2023.100058.*
                                *Kim, S., Paul, M., Negahban-Azar, M., Micallef, S., Rosengerg Goldstein, R., Hashem, F., Parveen, S., Sapkota, A., Kniel, K., Sapkota, A., Pachepsky, Y.A., Sharma, M. 2022. Persistent spatial patterns of Listeria monocytogenes and Salmonella enterica concentrations in surface waters: Empirical orthogonal function analysis of data from Maryland. Applied Sciences. 12:7526. https://doi.org/10.3390/app12157526.*
                                *Pachepsky, Y.A., Harriger, D.M., Panko Graff, C., Stocker, M.D., Smith, J.E. 2023. Coupled dynamics of fecal indicator bacteria in sandy sediments and the water column: a three-year high-frequency study at a Pennsylvania creek. Water, Air, and Soil Pollution. 234:398. https://doi.org/10.1007/s11270-023-06371-z.*
                                *Smith, J., Hill, R., Wolny, J., Stocker, M., Pachepsky, Y.A. 2022. Estimating phytoplankton concentrations in agricultural irrigation ponds from water quality measurements: a machine learning application. Journal of Phycology. 9(11):142.*
                                *Stocker, M.D., Smith, J.E., Pachepsky, Y.A. 2022. Depth-dependent concentrations of E. coli in agricultural irrigation ponds. Water. 14(14):2276. https://doi.org/10.3390/w14142276.*
                                *Stocker, M.D., Smith, J., Pachepsky, Y.A. 2023. Spatial variation of tetracycline-resistant E. coli and relationships with water quality variables in irrigation water: A pilot study. Journal of Applied Microbiology. 3(2):504-518. https://doi.org/10.3390/applmicrobiol3020036.*
                                *Solaiman, S., Handy, E., Brinks, T., Good, K., Bollinger, C., Sapkota, A.R., Sharma, M., Micallef, S.A. 2022. Escherichia coli phylogroup distribution and prevalence of extended spectrum ß-lactamase (ESBL) producers in U.S. Mid-Atlantic surface and reclaimed water. Environmental Microbiology. https://doi.org/10.1128/AEM.00837-22.*
                                *Morgado, M.E., Hudson, C.L., Chattopadhay, S., Ta, K., East, C.L., Purser, N., Allard, S., Ferrier, D.M., Sapokata, A.R., Sharma, M., Rosenburg-Goldstien, R. 2022. The effect of a first-flush rainwater harvesting irrigation system on E. coli and pathogen concentrations in irrigation water, soil, and produce. Science of the Total Environment. https://doi.org/10.1016/j.scitotenv.2022.156976.*
                                *Malayil, L., Ramachandran, P., Chattopadhyay, S., Allard, S.M., Bui, A., Butron, J., Callahan, M., Craddock, H., Murray, R., East, C.L., Sharma, M., Kniel, K.E., Micallef, S.A., Hashem, F., Gerba, C., Ravishankar, S., Parveen, S., May, E., Handy, E.T., Kulkarni, P., Anderson-Coughlin, B., Craighead, S., Gartley, S., Vanore, A., Duncan, R., Foust, D., Haymaker, J., Betancourt, W., Zhu, L., Mongodin, E., Sapkota, A., Sapkota, A.R. 2022. Variations in bacterial diversity and antibiotic resistance genes across diverse recycled and surface waters used for irrigation in the Mid-Atlantic and Southwest United States: A CONSERVE two-year field study. Journal of Environmental Science and Technology. https://doi.org/10.1021/acs.est.2c02281.*
                                *Vikram, A., Callahan, M.L., Woolston, J.W., Sharma, M., Sulakvelidze, A. 2022. Phage biocontrol for reducing bacterial foodborne pathogens in produce and other foods. Current Opinion in Biotechnology. 78. Article 102805. https://doi.org/10.1016/j.copbio.2022.102805.*


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