Agricultural Water Treatment and FSMA Compliance
Project Summary
Evaluated sanitizer efficacy in preharvest agricultural water collected from Florida farms under realistic conditions. Verified performance of chlorine-based sanitizers across contact times, temperatures, and concentrations. Applied kinetic modeling to estimate treatment conditions required to achieve FSMA’s 3-log microbial reduction target, supporting validation of agricultural water treatment strategies and risk-based water management decisions for produce safety. In related work, evaluated novel treatment approaches such as chitosan microparticles, achieving up to a 2-log reduction of microbial loads in fecally polluted water.
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Why It Matters
Agricultural water quality varies across production environments, directly impacting treatment efficacy and food safety outcomes. This work evaluates microbial control strategies under realistic field conditions rather than idealized laboratory matrices, providing data that are directly applicable to produce operations.
The results support FSMA-aligned validation of agricultural water treatment systems by identifying treatment conditions required to achieve target microbial reductions under variable conditions. This enables implementation of risk-based preventive controls grounded in quantitative performance data.
In multiple cases, viral targets demonstrated greater resistance than bacterial indicators under comparable treatment conditions, highlighting limitations of indicator-based validation approaches. These findings support the need for risk-based frameworks that account for pathogen-specific behavior in treatment validation.
Key Contributions
- Evaluated sanitizer efficacy in agricultural water from commercial farm environments
- Quantified treatment performance across contact time, temperature, and concentration
- Applied kinetic modeling to estimate conditions required to achieve FSMA 3-log reduction targets
- Assessed novel mitigation approaches, including chitosan microparticles, for microbial reduction
- Generated data to support risk-based agricultural water management and validation strategies
Peer-reviewed Publications
Ashlyn Lake, Yusuf Nuradeen Garba, Mya Maybank, Sarah Johnson, Christopher K. Mutch, Alexander Mueck, Simon Riley, Arie H. Havelaar, Naim Montazeri*. 2025. Effectiveness of chlorine against Tulane virus, a human norovirus surrogate, and Escherichia coli in agricultural water used for frost protection of produce. Journal of Food Protection, 88(6): 100524. https://doi.org/10.1016/j.jfp.2025.100524.
Candace Barnes, Rebecca Barber, Keith Schneider, Michelle Danyluk, Anita Wright, Melissa Jones, and Naim Montazeri*. 2021. Application of chitosan microparticles against human norovirus. Journal of Food Protection, 84(12): 2092–2098. https://doi.org/10.4315/jfp-21-220.
Relevant Skills and Methods
- Agricultural water microbiology
- Sanitizer validation and performance testing
- FSMA-aligned microbial reduction assessment
- Kinetic modeling
- R programming
- Experimental design under realistic environmental conditions
- Viral and bacterial reduction assessment using FDA BAM methods
- Risk-based interpretation of treatment performance
Data and Code Availability
Supporting datasets, modeling workflows, and analysis scripts are publicly available:
- Chlorine inactivation of enteric pathogens in agricultural water (2025)
- Zenodo (dataset and archived code): https://doi.org/10.5281/zenodo.15249558
- GitHub (modeling scripts and workflows): https://github.com/naimont/CONTACT_Obj1_m1/
- Zenodo (dataset and archived code): https://doi.org/10.5281/zenodo.15249558