INTEGRATED ASSESSMENT AND PREDICTIVE MODELING OF FOODBORNE PATHOGEN SURVIVAL IN THE STRAWBERRY SUPPLY CHAIN

Author

• Prachi Pahariya, Southern Illinois University CarbondaleFollow

Date of Award

8-1-2026

Degree Name

Doctor of Philosophy

Department

Agricultural Sciences

First Advisor

Choudhary, Ruplal

Abstract

Strawberries are widely consumed across the globe due to their nutritional value, sensory qualities, and health-promoting properties. They also play a significant role in the U.S. agricultural economy, ranking among the largest and highest-value fruit crops. However, they are highly susceptible to microbial contamination because of extensive handling during production, distribution, and storage. In addition, the lack of effective kill steps or routine post-harvest treatments, largely due to their sensitivity to quality degradation and fungal growth, further increases their vulnerability. These factors make strawberries highly prone to microbial contamination throughout the supply chain. The overall objective of this dissertation was to evaluate microbial safety risks associated with strawberries from production to post-harvest handling and to develop predictive and intervention-based strategies to enhance their safety. Specifically, the study aimed to (i) assess microbial contamination in collected farm samples by analyzing indicator microorganisms, (ii) model the survival behavior of foodborne pathogens under different storage temperatures, (iii) determine the influence of strawberry maturity stages on pathogen survival, and (iv) investigate the efficacy of non-thermal UV-C technologies for microbial reduction and model the post-treatment survival. In Chapter 3, microbial assessment of indicator microorganisms on environmental samples collected from local farms were performed. Indicator microorganisms were detected in strawberries, soil, water, and bins swabs samples which highlight the importance of implementing Good Agricultural Practices (GAP), particularly minimizing soil-fruit contact and ensuring irrigation water quality. In Chapter 4, the survival behavior of Escherichia coli and Listeria monocytogenes on strawberry surfaces was evaluated at different storage temperatures. Strawberries inoculated with the pathogens were stored at 4, 15, 25, and 37 °C to evaluate pathogen survival kinetics. The results showed that both pathogens survived under all tested temperature conditions, although reductions varied depending on storage temperature and time. E. coli exhibited an initial increase at higher temperatures, followed by gradual reductions, while greater reductions of up to approximately 2.8 log CFU/g were observed during extended storage at lower temperatures. L. monocytogenes showed moderate reductions ranging from approximately 1–1.8 log CFU/g across temperatures. The Weibull model effectively described the non-linear survival behavior of both bacteria and demonstrated good predictive performance for estimating microbial survival kinetics. Secondary models relating temperature to kinetic parameters were also developed and successfully validated at 10 °C, demonstrating good agreement between predicted and observed microbial counts. In Chapter 5, the influence of strawberry maturity stages on pathogen survival was investigated using unripe, semi-ripe, and ripe strawberries stored at 15, 25, and 37 °C. The results demonstrated that strawberry maturity significantly affected microbial persistence, with unripe strawberries generally showing greater pathogen reductions compared to semi-ripe and ripe strawberries. However, both pathogens survived across all maturity stages and storage conditions, emphasizing the importance of proper storage and handling practices throughout ripening. In addition, the effectiveness of UV-C mercury lamps and UV-C LEDs as non-thermal interventions for reducing microbial contamination on strawberries was evaluated in Chapter 6. Both treatments significantly reduced populations of E. coli and L. monocytogenes, with maximum reductions observed after 25 min of exposure. UV-C mercury lamps achieved reductions of up to 2.75 log CFU/g for E. coli and 2.63 log CFU/g for L. monocytogenes, while UV-C LEDs achieved reductions of 2.39 and 2.15 log CFU/g, respectively. During refrigerated storage following treatment, pathogen populations continued to decline until product spoilage. Predictive modeling further confirmed the suitability of Weibull models for describing microbial inactivation and survival patterns after UV-C treatment. In conclusion, this dissertation demonstrated that the microbial safety of strawberries is influenced by several interacting factors, including agricultural practices, storage temperature, fruit maturity, and post-harvest intervention technologies. The findings emphasize the importance of implementing Good Agricultural Practices (GAP), improving worker hygiene and irrigation water management, maintaining proper temperature, and adopting non-thermal technologies such as UV-C treatment to reduce microbial contamination risks associated with fresh strawberries. Furthermore, the predictive models developed in this research provide valuable tools for understanding pathogen survival behavior, supporting microbial risk assessment, and improving food safety management strategies for fresh produce industries.