Location: Produce Safety and Microbiology ResearchTitle: Use of mathematic models to describe the microbial inactivation on baby carrots by gaseous chlorine dioxide
|GUAN, JIEWEN - Washington State University
|TANG, JUMING - Washington State University
|SABLANI, SHYAM - Washington State University
|RANE, BHARGAVI - Washington State University
Submitted to: Food Control
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 12/19/2020
Publication Date: 1/8/2021
Publication URL: https://handle.nal.usda.gov/10113/7219331
Citation: Guan, J., Lacombe, A.C., Tang, J., Bridges, D.F., Sablani, S., Rane, B., Wu, V.C. 2021. Use of mathematic models to describe the microbial inactivation on baby carrots by gaseous chlorine dioxide. Food Control. 123. Article 107832. https://doi.org/10.1016/j.foodcont.2020.107832.
Interpretive Summary: Contamination of fresh produce with pathogenic bacteria may occur at any point throughout food supply chain from farm to fork. The greatest risk to consumers, is when vegetables and fruits are consumed without being washed or cooked. Fresh produce is reported to be associated with the greatest number of foodborne illnesses, with the largest average number of foodborne illnesses per outbreak. Therefore, a more effective antimicrobial is in great need to help improve the food safety system for post-harvest processing. Gaseous chlorine dioxide (ClO2) has been considered as an alternative to bleach because of its higher effectiveness and lower toxicity. Additionally, it offers the efficacy on the irregular surfaces on fresh produce where is hard for liquid antimicrobials to reach. Numerous studies have demonstrated the effectiveness of gaseous ClO2 inactivating bacteria on fresh produce in a lab-scale. Before the method can be implemented in an industrial-scale, systematic research is needed to prepare for scale-up treatments. This study worked on two key aspects of the preparation. One is to find appropriate nonpathogenic surrogate bacteria that share similar response patterns to gaseous ClO2 with pathogens. This aims to mimic real pathogens including Shiga toxin-producing Escherichia coli (STEC) and Salmonella during the efficacy validation treatments in the food processing plants. Two is to model the inactivation kinetics of gaseous ClO2. The mathematical models were established to predict the time needed to inactivate bacteria on baby carrots. High and low ClO2 concentrations give the flexibility of short and long treatment times depending on the industrial needs. These results can be very useful when scaling up the gaseous ClO2 treatments to better secure food safety and prevent outbreaks.
Technical Abstract: This study investigated the behavior of Shiga toxin-producing Escherichia coli (STEC), Salmonella, and potential surrogate bacteria (nonpathogenic E. coli and attenuated Salmonella) subjected to gaseous chlorine dioxide(ClO2). Pathogenic and surrogate bacteria were separately inoculated on carrots (400 g) and treated with gaseous ClO2 at low (1 g) or high (6 g) ClO2 precursor inputs for 0, 15, 30, and 60 min in a 35 L enclosed chamber.Overall, significant log reductions (P < 0.05) were observed for all treatments after 30 min compared to untreated control. The Weibull model demonstrated a better fit to the experimental data (RMSE = 0.0–0.2),compared to the first-order model (RMSE = 0.3–0.9), which indicated a nonlinear trend. The Weibull model calculated times for a 3-log reduction at the high inputs (6 g ClO2 precursor) were 15.6 and 60.3 min for surrogate E. coli and Salmonella, and 24.6 and 31.3 min for the pathogen counterparts, respectively. Whereas at the low inputs (1 g ClO2 precursor), the times to achieve 3-log reductions increased to 110.3 and 816.6 min for surrogate E. coli and Salmonella, 805.3 and 409.5 min for pathogenic E. coli and Salmonella, respectively. This study provided useful treatment times and concentrations for an effective 3-log microbial reduction via modeling. In addition, potential surrogates were validated for future pilot-scale trials in the processing environment.