|ZHOU, SIYUAN - Rutgers University|
|Sheen, Shiowshuh - Allen|
|PANG, YU-HSIN - Rutgers University|
|YAM, KIT - Rutgers University|
Submitted to: Journal of Food Protection
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 1/28/2015
Publication Date: 2/1/2015
Citation: Zhou, S., Sheen, S., Pang, Y., Liu, L.S., Yam, K.L. 2015. Modeling the impact of vapor thymol concentration, temperature and modified atmosphere condition on growth behavior of Salmonella spp. on raw shrimp. Journal of Food Protection. 78(2):293-301.
Interpretive Summary: Salmonella is a common contaminant on raw shrimp and causes foodborne illness outbreaks on a global basis. Salmonella might be sensitive to some natural antimicrobial compounds. In this report, the natural antimicrobial compound thymol (in vapor phase at 0, 0.8 and 1.6 mg/l)) and modified atmosphere (0.04 and 59.5 percent CO2) were found very effective for inhibiting the growth of Salmonella spp. at various storage temperatures (8, 12 and 16 degree C) which can be used to reduce illness risk from Salmonella on shrimp and other seafood. Predictive models were developed and validated to describe and predict the Salmonella growth potential with impact of thymol and modified atmosphere packaging. The predictive growth models which were developed will assist seafood processors provided safer products for consumers.
Technical Abstract: Salmonella spp. is a microorganism of concern, on a global basis, for raw shrimp. This research modeled the impact of vapor thymol concentration (0, 0.8 and 1.6 mg/l), storage temperature (8, 12 and 16 degree C) and modified atmosphere packaging (0.04 and 59.5 percent CO2) against the growth behavior of a Salmonella spp. cocktail (6 strains) on raw shrimp. Lag time (h) and maximum growth rate (log CFU/g/h), chosen as two growth indicators, were obtained through DMFit software and then developed into polynomial models as well as secondary models consisting of all three impact factors in “dimensionless” equations. The models were validated and results showed that lag time may be a better indicator than maximum growth rate for predicting microbial growth behavior, and the predictive values from polynomial models demonstrated a greater match to the observed experimental values than the secondary models. This information will provide the food industry with insights to the potential safety risk of Salmonella spp. growth on raw shrimp under stressed conditions.