These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
Pubmed for Handhelds
PUBMED FOR HANDHELDS
Search MEDLINE/PubMed
Title: Modeling inactivation kinetics for Enterococcus faecium on the surface of peanuts during convective dry roasting. Author: Casulli KE, Igo MJ, Schaffner DW, Dolan KD. Journal: Food Res Int; 2021 Dec; 150(Pt B):110766. PubMed ID: 34863505. Abstract: Dry roasting can reduce Salmonella contamination on peanuts. While previous studies evaluated impact of product temperature, process humidity, product moisture, and/or product water activity on Salmonella lethality, no published study has tested multiple primary and secondary models on data collected in a real-world processing environment. We tested multiple primary and secondary models to quantify Salmonella surrogate, Enterococcus faecium, inactivation on peanuts. Shelled runner-type peanuts inoculated with E. faecium were treated at various air temperatures (121, 149, and 177 °C) and air velocities (1.0 and 1.3 m/s) for treatment times from 1 to 63 min. Peanut surface temperature was measured during treatment. Water activity and moisture content were measured, and E. faecium were enumerated after treatment. Microbial inactivation was modeled as a function of time, product temperature, and product moisture. Parameters (Dref, zT, zaw, zMC, and/or n) were compared between model fits. The log-linear primary model combined with either the modified Bigelow-type secondary model accounting for aw or moisture content showed improved fit over the log-linear primary model combined with the traditional Bigelow-type secondary model. The Weibull primary model combined with the traditional Bigelow-type secondary model had the best fit. All parameter relative errors were less than 15%, and RMSE values ranged from 0.379 to 0.674 log CFU/g. Incorporating either aw or moisture content in the inactivation models did not make a practical difference within the range of conditions and model forms evaluated, and air velocity did not have a significant impact on inactivation. The models developed can aid processors in developing and validating pathogen reduction during peanut roasting.[Abstract] [Full Text] [Related] [New Search]