Modeling inactivation kinetics for Enterococcus faecium on the surface of peanuts during convective dry roasting

Kaitlyn E Casulli; Matthew J Igo; Donald W Schaffner; Kirk D Dolan

doi:10.1016/j.foodres.2021.110766

Modeling inactivation kinetics for Enterococcus faecium on the surface of peanuts during convective dry roasting

Food Res Int. 2021 Dec;150(Pt B):110766. doi: 10.1016/j.foodres.2021.110766. Epub 2021 Oct 18.

Authors

Kaitlyn E Casulli¹, Matthew J Igo², Donald W Schaffner³, Kirk D Dolan⁴

Affiliations

¹ Michigan State University, Department of Biosystems and Agricultural Engineering, 524 S. Shaw Ln., East Lansing, MI 48824, USA; Rutgers University, Department of Food Science, 65 Dudley Rd., New Brunswick, NJ 08901, USA. Electronic address: casullik@msu.edu.
² Rutgers University, Department of Food Science, 65 Dudley Rd., New Brunswick, NJ 08901, USA. Electronic address: mji27@scarletmail.rutgers.edu.
³ Rutgers University, Department of Food Science, 65 Dudley Rd., New Brunswick, NJ 08901, USA. Electronic address: don.schaffner@rutgers.edu.
⁴ Michigan State University, Department of Biosystems and Agricultural Engineering, 524 S. Shaw Ln., East Lansing, MI 48824, USA; Michigan State University, Department of Food Science and Human Nutrition, 469 Wilson Rd., East Lansing, MI 48824, USA. Electronic address: dolank@msu.edu.

PMID: 34863505
DOI: 10.1016/j.foodres.2021.110766

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 (D_ref, z_T, z_aw, z_MC, and/or n) were compared between model fits. The log-linear primary model combined with either the modified Bigelow-type secondary model accounting for a_w 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 a_w 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.

Keywords: Dry roasting; Enterococcus faecium; Inactivation; Modeling; Parameter estimation; Peanut; Salmonella.

Publication types

Research Support, Non-U.S. Gov't
Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

Arachis
Enterococcus faecium*
Kinetics
Salmonella