Survival of pathogens in low moisture foods

Rachon, G. (2018) Survival of pathogens in low moisture foods. DAgriFood thesis, University of Reading.

Abstract/Summary

This work investigated the survival and heat resistance of pathogens (Salmonella spp and Listeria monocytogenes) and a potential surrogate strain (E. faecium NRRL B-2354) in a selection of low moisture foods. The pathogens and the potential surrogate bacteria were inoculated into a selection of low moisture products (confectionery formulation, chicken meat powder, pet food and savoury seasoning, paprika powder and rice flour) and survival during storage as well as heat resistance were determined using glass vials and specially designed thermal cells. This study showed that pathogens can survive well in low moisture foods and survival was dependent on many factors such as water activity (aw), storage temperature and food composition. It was also shown that RpoS regulon plays an important role in Salmonella survival in low moisture foods. A strain lacking an active RpoS was significantly less viable in low moisture foods and significantly less heat resistant than the RpoS+ve strain. This study also showed that the use of E. faecium NRRL B-2354 as a surrogate is feasible for process validation although it has some limitations. It was shown that E. faecium NRRL B-2354 cannot be used as a surrogate in products containing high levels of sugar (confectionery powder) as Salmonella was significantly more heat resistant in this type of product than E. faecium NRRL B-2354. It was also shown that in paprika powder and in rice flour the two most resistant Salmonella strains (S. Enteritidis - PT 30 ATCC BAA-1045 and S. Typhimurium ST30; both RpoS +ve) in some conditions were more resistant than E. faecium NRRL B-2354. This study also showed that survival curves representing microbial survival during storage or during heat processes may not always be linear. In this study, concave upwards, concave downwards and linear curves were recorded and the Weibull model was used to fit raw data and precisely calculate the time required for 5 log reduction in viable numbers.

Additional Information	Published offprint removed from Appendix 2 due to publisher restrictions
Item Type	Thesis (DAgriFood)
URI	https://centaur.reading.ac.uk/id/eprint/78786
Divisions	Life Sciences > School of Chemistry, Food and Pharmacy
Date on Title Page	2017
Additional Information	Published offprint removed from Appendix 2 due to publisher restrictions
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