Title
Meta-regression models describing the effects of added lactic acid bacteria on pathogen inactivation in milk and cheese
Date Issued
01 January 2020
Access level
metadata only access
Resource Type
conference paper
Author(s)
Silva B.N.
Teixeira J.A.
Cadavez V.
Instituto Politécnico de Bragança
Publisher(s)
EUROSIS
Abstract
Biopreservation methods based on the use of lactic acid bacteria (LAB) have been proposed as hurdles to increase the microbiological safety of many products, including fermented milk and cheese. For that reason, the objective of this research was: (i) to collect all available literature on Bacillus cereus, Clostridium perfringens, Listeria monocytogenes, Listeria innocua, Staphylococcus aureus and Escherichia coli inactivation in milk and cheese containing LAB; and (ii) to harmonise the retrieved data by constructing two separate meta-regression models that summarise LAB effectiveness. After systematic review, 426 observations on log reduction data were extracted from twenty studies. The results suggest that exposure time, antimicrobial and pathogen's inoculum concentrations and biopreservative method of application are related to LAB antimicrobial effectiveness. Furthermore, interaction between bacterium and exposure time was found, revealing the distinct LAB inhibitory effect on different pathogens for the same exposure time. One model also showed that, generally, higher microbial reduction can be achieved when LAB are added to milk, while application into cheese surface or mixture tend to present lower antimicrobial effect, even if still adequate for pathogen control. Globally, the results of these metaregression models highlight the opportunity for increased microbial safety of dairy fermented products by adding functional starter cultures.
Start page
151
End page
158
Language
English
OCDE Knowledge area
Tecnologías de bioprocesamiento, Biocatálisis, Fermentación Ciencia animal, Ciencia de productos lácteos
Scopus EID
2-s2.0-85101992654
Resource of which it is part
11th International Conference on Simulation and Modelling in the Food and Bio-Industry, FOODSIM 2020
ISBN of the container
978-949285913-6
Conference
11th International Conference on Simulation and Modelling in the Food and Bio-Industry, FOODSIM 2020
Sponsor(s)
Beatriz Nunes Silva acknowledges the financial support provided by the Portuguese Foundation for Science and Technology (FCT) through the PhD grant SFRH/BD/137801/2018. The authors are grateful to the Foundation for Science and Technology (FCT, Portugal) and FEDER under Programme PT2020 for financial support to CIMO (UID/AGR/00690/2019). Dr. Gonzales-Barron acknowledges the national funding by FCT, P.I., through the Institutional Scientific Employment Programme contract.
Sources of information: Directorio de Producción Científica Scopus