Abstract：
:The aim of this study was to develop a model to predict growth of Listeria in complex food matrices as a function of pH, water activity and undissociated acetic and propionic acid concentration i.e. common food hurdles. Experimental growth curves of Listeria in food products and broth media were collected from ComBase, the literature and industry sources from which a bespoke secondary gamma model was constructed. Model performance was evaluated by comparing predictions to measured growth rates in growth media (BHI broth) and two adjusted food matrices (zucchini purée and béarnaise sauce). In general, observed growth rates were higher in broth than in the food matrices which resulted in the model over-estimating growth in the adjusted food matrices. In addition, model outputs were more accurate for conditions without acids, indicating that the organic acid component of the model was a source of inaccuracy. In summary, a new predictive growth model for innovating or renovating food products that rely on multi-hurdle technology was created. This study is the first to report on modelling of propionic acid as an inhibitor of Listeria in combination with other hurdles. Our findings provide valuable insights into predictive model design and performance and highlight the importance of experimental validation of models in real food matrices rather than laboratory media alone.
journal_name
Food Microbioljournal_title
Food microbiologyauthors
Nyhan L,Begley M,Mutel A,Qu Y,Johnson N,Callanan Mdoi
10.1016/j.fm.2018.03.002subject
Has Abstractpub_date
2018-09-01 00:00:00pages
75-85eissn
0740-0020issn
1095-9998pii
S0740-0020(17)30963-2journal_volume
74pub_type
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