AI Article Synopsis
- Predictive microbiology (PM) uses mathematical models and experimental data to forecast how microorganisms behave in food, particularly under specific conditions.
- PM is increasingly applied in winemaking to monitor yeast growth and assess contamination risks from harmful fungi, although its potential in this area is often overlooked.
- This review focuses on applications of PM in winemaking, including fermentation kinetics, modeling yeast and bacteria behavior, and managing toxin production and removal.
Article Abstract
Predictive microbiology (PM) is an essential element in food microbiology; its aims are the determination of the responses of a given microorganism combining mathematical models with experimental data under certain environmental conditions, and the simulation a priori of the growth/inactivation of a population based on the known traits of a food matrix. Today, a great variety of models exist to describe the behaviour of several pathogenic and spoilage microorganisms in foods. In winemaking, many mathematical models have been used for monitoring yeast growth in alcoholic fermentation as well as to predict the risk of contamination of grapes and grape products by mycotoxin producing fungi over the last years, but the potentialities of PM in wine microbiology are underestimated. Thus, the goals of this review are to show some applications and perspectives in the following fields: (1) kinetics of alcoholic and malolactic fermentation; (2) models and approaches for yeasts and bacteria growth/inactivation; (3) toxin production and removal.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8875561 | PMC |
| http://dx.doi.org/10.3390/microorganisms10020421 | DOI Listing |
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