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Abstract:

Bakery products represent a six billion euro market in France and a 40 billion euro market in Europe. With great volumes manufactured, these products do not avoid the current food waste phenomenon of which a significant part comes from mold spoilage.
In order to quantify this spoilage and tackle it, this PhD work aimed at developing a method to assess mold spoilage risk of bakery products. To do so, two relevant phenotypic responses were identified (i.e. lag time and radial growth rate). Four environmental factors having a significant impact on mold growth in bakery products, were then identified and ranked (i.e. water activity, storage temperature, organic acids and a “clean-label” preservative). More precisely, original Gamma-type predictive models were first developed to describe the factors’ effect on the selected phenotypic responses. Then these models were implemented in a probabilistic tool aiming at quantifying mold spoilage.
This tool, addressed to manufacturers, will enable i) to estimate realistically products’ best-before dates and ii) to select and adjust formulation factors to decrease the mold spoilage risk in bakery products.

Valorisation :

• Dagnas, S., E. Gauvry, B. Onno and J.-M. Membré 2015. Quantifying effect of lactic, acetic and propionic acids on growth of molds isolated from spoiled bakery products. Journal of Food Protection 78(9): 1689-1698. Ranking du JCR: Q2. https://doi.org/10.4315/0362-028X.JFP-15-046
• Dagnas, S., M. Gougouli, B. Onno, K. P. Koutsoumanis and J.-M. Membré 2015. Modeling red cabbage seed extract effect on Penicillium corylophilum: Relationship between germination time, individual and population lag time. International Journal of Food Microbiology 211: 86-94. Ranking du JCR: Q1. http://dx.doi.org/10.1016/j.ijfoodmicro.2015.07.008.
• Dagnas, S., M. Gougouli, B. Onno, K. P. Koutsoumanis and J.-M. Membré 2017. Quantifying the effect of water activity and storage temperature on single spore lag times of three moulds isolated from spoiled bakery products. International Journal of Food Microbiology 240: 75-84. Ranking du JCR: Q1. http://dx.doi.org/10.1016/j.ijfoodmicro.2016.06.013.
• Dagnas, S. and J. M. Membre 2013. Predicting and preventing mold spoilage of food products. Journal of Food Protection 76(3): 538-51. Ranking du JCR: Q2. https://doi.org/10.4315/0362-028X.JFP-12-349.
• Dagnas, S., B. Onno and J.-M. Membré 2014. Modeling growth of three bakery product spoilage molds as a function of water activity, temperature and pH. International Journal of Food Microbiology 186(0): 95-104. Ranking du JCR: Q1. http://dx.doi.org/10.1016/j.ijfoodmicro.2014.06.022.