PREDICTIVE MODELLING APPROACH APPLIED TO BAKERY PRODUCTS

J.-M. Membré, M. Kubaczka, C. Chèné
Predictive microbiology has been focused on pathogenic bacteria, yet food spoilage by yeast or moulds causes serious deterioration, producing visible growth on surface, off-odours, off-flavours or slime. Yeast and moulds can be found in a wide variety of environments due to their capacity to utilise a variety of substrates and their relative tolerance of low pH and low water activity. The aim of this paper is to validate models obtained in laboratory conditions on the behaviour of Zygosaccharomyces rouxii and Penicillium brevicompactum as functions of pH, preservative substances (E 280, E 211, E 200) and humectants (glycerol, sorbitol, glucose). The two spoiling micro-organisms were isolated from bakery products. Predictive microbiology tools, particularly non linear growth models and growth / no growth interface concept, were adapted to sweet intermediate moisture foods. Various bakery products were made in a pilot process, with various pH and concentrations of preservative agents and humectants (a set of 24 kinds of cakes was generated) to appreciate the validity of laboratory data.
Membré, J.-M., Kubaczka, M. and Chèné, C. (2001). PREDICTIVE MODELLING APPROACH APPLIED TO BAKERY PRODUCTS. Acta Hortic. 566, 369-374
DOI: 10.17660/ActaHortic.2001.566.47
https://doi.org/10.17660/ActaHortic.2001.566.47
Bakery products, food safety, predictive models, Penicillium brevicompactum, Zygosaccharomyces rouxii
English

Acta Horticulturae