Abstract
A quarter of all food that is produced has been estimated to be spoiled by microbes. Reducing this number will help in the challenge to keep feeding an increasing world population. Food industry aims to develop products that are safe by design to prevent spoilage and growth of pathogens before
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the end of the shelf life. However, spoilage and safety incidents do occur, leading to recalls, food waste and economic losses. To limit these losses, industrially processed food products are designed with preservation hurdles. This is a concept of applying a mixture of processing tools and adapting levels of key product parameters, such as pH, water activity or weak acids, in order to inactivate or inhibit growth of target microorganisms. As a result of current consumer trends, products are redesigned by using milder processing methods, less salt and without the use of preservatives. These developments put a tension on shelf-lives, because they favour microbial growth. To estimate the potential growth of microorganisms in food, industry uses microbiological risk assessments. These cover all scientific information, including processing parameters, chemical analysis of key product parameters, microbiological modelling and challenge test results. Microbiological modelling is essential to make these assessments quantitative. The degree of uncertainty and variability should be explicitly considered in these analyses to make them more realistic. In this thesis, inter- and intra-strain variability of the food spoilage fungi Paecilomyces variotii, Aspergillus niger and Penicillium roqueforti was studied with a focus on the former fungus. To this end, 108 P. variotii strains, 21 A. niger strains and 20 P. roqueforti strains were studied, which were isolated from various locations and substrates. The heat resistance of the asexual spores, the conidia, and variability at different levels was quantified. Results show that the heterogeneity in stress resistant conidia is considerable within the three different species, which is of high relevance for the food industry. Reduction in food loss and waste will contribute to global food security for the decades to come. This thesis contributes to a better understanding of inter- and intra-strain heterogeneity of P. variotii and, more general, the Eurotiales. This data can be used as input to improve predictive models in food industry that describe spoilage due to contamination by airborne conidia and more specifically, by P. variotii conidia. In the end, the most resistant spore defines if spoilage by a fungus can occur. Therefore, implementation of variability in microbiological modelling could lead to microbiological risk assessments with higher precision, which results in less recalls, less economic losses, and most importantly: less food waste.
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