Abstract

The present study developed a model for effectively assessing the risk of spoilage caused by Aspergillus niger to identify key control measures employed in bakery supply chains. A white bread supply chain comprising a processing plant and two retail stores in Taiwan was selected in this study. Time–temperature profiles were collected at each processing step in summer and winter. Visual mycelium diameter predictions were validated using a time-lapse camera. Six what-if scenarios were proposed. The mean risk of A. niger contamination per package sold by retailer A was 0.052 in summer and 0.036 in winter, and that for retailer B was 0.037 in summer and 0.022 in winter. Sensitivity analysis revealed that retail storage time, retail temperature, and mold prevalence during factory cooling were the main influencing factors. The what-if scenarios revealed that reducing the retail environmental temperature by 1 °C in summer (from 23.97 °C to 22.97 °C) and winter (from 23.28 °C to 22.28 °C) resulted in a reduction in spoilage risk of 47.0% and 34.7%, respectively. These results indicate that food companies should establish a quantitative microbial risk assessment model that uses real data to evaluate microbial spoilage in food products that can support decision-making processes.

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