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.
Keywords: Aspergillus niger; Bakery products; Risk assessment.
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