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Integrating predictive models and sensors to manage food stability in supply chains
journal contributionposted on 2023-05-19, 14:46 authored by Mark TamplinMark Tamplin
Food products move through complex supply chains, which require effective logistics to ensure food safety and to maximize shelf-life. Predictive models offer an efficient means to monitor and manage the safety and quality of perishable foods, however models require environmental data to estimate changes in microbial growth and sensory attributes. Currently, several companies produce Time-Temperature Indicators that react at rates that closely approximate predictive models; these devices are simple and cost-effective for food companies. However, even greater outcomes could be realized using sensors that transfer data to predictive models in real-time. This report describes developments in predictive models designed for supply chain management, as well as advances in environmental sensors. Important innovation can be realized in both supply chain logistics and food safety management by integrating these technologies.
Publication titleFood Microbiology
Department/SchoolTasmanian Institute of Agriculture (TIA)
PublisherAcademic Press Ltd Elsevier Science Ltd
Place of publication24-28 Oval Rd, London, England, Nw1 7Dx
Rights statementCopyright 2017 Elsevier Ltd.