PolyCheck. Using advanced data science to design a better protocol to detect and monitor listeria in the food preparation industry
PolyCheck. Using advanced data science to design a better protocol to detect and monitor listeria in the food preparation industry
批准号:
10009393
负责人:
金额:
$13.07万
依托单位:
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2021
资助国家:
英国
项目状态:
已结题
起止时间:
2021 至 --
中文摘要
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英文摘要
Listeria is the deadliest food-borne disease in the UK. It is generally transmitted when food is harvested, processed, prepared, packed, transported or stored in environments contaminated with _L. monocytogenes_. These environments can be contaminated by raw materials, water, soil, and incoming air. Detecting and monitoring listeria effectively for companies engaged in food preparation and processing has proved elusive and difficult in the past decades.FoodScan (PolyChord's first project in food safety) has already proved capable of better monitoring the growth/death of enterococcus and salmonella than other standard methods. We will use what we have learnt in the FoodScan project to apply similar methodology to improving the monitoring of listeria monocytogenes. In this new approach, PolyChord will be closely collaborating with a leading food preparation company and Prof. Seamus Fanning - a world-renowned biologist - to develop a data driven approach for detecting and monitoring listeria monocytogenes in produce entering food processing factories in the UK. The outcoming result will be called PolyCheck, a new way of using data science to identify listeria in incoming foods and a major step towards establishing a better protocol for addressing Listeria in the food preparation industry.We use what we have learnt in the FoodScan project, applying our advanced data science, PolyChord, combined with cutting-edge of precision food science to develop a data driven approach to detecting and monitoring listeria. We will be working closely with a leading food preparation company and Prof. Seamus Fanning to combine environmental data with genomic sequencing. The outcoming result will be called PolyCheck, which is a practical step towards establishing a better protocol for addressing Listeria in the food preparation industry.
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国内基金
海外基金
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批准号:52073127
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项目类别:面上项目
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资助金额:58.0万元
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批准年份:2020
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负责人:Alidad Amirfazli
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依托单位:
Molecular Interaction Reconstruction of Rheumatoid Arthritis Therapies Using Clinical Data
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批准号:31070748
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项目类别:面上项目
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资助金额:34.0万元
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批准年份:2010
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负责人:Christine Nardini
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依托单位: