FARM WATCH: Fight AbR with Machine learning and a Wide Array of sensing TeCHnologies
FARM WATCH: Fight AbR with Machine learning and a Wide Array of sensing TeCHnologies
批准号:
104986
负责人:
金额:
$94.7万
依托单位国家:
英国
项目类别:
Collaborative R&D
财政年份:
2019
资助国家:
英国
项目状态:
已结题
起止时间:
2019 至 --
中文摘要
禽肉是中国的第二大肉类来源,消费量迅速增长。为了满足需求,家禽养殖业广泛使用抗生素。中国是世界上食品生产中使用抗生素最多的人(23%)。抗生素的过度使用伴随着抗生素耐药性(ABR)的出现和通过直接接触、环境污染和食物消费向人类传播的人畜共患病的增加。对养鸡场细菌感染的有效和快速诊断可以减少对抗生素的需求,从而减少ABR。农场观察将识别和验证用于中国养鸡业的新诊断生物标记物。这些生物标志物将通过结合从生产线收集的不同信息来预测和检测细菌感染、ABR叛乱和人畜共患传播。它们将建立在对传染病流行途径的透彻了解、大规模数据收集以及机器学习和云计算推动的统计建模/数据挖掘的基础上。
英文摘要
Poultry is the 2nd most important source of meat in China, with consumption rapidly increasing. To meet demand, poultry production has made extensive use of antibiotics. China is the largest user of antibiotics forfood production in the world (23%). Overuse of antibiotics has been accompanied by increased appearance ofantibiotic resistance (ABR) and zoonotic transfer to humans via direct contact, environmental contamination and food consumption. Effective and rapid diagnostics of bacterial infection in chicken farming could reduce the need for antibiotics, thus reducing ABR. FARM WATCH will identify and validate new diagnostic biomarkers for use in the Chinese chicken farming industry. The biomarkers will be designed to predict and detect bacterial infection, insurgence of ABR, and zoonotic transfer to humans, by combining heterogeneous information collected from the production line. They will be developed from a thorough understanding of theepidemiological pathways of infection, from large-scale collection of data and statistical modelling / data mining powered by machine learning and cloud computing.
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