ISCF WAVE 1 AGRI TECH: Early Detection of Lameness in Dairy Cows through Multi-format Data Synthesis

ISCF WAVE 1 AGRI TECH：通过多格式数据合成早期检测奶牛跛行

• 批准号: BB/R021538/1
• 负责人: Martin Green
• 金额: $ 24.4万
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2018
• 资助国家: 英国
• 起止时间: 2018 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FR021538%2F1
• 关键词: ISCF; WAVE; AGRI; TECH; Early

Lameness in dairy cattle is increasingly recognised as a growing and significant economic and welfare problem in dairy nations around the world. Lameness remains at unacceptably high levels amongst the UK's 1.8 million dairy cattle; recent work suggests that approximately one in three cows are identifiably lame on any given day. Research has indicated that very early detection and treatment of lameness substantially reduces the prevalence of lameness which leads to increased milk production as well as enhanced cow welfare. Very early detection of lameness is difficult and technologies to identify the pre-clinical stages of disease would dramatically advance this area. The aim of this research is to synthesis data from multiple sources, including state-of-the-art thermography, activity/location monitoring and rumination sensors, to accurately predict pre-clinical onset of lameness in dairy cows such that early stage interventions are possible.

奶牛跛行越来越被认为是世界各地奶制品国家日益严重的经济和福利问题。在英国180万头奶牛中，跛足率仍然处于不可接受的高水平;最近的研究表明，在任何一天，大约三分之一的奶牛都是跛足的。研究表明，跛行的早期发现和治疗大大降低了跛行的患病率，从而增加了牛奶产量，提高了奶牛福利。跛足的早期检测是困难的，识别疾病临床前阶段的技术将大大推进这一领域。本研究的目的是综合来自多个来源的数据，包括最先进的热成像，活动/位置监测和反刍传感器，以准确预测奶牛跛行的临床前发作，以便早期干预成为可能。