Alsaaod Maher, Fadul Mahmoud, Steiner Adrian
Clinic for Ruminants, Vetsuisse-Faculty, University of Bern, Switzerland.
Clinic for Ruminants, Vetsuisse-Faculty, University of Bern, Switzerland.
Vet J. 2019 Apr;246:35-44. doi: 10.1016/j.tvjl.2019.01.005. Epub 2019 Jan 31.
There is an increasing demand for health and welfare monitoring in modern dairy farming. The development of various innovative techniques aims at improving animal behaviour monitoring and thus animal welfare indicators on-farm. Automated lameness detection systems have to be valid, reliable and practicable to be applied in veterinary practice or under farm conditions. The objective of this literature review was to describe the current automated systems for detection of lameness in cattle, which have been recently developed and investigated for application in dairy research and practice. The automatic methods of lameness detection broadly fall into three categories: kinematic, kinetic and indirect methods. The performance of the methods were compared with the reference standard (locomotion score and/or lesion score) and evaluated based on level-based scheme defining the degree of development (level I, sensor technique; level II, validation of algorithm; level III, performance for detection of lameness and/or lesion; level IV, decision support with early warning system). Many scientific studies have been performed on levels I-III, but there are no studies of level IV technology. The adoption rate of automated lameness detection systems by herd managers mainly yields returns on investment by the early identification of lame cows. Long-term studies, using validated automated lameness detection systems aiming at early lameness detection, are still needed in order to improve welfare and production under field conditions.
现代奶牛养殖中对健康和福利监测的需求日益增加。各种创新技术的发展旨在改善动物行为监测，从而提高农场的动物福利指标。自动化跛行检测系统必须有效、可靠且实用，才能应用于兽医实践或农场环境。本文献综述的目的是描述目前用于检测牛跛行的自动化系统，这些系统最近已被开发并研究用于奶牛研究和实践。跛行检测的自动方法大致可分为三类：运动学方法、动力学方法和间接方法。将这些方法的性能与参考标准（运动评分和/或病变评分）进行比较，并根据定义发展程度的分级方案进行评估（一级，传感器技术；二级，算法验证；三级，跛行和/或病变检测性能；四级，带有预警系统的决策支持）。在一级到三级水平上已经进行了许多科学研究，但尚未有关于四级技术的研究。畜群管理者对自动化跛行检测系统的采用率主要通过早期识别跛足奶牛来实现投资回报。为了在田间条件下改善福利和生产，仍然需要使用经过验证的旨在早期检测跛行的自动化跛行检测系统进行长期研究。
