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Smart Agriculture ›› 2020, Vol. 2 ›› Issue (3): 21-36.doi: 10.12133/j.smartag.2020.2.3.202006-SA003

• 专题--农业人工智能与大数据 • 上一篇    下一篇

奶牛跛行自动识别技术研究现状与挑战

韩书庆1(), 张晶1, 程国栋1, 彭英琦2, 张建华1, 吴建寨1()   

  1. 1.中国农业科学院农业信息研究所/农业农村部农业大数据重点实验室,北京 100081
    2.四川农业大学 机电学院,四川 雅安 625014
  • 收稿日期:2020-06-08 修回日期:2020-07-08 出版日期:2020-09-30 发布日期:2020-12-09
  • 基金资助:
    国家重点研发计划资助(2017YFD0502006);中国农业科学院基本科研业务费专项(Y2018ZK46);中央级公益性科研院所基本科研业务费专项(JBYW-AII-2019-41)
  • 作者简介:韩书庆(1986-),男,博士,副研究员,研究方向为畜禽行为识别与畜牧物联网技术。E-mail:hanshuqing@caas.cn
  • 通讯作者: 吴建寨 E-mail:hanshuqing@caas.cn;wujianzhai@caas.cn

Current State and Challenges of Automatic Lameness Detection in Dairy Cattle

HAN Shuqing1(), ZHANG Jing1, CHENG Guodong1, PENG Yingqi2, ZHANG Jianhua1, WU Jianzhai1()   

  1. 1.Agricultural Information Institute of Chinese Academy of Agricultural Sciences/Key Laboratory of Agricultural Big Data, Ministry of Agriculture and Rural Affairs, Beijing 100081, China
    2.College of Mechanical and Electrical Engineering, Sichuan Agricultural University, Ya'an 625014, China
  • Received:2020-06-08 Revised:2020-07-08 Online:2020-09-30 Published:2020-12-09
  • corresponding author: Jianzhai WU E-mail:hanshuqing@caas.cn;wujianzhai@caas.cn

摘要:

奶牛跛行是奶牛发生肢蹄病的外在表现。人工识别跛行奶牛存在效率低、成本高、主观性强等问题。奶业对奶牛跛行自动识别技术需求日益强烈。本文从机器视觉技术、压力分布测量技术、可穿戴技术、行为分析技术和跛行分类技术5个方面,分析了奶牛跛行自动识别技术的原理、功能、特点及研究现状。总结发现,当前奶牛跛行自动识别技术研究大多集中在传感器研发和算法开发,而性能验证和决策支持的研究较少,面临的主要挑战包括高质量跛行识别数据获取难度大,缺乏早期跛行识别技术手段,奶牛个体差异干扰模型识别精度,牧场非结构化环境对识别系统性能要求高,以及技术应用效果难评估等。因此,为促进奶牛跛行自动识别技术的发展,建议推动牧场跛行监测数据共享,研究奶牛个体跛行判别模型的构建方法,开发融合跛行检测、体况评分等多功能的一体化智能通道,并分析评价跛行自动识别技术应用在保障动物福利、环境生态、粮食安全等方面的重要意义。

关键词: 跛行检测, 行为分析, 精准畜牧业, 机器视觉, 自动识别, 压力分布, 可穿戴技术

Abstract:

Lameness in dairy cattle could cause significant economic losses to the dairy industry. Detection of lameness in a timely manner is critical to the high-quality development of dairy industry. The traditional method is visual locomotion scoring by dairy farmers, which is low efficiency, high cost and subjective. The demand for automated lameness detection is increasing. The review was conducted to find out the current state and challenges of automatic lameness detection technology development and to learn from the latest findings. The current automatic lameness detection systems were reviewed in this paper mainly rely on five technologies or combinations thereof, including machine vision, pressure distribution measuring system, wearable sensor system, behavior analysis and classification; the principle, function and features of these technologies were analyzed. Machine vision technique is to extract feature variables (e.g. back arch, head bob, abduction, stride length, walking speed, temperature, etc.) from video recordings of cattle movement by image processing. Pressure distribution measuring system contains an array of load cells to sense gait variables, when dairy cattle are walking by. By using accelerometer with high frequency data collection, the gait cycle parameters can be extracted and used for lameness detection. By using wearable devices, the number of lying/standing bouts and their duration, the total time spent lying, standing and ruminating per day can be recorded for individual cattle. The lameness can also be detected by behavior analysis. Currently, most of these studies were in the stage of sensor development or validation of algorithm. A few studies were in the stage of validation of performance and decision support with early warning system. The challenges to apply automatic lameness detection system in dairy farm includes the difficulties of acquiring high quality data of lameness features, lack of techniques to detect early lameness, identification errors caused by individual gait differences among dairy cattle, difficulties to function well in unstructured environment and difficulties to evaluate the benefits. To accelerate the development of automatic lameness detection systems, recommendations are proposed as follows: ①promoting lameness data sharing and data exchange among dairy farms; ②developing individual-based lameness classification model; ③developing multifunctional smart station which can detect lameness, measure body condition score, weighing, etc; ④evaluating the significance of automatic lameness detection to the dairy industry from the perspective of animal welfare, environment and food safety.

Key words: lameness detection, behavior analysis, precision livestock farming, machine vision, automated dection, pressure distribution, wearable sensor system

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