Schweinzer V, Gusterer E, Kanz P, Krieger S, Süss D, Lidauer L, Berger A, Kickinger F, Öhlschuster M, Auer W, Drillich M, Iwersen M
Clinical Unit for Herd Health Management in Ruminants, University Clinic for Ruminants, Department for Farm Animals and Veterinary Public Health, University of Veterinary Medicine Vienna, 1210, Vienna, Austria; Smartbow GmbH, Jutogasse 3, 4675, Weibern, Austria.
Clinical Unit for Herd Health Management in Ruminants, University Clinic for Ruminants, Department for Farm Animals and Veterinary Public Health, University of Veterinary Medicine Vienna, 1210, Vienna, Austria.
Theriogenology. 2019 May;130:19-25. doi: 10.1016/j.theriogenology.2019.02.038. Epub 2019 Mar 1.
Precision dairy farming technologies have tremendous potential to improve and support farmers in herd management decisions, particularly in reproductive management. Nowadays, estrus detection in cows is challenging and several supporting tools are available. In this study, a 3D-accelerometer integrated into an ear-tag (SMARTBOW, Smartbow GmbH, Weibern, Austria) was used for the detection of cows in estrus. Movement pattern based on accelerometer data were analyzed and processed by algorithms and machine learning, resulting in estrus alerts. For the evaluation of the system, reproductive performance data of 579 estrus events of multiparous cows were used to retrospectively evaluate the accuracy of estrus alerts generated by the accelerometer-based system and the overall performance of the system. Estrus events were classified as 'gold standard' events, if an estrus followed by AI resulted in pregnancy, and as 'recorded estrus' events, if two estrus events with an interval of 18-25 d were in the herd records, independent of whether estrus was followed by AI or pregnancy. In total, 316 'gold standard' events were matched with estrus alerts generated by the accelerometer-based system, resulting in a sensitivity of 97%. Furthermore, 263 'recorded estrus' events were compared with correct or incorrect estrus alerts by the system. Sensitivity, specificity, positive and negative predictive values, accuracy, and error rate for 'recorded estrus' events were 97%, 98%, 96%, 94%, 96%, and 2%, respectively. In summary, the SMARTBOW system is suitable for an automated detection of estrus events of multiparous cows in indoor housed dairy cows.
精准奶牛养殖技术在改善和支持养殖户进行畜群管理决策方面具有巨大潜力,尤其是在繁殖管理方面。如今,奶牛的发情检测具有挑战性,并且有多种辅助工具可供使用。在本研究中,一种集成在耳标中的三维加速度计(SMARTBOW,Smartbow GmbH,奥地利魏伯恩)被用于检测奶牛的发情情况。基于加速度计数据的运动模式通过算法和机器学习进行分析和处理,从而产生发情警报。为了评估该系统,利用579例经产奶牛发情事件的繁殖性能数据,对基于加速度计的系统生成的发情警报的准确性和系统的整体性能进行回顾性评估。如果发情后进行人工授精导致怀孕,则发情事件被分类为“金标准”事件;如果畜群记录中有间隔为18 - 25天的两次发情事件,则被分类为“记录发情”事件,无论发情后是否进行人工授精或怀孕。总共316例“金标准”事件与基于加速度计的系统生成的发情警报相匹配,灵敏度为97%。此外,将263例“记录发情”事件与系统正确或错误的发情警报进行比较。“记录发情”事件的灵敏度、特异性、阳性和阴性预测值、准确性和错误率分别为97%、98%、96%、94%、96%和2%。总之,SMARTBOW系统适用于自动检测室内饲养奶牛中经产奶牛的发情事件。