Department of Genetics and Biotechnology, Faculty of Agricultural Sciences, Aarhus University, Tjele DK 8830, Denmark.
J Dairy Sci. 2010 Jan;93(1):249-59. doi: 10.3168/jds.2008-1721.
Detection of estrus in dairy cattle is effectively aided by electronic activity tags or pedometers. Characterization of estrus intensity and duration is also possible from activity data. This study aimed to develop an algorithm to detect and characterize behavioral estrus from hourly recorded activity data and to apply the algorithm to activity data from an experimental herd. The herd comprised of Holstein (n=211), Jersey (n=126), and Red Dane (n=178) cattle, with virgin heifers (n=132) and lactating cows in the first 4 parities; n=895 cow-parities, with a total of 3,674 activity episodes. The algorithm was based on deviations from exponentially smoothed hourly activity counts and was used to identify onset, duration, and intensity of estrus. Learning data included 461 successful inseminations with activity records over a 2-wk period before and after the artificial insemination. Rates of estrus detection and error rate depended on the chosen threshold level. At a threshold giving 74.6% detection rate, daily error rate was 1.3%. When applied to a subset of the complete data where milk progesterone was also available, concordance of days to first activity-detected estrus with the similar trait based on progesterone was also dependent on the chosen threshold so that, with stricter thresholds, the agreement was closer. A single-trait mixed model was used to determine the effects of systematic factors on the estrus activity traits. In general, an activity episode lasted 9.24h in heifers and 8.12h in cows, with the average strength of 1.03 ln units (equivalent to a 2.8-fold increase) in both age groups. Red Danes had significantly fewer days to first episode of high activity than Holsteins and Jerseys (29.4, 33.1, and 33.9 d, respectively). However, Jerseys had significantly shorter duration and less strength of estrus than both Red Danes and Holsteins of comparable age. The random effect of cow affected days to first episode of high activity and strength as well as estrus duration. Days from calving to first episode of high activity correlated negatively with body condition scores in early lactation. The results suggest that data from activity monitors could supply valuable information about fertility traits and could thereby be helpful in management of herd fertility. To establish the complementarities or interdependence between progesterone and activity measurements, further studies with more information from different sources of measuring estrus are needed.
奶牛发情的检测可以通过电子活动标签或计步器有效辅助。活动数据还可以对发情强度和持续时间进行特征描述。本研究旨在开发一种算法，以便从每小时记录的活动数据中检测和描述行为发情，并将该算法应用于实验牛群的活动数据中。该牛群由荷斯坦牛（n=211）、泽西牛（n=126）和红牛（n=178）组成，其中有初产奶牛（n=132）和头胎前 4 胎的泌乳牛；n=895 个奶牛胎次，总共有 3674 个活动期。该算法基于对每小时活动计数的指数平滑偏差，并用于识别发情的开始、持续时间和强度。学习数据包括 461 次成功的人工授精，在授精前和授精后两周内有活动记录。发情检测率和错误率取决于所选的阈值水平。在一个阈值为 74.6%的检测率时，每日错误率为 1.3%。当应用于一个子集的完整数据中，其中也有牛奶孕酮可用时，基于孕酮的第一天活动检测到发情的天数与类似特征的一致性也取决于所选的阈值，因此，随着阈值的严格，一致性更高。使用单性状混合模型来确定系统因素对发情活动性状的影响。一般来说，发情活动期持续 9.24 小时，在小母牛中为 8.12 小时，在两组年龄中平均强度为 1.03ln 单位（相当于 2.8 倍的增加）。红牛的第一次高强度活动期的天数明显少于荷斯坦牛和泽西牛（分别为 29.4、33.1 和 33.9 天）。然而，与可比年龄的红牛和荷斯坦牛相比，泽西牛的发情持续时间和强度明显更短。奶牛的随机效应影响到第一次高强度活动期的天数、发情持续时间和强度。从产犊到第一次高强度活动期的天数与泌乳早期的体况评分呈负相关。结果表明，活动监测器的数据可以提供有关生育性状的有价值信息，从而有助于牛群生育力的管理。为了确定孕酮和活动测量之间的互补性或相互依赖性，需要进行更多信息的进一步研究，来自不同发情测量源。
