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quantification 行为活动 牛舍

Methodology for quantifying the behavioral activity of dairy cows in freestall barns.

机构信息

Department of Agricultural and Environmental Sciences, Università degli Studi di Milano, I-20133 Milan, Italy.

出版信息

J Anim Sci. 2013 Oct;91(10):4899-907. doi: 10.2527/jas.2012-5554. Epub 2013 Aug 21.

DOI:10.2527/jas.2012-5554
PMID:23965385
Abstract

The objectives of this study were to 1) evaluate the validity of automated monitoring systems as assessment method for the behavioral activity of dairy cows compared with video recording, and 2) determine the sampling intervals required to obtain reliable estimates of the daily behavior. To determine lying, standing, and walking, 12 cows were equipped with automatic recording devices (IceTag = 12 cows, HOBO Pendant G = 5 cows), and their behavior was simultaneously recorded using a video recording system. The correspondence between the IceTag, HOBO logger, and video recording data was analyzed using 2 × 2 contingency tables, and we determined the sensitivity, specificity, and predictive value (positive and negative). Both types of loggers demonstrated high sensitivity (Sen ≥ 0.961) and specificity (Sp ≥ 0.951) for lying and standing behaviors with predictive values near 1.00. The HOBO logger can accurately describe the laterality of lying behavior, whereas the IceTag device inadequately recorded walking, with probability predictive values ≤ 0.303. Daily behaviors of the dairy cows were compared for 10 different sampling intervals (1 s, and 1, 2, 3, 4, 5, 10, 15, 30, and 60 min) collected by the IceTag, using linear regression. A strong relationship (R(2) ≥ 0.978) was found between the total lying times from data on a per-second basis and estimates obtained by 1, 2, 3, 4, 5, 10, and 15 min sampling intervals. The sampling intervals of 1 and 2 min were comparable for all aspects of lying behavior (R(2) ≥ 0.813; P > 0.05 for slope = 1, intercept = 0). Long sampling intervals (30 and 60 min) showed positive relationship for estimating time spent lying and standing (R(2) ≥ 0.774), but were inappropriate for predicting these behaviors, because they lacked accuracy and precision. Both the IceTag and HOBO logger accurately measured all aspects of lying and standing behavior. Reliable estimates of lying and standing time can be generated using relatively short interval lengths (e.g., 3, 4, 5, 10, or 15 min). Shorter sampling intervals (≤ 2 min) are required to accurately measure aspects of lying behavior such as number of lying bouts per day. The automated monitoring systems are time- and labor-saving tools that can be used by research or on farm to assess cow comfort related to lying behavior.

摘要

本研究的目的是

1)评估自动监测系统作为评估奶牛行为的方法的有效性,与视频记录相比;2)确定获得奶牛日常行为可靠估计所需的采样间隔。为了确定奶牛的卧、站和行走行为,12 头奶牛配备了自动记录设备(IceTag = 12 头奶牛,HOBO Pendant G = 5 头奶牛),并同时使用视频记录系统记录它们的行为。使用 2×2 列联表分析 IceTag、HOBO 数据记录器和视频记录数据之间的一致性,确定敏感性、特异性和预测值(阳性和阴性)。两种类型的数据记录器对卧、站行为的敏感性(Sen≥0.961)和特异性(Sp≥0.951)均较高,预测值接近 1.00。HOBO 数据记录器可以准确描述卧行为的偏侧性,而 IceTag 设备对行走行为的记录不足,概率预测值≤0.303。使用线性回归比较了 IceTag 在 10 个不同采样间隔(1 s 以及 1、2、3、4、5、10、15、30 和 60 min)收集的奶牛的每日行为。基于每秒的数据,发现总卧时间与 1、2、3、4、5、10 和 15 min 采样间隔的估计值之间存在很强的关系(R2≥0.978)。对于卧行为的所有方面,1 和 2 min 的采样间隔都具有可比性(R2≥0.813;斜率=1,截距=0,P>0.05)。长采样间隔(30 和 60 min)对估计卧和站时间具有正相关关系(R2≥0.774),但不适用于预测这些行为,因为它们缺乏准确性和精密度。IceTag 和 HOBO 数据记录器均可准确测量卧和站行为的各个方面。使用相对较短的间隔(例如,3、4、5、10 或 15 min)可以生成可靠的卧和站时间估计值。要准确测量每日卧次等卧行为方面,需要更短的采样间隔(≤2 min)。自动监测系统是一种省时省力的工具,可用于研究或农场评估与卧行为相关的奶牛舒适度。

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