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利用现代技术评估大群组中个体产蛋鸡的活动和位置。

Assessing Activity and Location of Individual Laying Hens in Large Groups Using Modern Technology.

机构信息

Animal Behavior and Welfare Group, Department of Animal Science, Michigan State University, 474 S. Shaw Ln, East Lansing, MI 48824, USA.

Veterinary Public Health Institute, Vetsuisse Fakultät, University of Bern, Schwarzenburgstrasse 155, Liebefeld CH-3097, Switzerland.

出版信息

Animals (Basel). 2016 Feb 2;6(2):10. doi: 10.3390/ani6020010.

DOI:10.3390/ani6020010
PMID:26848693
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4773737/
Abstract

Tracking individual animals within large groups is increasingly possible, offering an exciting opportunity to researchers. Whereas previously only relatively indistinguishable groups of individual animals could be observed and combined into pen level data, we can now focus on individual actors within these large groups and track their activities across time and space with minimal intervention and disturbance. The development is particularly relevant to the poultry industry as, due to a shift away from battery cages, flock sizes are increasingly becoming larger and environments more complex. Many efforts have been made to track individual bird behavior and activity in large groups using a variety of methodologies with variable success. Of the technologies in use, each has associated benefits and detriments, which can make the approach more or less suitable for certain environments and experiments. Within this article, we have divided several tracking systems that are currently available into two major categories (radio frequency identification and radio signal strength) and review the strengths and weaknesses of each, as well as environments or conditions for which they may be most suitable. We also describe related topics including types of analysis for the data and concerns with selecting focal birds.

摘要

在大型群体中跟踪个体动物变得越来越可行,这为研究人员提供了一个令人兴奋的机会。以前,只能观察到相对难以区分的个体动物群体,并将它们组合成围栏级别的数据,但现在我们可以专注于这些大型群体中的个体行为者,并在最小的干预和干扰下跟踪它们在时间和空间上的活动。这一发展对于家禽业特别重要,因为随着从笼养向散养的转变,鸡群的规模越来越大,环境也越来越复杂。为了跟踪大型群体中个体鸟类的行为和活动,已经使用了许多不同的方法,取得了不同程度的成功。在使用的技术中,每种技术都有其相关的优点和缺点,这使得该方法在某些环境和实验中更适用或更不适用。在本文中,我们将目前可用的几种跟踪系统分为两大类(射频识别和无线电信号强度),并分别评估每种系统的优缺点,以及它们最适合的环境或条件。我们还描述了相关主题,包括数据分析类型和选择焦点鸟类的关注点。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2b0/4773737/a32c09c6f23f/animals-06-00010-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2b0/4773737/d480c973540a/animals-06-00010-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2b0/4773737/0cd1beffc834/animals-06-00010-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2b0/4773737/d49b1c945cd8/animals-06-00010-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2b0/4773737/fadaf0390a25/animals-06-00010-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2b0/4773737/a32c09c6f23f/animals-06-00010-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2b0/4773737/d480c973540a/animals-06-00010-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2b0/4773737/0cd1beffc834/animals-06-00010-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2b0/4773737/d49b1c945cd8/animals-06-00010-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2b0/4773737/fadaf0390a25/animals-06-00010-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/f2b0/4773737/a32c09c6f23f/animals-06-00010-g005.jpg

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