Fadul-Pacheco Liliana, Liou Michael, Reinemann Douglas J, Cabrera Victor E
Department of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA.
Department of Statistical Science, University of Wisconsin-Madison, Madison, WI 53706, USA.
Animals (Basel). 2021 Apr 24;11(5):1229. doi: 10.3390/ani11051229.
We have applied social network analysis (SNA) to data on voluntary cow movement through a sort gate in an automatic milking system to identify pairs of cows that repeatedly passed through a sort gate in close succession (affinity pairs). The SNA was applied to social groups defined by four pens on a dairy farm, each served by an automatic milking system (AMS). Each pen was equipped with an automatic sorting gate that identified when cows voluntarily moved from the resting area to either milking or feeding areas. The aim of this study was two-fold: to determine if SNA could identify affinity pairs and to determine if milk production was affected when affinity pairs where broken. Cow traffic and milking performance data from a commercial guided-flow AMS dairy farm were used. Average number of milked cows was 214 ± 34, distributed in four AMS over 1 year. The SNA was able to identify clear affinity pairs and showed when these pairings were formed and broken as cows entered and left the social group (pen). The trend in all four pens was toward higher-than-expected milk production during periods of affinity. Moreover, we found that when affinities were broken (separation of cow pairs) the day-to-day variability in milk production was three times higher than for cows in an affinity pair. The results of this exploratory study suggest that SNA could be potentially used as a tool to reduce milk yield variation and better understand the social dynamics of dairy cows supporting management and welfare decisions.
我们将社交网络分析（SNA）应用于自动挤奶系统中奶牛通过分选门的自愿移动数据，以识别连续多次紧密通过分选门的奶牛对（亲和对）。SNA应用于一个奶牛场中由四个牛舍定义的社会群体，每个牛舍都配备有自动挤奶系统（AMS）。每个牛舍都设有一个自动分选门，用于识别奶牛何时自愿从休息区移动到挤奶区或喂食区。本研究的目的有两个：确定SNA是否能够识别亲和对，以及确定当亲和对被打破时产奶量是否会受到影响。我们使用了一个商业化引导式AMS奶牛场的奶牛流动和挤奶性能数据。挤奶牛的平均数量为214±34头，在1年的时间里分布在四个AMS中。SNA能够识别出明确的亲和对，并显示出随着奶牛进入和离开社会群体（牛舍），这些配对何时形成和破裂。在所有四个牛舍中，亲和期的产奶量趋势都高于预期。此外，我们发现，当亲和关系被打破（奶牛对分离）时，产奶量的每日变异性比亲和对中的奶牛高出三倍。这项探索性研究的结果表明，SNA可能潜在地用作一种工具，以减少产奶量变化，并更好地理解奶牛的社会动态，从而支持管理和福利决策。
