Evidence map›Paper›PMID 33923167›Full record

ArticleAnimals : an open access journal from MDPI2021

A Preliminary Investigation of Social Network Analysis Applied to Dairy Cow Behavior in Automatic Milking System Environments.

Liliana Fadul-Pacheco, Michael Liou, Douglas J Reinemann, Victor E Cabrera

Abstract read
In one paragraph

Article in Animals : an open access journal from MDPI, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Liliana Fadul-PachecoDepartment of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA.ORCID 0000-0003-2101-7154
Michael LiouDepartment of Statistical Science, University of Wisconsin-Madison, Madison, WI 53706, USA.
Douglas J ReinemannBiological and Systems Engineering Department, University of Wisconsin-Madison, Madison, WI 53706, USA.ORCID 0000-0002-1319-0718
Victor E CabreraDepartment of Animal and Dairy Sciences, University of Wisconsin-Madison, Madison, WI 53706, USA.ORCID 0000-0003-1739-7457

Funding

Food and Agriculture Cyberinformatics and Tools from the USDA National Institute of Food and Agriculture. 2019-68017-29935/project accession no. 1019780
6 · The paper itself

Abstract

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.

Indexed as

affinitiescow behaviorcow management

Identifiers

PMID33923167
PMCPMC8146444

What OpenQuestion holds

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.