Evidence map›Paper›PMID 37627433›Full record

ArticleAnimals : an open access journal from MDPI2023

Real-Time Monitoring of Grazing Cattle Using LORA-WAN Sensors to Improve Precision in Detecting Animal Welfare Implications via Daily Distance Walked Metrics.

Shelemia Nyamuryekung'e, Glenn Duff, Santiago Utsumi, Richard Estell, Matthew M McIntosh, Micah Funk, Andrew Cox, Huiping Cao, Sheri Spiegal, Andres Perea and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Animals : an open access journal from MDPI, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
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

11 authors.

Shelemia Nyamuryekung'eDivision of Food Production and Society, Norwegian Institute of Bioeconomy Research (NIBIO), PB 115, N-1431 Ås, Norway.ORCID 0000-0001-9323-0208
Glenn DuffDepartment of Animal and Range Sciences, New Mexico State University, Las Cruces, NM 88003, USA.
Santiago UtsumiDepartment of Animal and Range Sciences, New Mexico State University, Las Cruces, NM 88003, USA.
Richard EstellUnited States Department of Agriculture-Agriculture Research Service, Jornada Experimental Range, Las Cruces, NM 88003, USA.
Matthew M McIntoshUnited States Department of Agriculture-Agriculture Research Service, Jornada Experimental Range, Las Cruces, NM 88003, USA.ORCID 0000-0002-8957-8735
Micah FunkDepartment of Animal and Range Sciences, New Mexico State University, Las Cruces, NM 88003, USA.
Andrew CoxDepartment of Animal and Range Sciences, New Mexico State University, Las Cruces, NM 88003, USA.
Huiping CaoDepartment of Computer Science, New Mexico State University, Las Cruces, NM 88003, USA.ORCID 0000-0002-1350-1846
Sheri SpiegalUnited States Department of Agriculture-Agriculture Research Service, Jornada Experimental Range, Las Cruces, NM 88003, USA.ORCID 0000-0002-5489-9512
Andres PereaDepartment of Animal and Range Sciences, New Mexico State University, Las Cruces, NM 88003, USA.
Andres F CibilsUnited States Department of Agriculture Southern Plains Climate Hub, United States Department of Aagricultulre-Agriculture Rearch Services, Oklahoma and Central Plains Agricultural Research Center, El Reno, OK 73036, USA.ORCID 0000-0002-4733-6463

Funding

United States Department of Agriculture 2019-69012-29853
6 · The paper itself

Abstract

Animal welfare monitoring relies on sensor accuracy for detecting changes in animal well-being. We compared the distance calculations based on global positioning system (GPS) data alone or combined with motion data from triaxial accelerometers. The assessment involved static trackers placed outdoors or indoors vs. trackers mounted on cows grazing on pasture. Trackers communicated motion data at 1 min intervals and GPS positions at 15 min intervals for seven days. Daily distance walked was determined using the following: (1) raw GPS data (RawDist), (2) data with erroneous GPS locations removed (CorrectedDist), or (3) data with erroneous GPS locations removed, combined with the exclusion of GPS data associated with no motion reading (CorrectedDist_Act). Distances were analyzed via one-way ANOVA to compare the effects of tracker placement (Indoor, Outdoor, or Animal). No difference was detected between the tracker placement for RawDist. The computation of CorrectedDist differed between the tracker placements. However, due to the random error of GPS measurements, CorrectedDist for Indoor static trackers differed from zero. The walking distance calculated by CorrectedDist_Act differed between the tracker placements, with distances for static trackers not differing from zero. The fusion of GPS and accelerometer data better detected animal welfare implications related to immobility in grazing cattle.

Indexed as

internet of thingslong range wide area networkprecision livestock farmingprecision livestock ranching

Identifiers

PMID37627433
PMCPMC10451644

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.