Evidence map›Paper›PMID 41157455›Full record

ArticleSensors (Basel, Switzerland)2025

Evaluating Reticulorumen Temperature, Rumination, Activity and pH Measured by Rumen Sensors as Indicators of Heat Load in Fattening Bulls.

Kay Fromm, Christian Ammon, Thomas Amon, Gundula Hoffmann

Abstract readEvaluation Study
In one paragraph

Article in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Kay FrommDepartment of Sensors and Modelling, Leibniz Institute for Agricultural Engineering and Bioeconomy e.V., Max-Eyth-Allee 100, 14469 Potsdam, Germany.ORCID 0009-0007-8888-235X
Christian AmmonDepartment of Sensors and Modelling, Leibniz Institute for Agricultural Engineering and Bioeconomy e.V., Max-Eyth-Allee 100, 14469 Potsdam, Germany.ORCID 0000-0001-6852-4992
Thomas AmonDepartment of Sensors and Modelling, Leibniz Institute for Agricultural Engineering and Bioeconomy e.V., Max-Eyth-Allee 100, 14469 Potsdam, Germany.ORCID 0000-0003-2468-3160
Gundula HoffmannDepartment of Sensors and Modelling, Leibniz Institute for Agricultural Engineering and Bioeconomy e.V., Max-Eyth-Allee 100, 14469 Potsdam, Germany.ORCID 0000-0002-0421-6250

Funding

Federal Ministry of Agriculture, Food and Regional Identity (BMLEH) 28N304208
6 · The paper itself

Abstract

The aim of this experiment was to determine whether reticulorumen temperature (ReT), rumination, activity or pH captured by a rumen sensor bolus system (smaXtec animal care GmbH, Graz, Austria) can be used as an early indicator of heat load (HL) and to assess how its daily patterns are influenced by diurnal effects. Physiological and behavioral data from 70 male feedlot cattle (Uckermärker, Hereford, Simmentaler) housed in a closed barn were investigated using the calculated temperature-humidity index (THI) from remote HOBO Onset climate sensors over a period of 210 days. Using time series analysis and seasonal ARIMA modeling, it was found that ReT followed the same patterns throughout days with a THI < 74 as well as days under heat load conditions. Time series and correlation analyses were also performed for the rumen pH, rumination index and activity index. The collective mean ReT over the winter days assessed (

Indexed as

CattleRumenRumination, DigestiveAnimalsBody TemperatureHot TemperatureHydrogen-Ion ConcentrationMaleMotionSeasonsbull husbandryheat load detectionprecision livestock farmingreticulorumen temperaturerumen pHrumen sensor-based monitoring

Identifiers

PMID41157455
PMCPMC12567746

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.