Evidence map›Paper›PMID 40745358›Full record

ArticleScientific reports2025

Insights into thermal stress effects on performance and behavior of grazing cattle via multimodal sensor monitoring.

Regina Eckhardt, Reza Arablouei, Kieren McCosker, Greg Bishop-Hurley, Neil Bagnall, Ben Hayes, Antonio Reverter, Aaron Ingham, Heinz Bernhardt

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
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

9 authors.

Regina EckhardtChair of Agricultural Systems Engineering, TUM School of Life Sciences, Technical University of Munich, 85354, Freising, Germany. regina.eckhardt@tum.de.
Reza ArabloueiData61, CSIRO, Pullenvale, QLD, 4069, Australia.
Kieren McCoskerCentre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, 4067, Australia.
Greg Bishop-HurleyAgriculture and Food, CSIRO, St Lucia, QLD, 4067, Australia.
Neil BagnallAgriculture and Food, CSIRO, St Lucia, QLD, 4067, Australia.
Ben HayesCentre for Animal Science, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, St Lucia, QLD, 4067, Australia.
Antonio ReverterAgriculture and Food, CSIRO, St Lucia, QLD, 4067, Australia.
Aaron Ingham *Agriculture and Food, CSIRO, St Lucia, QLD, 4067, Australia.
Heinz Bernhardt *Chair of Agricultural Systems Engineering, TUM School of Life Sciences, Technical University of Munich, 85354, Freising, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cattle have been observed to change their behavior and location in response to thermal stress. This study employs a multimodal sensor-based approach to assess if the behavior of grazing cattle changed in response to thermal conditions that occurred during two trials conducted in Queensland, Australia, over late spring and early summer. Each trial involved sixty cattle (Brahman and Droughtmaster) fitted with eGrazor collars containing triaxial accelerometer and GNSS sensors. Cattle were genotyped and weighed weekly, and relevant meteorological data was collected. Accelerometer data was used to classify cattle behavior at five-second intervals into six distinct categories: grazing, walking, ruminating, resting, drinking, and other. GNSS data and satellite imagery were utilized to estimate time spent in open areas, while the Comprehensive Climate Index (CCI) was calculated from meteorological data and used to identify the two warmest and coolest weeks of both trials. Correlation analysis revealed that, during days of higher CCI, cattle increased time in the shade (correlation coefficient [Formula: see text]), reduced daytime grazing ([Formula: see text]), shifted grazing to nighttime ([Formula: see text]), and prolonged daytime resting ([Formula: see text]). Weather variations had a subtle influence on weight gain, while cattle with increased Bos indicus genetic proportion were more active during periods of higher CCI. These findings emphasize the potential of sensor-based monitoring to quantify cattle behavioral responses to variable weather conditions in relevant production environments.

Indexed as

Behavior, AnimalHeat-Shock ResponseAccelerometryAnimalsCattleQueenslandSeasons

Identifiers

PMID40745358
PMCPMC12314005

What OpenQuestion holds

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LicenceCC BY
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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.