Evidence map›Paper›PMID 41019777›Full record

ArticleFrontiers in robotics and AI2025

Avoidance behaviours of farmed Atlantic salmon (

Qin Zhang, Nina Bloecher, Linn Danielsen Evjemo, Martin Føre, Eleni Kelasidi

Abstract read
In one paragraph

Article in Frontiers in robotics and AI, 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

5 authors.

Qin ZhangDepartment of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway.
Nina BloecherDepartment of Aquaculture, SINTEF Ocean AS, Trondheim, Norway.
Linn Danielsen EvjemoDepartment of Aquaculture, SINTEF Ocean AS, Trondheim, Norway.
Martin FøreDepartment of Engineering Cybernetics, Norwegian University of Science and Technology, Trondheim, Norway.
Eleni KelasidiDepartment of Aquaculture, SINTEF Ocean AS, Trondheim, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Intensive finfish aquaculture is increasingly relying on enabling technologies and solutions such as sensor systems, robotics, and other machinery. Together with conventional farming equipment, these systems may emanate acoustic noise and artificial light, impacting the pen environment. Farmed fish have been observed to respond behaviourally and/or physiologically to anthropogenic sounds and lights, indicating a stress reaction that could impair welfare and health. This study aimed to investigate how farmed Atlantic salmon respond to such stimuli, with direct implications for the design and operation of robotic and mechanised systems in sea pens. We conducted experiments where we systematically exposed adult farmed Atlantic salmon in commercial net pens to sounds of frequencies within the range common to farm equipment (100-1,000 Hz), and submerged lights at 8 and 12 m with four different intensities (600 lx-14,500 lx). Data was analysed using sonar data and a deep learning (DL) based method for processing that automatically identified fish distribution patterns and estimated the average avoidance distance to the sound/light source. The fish fled from the sound source while playing sounds of 400 Hz, while sounds at other frequencies did not elicit a response. The response to light intensity depended on deployment depth, with the fish moving closer to the source when intensity was increased at 8 m depth, but conversely moving further away with increasing density when it was placed at 12 m. These outcomes are important inputs for the design of equipment, autonomous vehicles, robotic interventions and operations at commercial farms to ensure that their sound and light emissions have minimal impact on the fish, thereby reducing the potential of induced stress.

Indexed as

aquaculturebehaviourdeep learningfish farm design inputsrobotics and automationSalmo salar

Identifiers

PMID41019777
PMCPMC12460098

What OpenQuestion holds

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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.