Avoidance behaviours of farmed Atlantic salmon (Salmo salar L.) to artificial sound and light: a case study of net-pen mariculture in Norway.

IF 3 Q2 ROBOTICS
Frontiers in Robotics and AI Pub Date : 2025-09-11 eCollection Date: 2025-01-01 DOI:10.3389/frobt.2025.1657567
Qin Zhang, Nina Bloecher, Linn Danielsen Evjemo, Martin Føre, Eleni Kelasidi
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引用次数: 0

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.

养殖大西洋鲑鱼(Salmo salar L.)对人工声光的回避行为:挪威网笼海水养殖的案例研究。
集约化鳍鱼养殖越来越依赖于传感器系统、机器人和其他机械等技术和解决方案。与传统的养殖设备一起,这些系统可能会发出噪音和人造光,影响猪圈环境。观察到养殖鱼类在行为和/或生理上对人为声音和光线作出反应,表明可能损害福利和健康的应激反应。这项研究旨在调查养殖的大西洋鲑鱼是如何对这种刺激做出反应的,这对海洋围栏中机器人和机械化系统的设计和操作有直接的影响。我们进行了实验,我们系统地将商业网栏中养殖的成年大西洋鲑鱼暴露在农场设备常见频率范围内的声音(100-1,000 Hz),以及8米和12米的四种不同强度(600 lx-14,500 lx)的水下灯光下。数据分析使用声纳数据和基于深度学习(DL)的处理方法,自动识别鱼类分布模式,并估计到声光源的平均躲避距离。当播放400赫兹的声音时,鱼会逃离声源,而其他频率的声音则不会引起反应。对光强的响应取决于部署深度,当光强在8 m深度增加时,鱼会向光源靠近,而当光强在12 m深度增加时,鱼会向远离光强的方向移动。这些结果对于设备设计、自动驾驶车辆、机器人干预和商业养殖场的操作都是重要的输入,以确保它们的声音和光发射对鱼的影响最小,从而减少诱发压力的可能性。
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来源期刊
CiteScore
6.50
自引率
5.90%
发文量
355
审稿时长
14 weeks
期刊介绍: Frontiers in Robotics and AI publishes rigorously peer-reviewed research covering all theory and applications of robotics, technology, and artificial intelligence, from biomedical to space robotics.
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