Ultra-Low Power Sensor Devices for Monitoring Physical Activity and Respiratory Frequency in Farmed Fish

Abstract

Integration of technological solutions aims to improve accuracy, precision and repeatability in farming operations, and biosensor devices are increasingly used for understanding basic biology during livestock production. The aim of this study was to design and validate a miniaturized tri-axial accelerometer for non-invasive monitoring of farmed fish with re-programmable schedule protocols. The current device (AE-FishBIT v.1s) is a small (14 mm × 7 mm × 7 mm), stand-alone system with a total mass of 600 mg, which allows monitoring animals from 30 to 35 g onwards. The device was attached to the operculum of gilthead sea bream ( Sparus aurata ) and European sea bass ( Dicentrarchus labrax ) juveniles for monitoring their physical activity by measurements of movement accelerations in x - and y -axes, while records of operculum beats ( z -axis) served as a measurement of respiratory frequency. Data post-processing of exercised fish in swimming test chambers revealed an exponential increase of fish accelerations with the increase of fish speed from 1 body-length to 4 body-lengths per second, while a close relationship between oxygen consumption (MO 2 ) and opercular frequency was consistently found. Preliminary tests in free-swimming fish kept in rearing tanks also showed that device data recording was able to detect changes in daily fish activity. The usefulness of low computational load for data pre-processing with on-board algorithms was verified from low to submaximal exercise, increasing this procedure the autonomy of the system up to 6 h of data recording with different programmable schedules. Visual observations regarding tissue damage, feeding behavior and circulating levels of stress markers (cortisol, glucose, and lactate) did not reveal at short term a negative impact of device tagging. Reduced plasma levels of triglycerides revealed a transient inhibition of feed intake in small fish (sea bream 50–90 g, sea bass 100–200 g), but this disturbance was not detected in larger fish. All this considered together is the proof of concept that miniaturized devices are suitable for non-invasive and reliable metabolic phenotyping of farmed fish to improve their overall performance and welfare. Further work is underway for improving the attachment procedure and the full device packaging.

Tissue-Specific Orchestration of Gilthead Sea Bream Resilience to Hypoxia and High Stocking Density

“…Progress toward a more sustainable and environmentally friendly aquaculture requires important investments in both conventional and new methodologies for a less invasive and more refined phenotyping of individual farmed fish. Main achievements so far include the use of acoustic telemetry or stand-alone biosensors for the non-disturbing monitoring of feeding behavior or metabolic capabilities (Føre et al, 2017; Martos-Sitcha et al, 2019). In addition to that, major progress has been done with the advent of wide-holistic omics based on functional genomics, proteomics, metabolomics and metagenomics as powerful toolsets for the development of a highly technified aquaculture in different fish species (Yáñez et al, 2015; Martin and Król, 2017; Martínez-Porchas and Vargas-Albores, 2017; Alfaro and Young, 2018; Rodrigues et al, 2018).…”

Early prediction of declining health in small ruminants with accelerometers and machine learning

“…A promising alternative could be to use biologgers to remotely monitor behaviour linked to poor health (19)(20)(21)(22). Thanks to advancements in on-animal sensor technology, effective tracking and monitoring of terrestrial animals can now give access to large quantities of data on their behaviour and their interactions between each other and with their environment (23).…”

Use of accelerometer technology for individual tracking of activity patterns, metabolic rates and welfare in farmed gilthead sea bream (Sparus aurata) facing a wide range of stressors

“…However, it is important to ensure that these devices do not negatively impact the animals and, hence, skew the data. The proposed solution for farmed fish within the AQUAEXCEL 2020 EU project is a small and smart device (AEFishBIT), working in stand-alone with an autonomy of 6 hours of continuous recording and re-programmable schedule protocols (Martos-Sitcha et al, 2019).…”