ABSTRACT
Knowledge of the vertical migration pattern of sea lice (Lepeophtheirus salmonis) copepodites is necessary for designing efficient measures to prevent lice infestations on farmed Atlantic salmon (Salmo Salar) in sea-cages. However, data can be challenging to acquire at a large scale under realistic circumstances without interfering with the natural behavior of the specimen. A mesocosm platform was built to help acquire this data consisting of a sensor package in an underwater housing being pulled up and down along a 11-meter-long transparent tube containing planktonic organisms while collecting image-, temperature- and spectrometer data. The platform was placed at a salmon farm and the acrylic tube was filled with L. salmonis copepodites and was pre-programmed to run a profile scan twice per hour for four consecutive days. Using a fully convolutional neural network, the copepodites were automatically counted - creating a depth profile of detected lice and measured light specter. The final results showed a diurnal migration pattern throughout the test period.â¢Capable of acquiring vertical density profiles of any aquatic species between 0,5 - 10 mm down to 11 m below the surface.â¢Fully automated and can be left unintended for weeks while collecting data.
ABSTRACT
Thermal treatment is a controversial method to control sea lice in the Atlantic salmon farming industry. This study aimed to complement the growing evidence base to document the impact of thermal treatments on salmon welfare, behaviour, physiology and health. Here, fish were treated two times (four weeks apart) for 30 s in either 27, 30, or 33 °C warm water, and parameters were compared to a procedural control (exposed to their holding temperature of 14 °C) or a negative control (where no treatments were applied). The fish had a clear behavioural response to the warm water, despite low difference between treatment and holding temperature (Δt = 13, 16 or 19 °C). Eye damages were more prevalent in the warm water treated groups than in the controls. Little difference was recorded between treatment groups in their growth and condition factor, blood plasma values, organ health, and long-term coping ability. There was, however, a significant increase in mortality as a function of temperature after the first treatment (14 °C: 6.5%, 27 °C: 5.3%, 30 °C: 12.4% and 33 °C: 18.9% mortality). The first treatment was performed only two weeks after the fish had been tagged and moved into the experimental holding tanks, while the fish had been allowed to recover for four weeks without any handling before the second treatment. The group of fish that were not subjected to any treatments (the negative control) had no mortality throughout the entire experimental period.
ABSTRACT
We describe the use of an optical hyperspectral sensing technique to identify the smoltification status of Atlantic salmon (Salmo salar) based on spectral signatures, thus potentially providing smolt producers with an additional tool to verify the osmoregulatory state of salmon. By identifying whether a juvenile salmon is in the biological freshwater stage (parr) or has adapted to the seawater stage (smolt) before transfer to sea, negative welfare impacts and subsequent mortality associated with failed or incorrect identification may be reduced. A hyperspectral imager has been used to collect data in two water flow-through and one recirculating production site in parallel with the standard smoltification evaluations applied at these sites. The results from the latter have been used as baseline for a machine-learning algorithm trained to identify whether a fish was parr or smolt based on its spectral signature. The developed method correctly classified fish in 86% to 100% of the cases for individual sites, and had an overall average classification accuracy of 90%, thus indicating that analysis of spectral signatures may constitute a useful tool for smoltification monitoring.
