Data for characterization of the optical properties of Atlantic salmon (Salmo salar) blood.

Photoplethysmography is a recent addition to physio-logging in Atlantic salmon which can be used for pulse oximetry provided that the properties for light propagation in salmon tissues are known. In this work, optical properties of three constituents of Atlantic salmon blood have been characterized using a photo spectrometer in the VIS-NIR range (450-920 nm). Furthermore, Atlantic salmon blood cell size has been measured using a Coulter counter as part of light scattering property evaluations. Results indicate that plasma contributes little to scattering and absorption for wavelengths typically used in pulse oximetry as opposed to blood cells which are highly scattering. Extinction spectra for oxygenated and deoxygenated hemoglobin indicate that Atlantic salmon hemoglobin is similar to that in humans. Pulse oximetry sensors originally intended for human applications may thus be used to estimate blood oxygenation levels for this species.

Identification of spectral signature for in situ real-time monitoring of smoltification.

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.

Modelling growth performance and feeding behaviour of Atlantic salmon (Salmo salar L.) in commercial-size aquaculture net pens: Model details and validation through full-scale experiments.

We have developed a mathematical model which estimates the growth performance of Atlantic salmon in aquaculture production units. The model consists of sub-models estimating the behaviour and energetics of the fish, the distribution of feed pellets, and the abiotic conditions in the water column. A field experiment where three full-scale cages stocked with 120,000 salmon each (initial mean weight 72.1  ± SD 2.8 g) were monitored over six months was used to validate the model. The model was set up to simulate fish growth for all the three cages using the feeding regimes and observed environmental data as input, and simulation results were compared with the experimental data. Experimental fish achieved end weights of 878, 849 and 739 g in the three cages respectively. However, the fish contracted Pancreas Disease (PD) midway through the experiment, a factor which is expected to impair growth and increase mortality rate. The model was found able to predict growth rates for the initial period when the fish appeared to be healthy. Since the effects of PD on fish performance are not modelled, growth rates were overestimated during the most severe disease period. This work illustrates how models can be powerful tools for predicting the performance of salmon in commercial production, and also imply their potential for predicting differences between commercial scale and smaller experimental scales. Furthermore, such models could be tools for early detection of disease outbreaks, as seen in the deviations between model and observations caused by the PD outbreak. A model could potentially also give indications on how the growth performance of the fish will suffer during such outbreaks. STATEMENT OF RELEVANCE: We believe that our manuscript is relevant for the aquaculture industry as it examines the growth performance of salmon in a fish farm in detail at a scale, both in terms of number of fish and in terms of duration, that is higher than usual for such studies. In addition, the fish contracted a disease (PD) midway through the experiment, thus resulting in a detailed dataset containing information on how PD affects salmon growth, which can serve as a foundation to understanding disease effects better. Furthermore, the manuscript describes an integrated mathematical model that is able to predict fish behaviour, growth and energetics of salmon in response to commercial production conditions, including a dynamic model of the distribution of feed pellets in the production volume. To our knowledge, there exist no models aspiring to estimate such a broad spectre of the dynamics in commercial aquaculture production cages. We believe this model could serve as a future tool to predict the dynamics in commercial aquaculture net pens, and that it could represent a building block that can be utilised in a future development of knowledge-driven decision-support tools for the salmon industry.