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.