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.

Microscopic hyperspectral imaging used as a bio-optical taxonomic tool for micro- and macroalgae.

In the presented study a hyperspectral imager (400-700 nm) mounted on a stereo-microscope was used to separate differences in in vivo optical signatures identifying different pigment groups of bloom-forming phytoplankton and macroalgae by comparing spectral absorption, transmittance, and reflectance from 400-700 nm. The results show that the hyperspectral imager could be used to detect spectral characteristics on the microm level to calibrate, validate, identify, and separate objects with differences in color (optical fingerprinting). This information can be used for pigment group specific taxonomy (bio-optical taxonomy), eco-physiological information (e.g., health status), monitoring, and mapping applications.