During three cruises in the Mid Atlantic Ridge area in 2016 and 2017, we studied the biomass of mesopelagic fish and its potential as a source of protein and oil for animal feed and human consumption. We collected samples of mesopelagic species down to a depth of 600 m, studied fish behaviour, identified and quantified the species composition of the catches, analysed the chemical composition of the catch samples, and evaluated the presence of unwanted substances. Results showed that Maurolicus muelleri (Mueller’s pearlside) and Benthosema glaciale (Glacier lantern fish) were the most abundant fish species in our samples and catches containing 80% fish can be a good source of protein and marine lipids including eicosapentaenoic acid (C20:5n3) and docosahexaenoic acid (C22:6n3). Unwanted substances, except for Cd and As, were present at levels far lower than the limits set by European Union regulations. However, our experiments identified challenges that may limit the efficiency of commercial operations in the Northeast Atlantic. Combined real-time optical and/or multifrequency acoustic systems will be needed to improve species identification and ensure cost-effective fishing operations. Also, selective trawls that target only fish and release unwanted species are needed to secure high-quality oils and proteins.

The 3D machine vision system presented in this article enables high-speed and accurate weight estimation of whole herring, thus enabling an increase in profitability for the pelagic primary processors through a more accurate weight grading.

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ABSTRACT:19 Among the rest raw material in herring (Clupea harengus) fractions, produced during the 20 filleting process of herring, there are high value products such as roe and milt. As of today there 21 has been little or no major effort to process these by-products in an acceptable state, except 22 for by manual separation and mostly mixed into low-value products. Even though pure roe and 23 milt fractions can be sold for as much as ten times the value of the mixed fractions, the 24 separation costs using manual techniques render this economically unsustainable. Automating 25 this separation process could potentially give the pelagic fish industry better raw material 26 utilization and a substantial additional income. In this paper, a robust classification approach is 27 described which enables separation of these by-products based on their distinct reflectance

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