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Robotic Raman Spectroscopy for Rapid Fatty Acid Measurement in Salmon Fillets

Michael Angelo Amith Fenelon, Tiril Aurora Lintvedt, Antonio C. Leite, Jens Petter Wold

Year
2023
Citations
5

Abstract

In this work, we present a robotic solution to measure the content of omega-3 fatty acids in salmon fillets using Raman spectroscopy. Fatty acid composition is a significant quality parameter for the salmon farming industry as a high content contributes to consumer health, a redder fillet, and fewer unwanted dark spots, leading to a higher fillet price. The current methodology for evaluating omega-3 fatty acids in salmon fillets is conducted manually using a Raman probe, which is tiresome, error-prone, time-consuming, and demands labor. To overcome these drawbacks, we propose a semi-autonomous robotic scanning platform composed of a visual servoing system and a motion planning algorithm. We then develop a proof-of-concept demonstration using commercial Raman technology, a 6-DoF robot arm, an RGB camera, and a linear conveyor module, emulating an industrial environment on a laboratory scale. The proposed robot and sensor integration methodology effectively performs real-time measurement of fatty acid content in salmon fillets moving on a conveyor belt at low and high speeds, preventing human-prone errors and increasing operating efficiency.

Keywords

Fillet (mechanics)Fatty acidArtificial intelligenceConveyor beltRobotRaman spectroscopyComputer scienceComputer visionEnvironmental scienceBiological system

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