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Keywords:

  • salmon;
  • rigor mortis;
  • handling stress;
  • low-frequency vibrations;
  • neural network

ABSTRACT

The rigor mortis development of large Atlantic salmon was evaluated at a commercial plant using a sensory method, a mechanical rigorometer and low-frequency vibrations. The fish were classified according to rigor state using a neural network. Assessments were done with fish subjected to two different levels of handling stress prior to slaughter. White muscle high-energy phosphates and inosine monophosphate were used as indices of stress showing that handling stress may be considerable during commercial slaughter. Results indicate rigor assessment should be nondestructive and classificaton of rigor state was possible using a lowfrequency vibration method combined with a neural network.