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The present study investigates the suitability of a machine vision-based method to detect deviations in the Shannon entropy (SE) of a European seabass ( Dicentrarchus labrax ) biological system fed with different selenium:mercury (Se:Hg) molar ratios. Four groups of fish were fed during 14 days with commercial feed (control) and with the same feed spiked with 0.5, 5 and 10 mg of MeHg per kg, giving Se:Hg molar ratios of 29.5 (control-C 1 ); 6.6, 0.8 and 0.4 (C 2 , C 3 and C 4 ). The basal SE of C 1 and C 2 (Se:Hg &gt; 1) tended to increase during the experimental period, while that of C 3 and C 4 (Se:Hg &lt; 1) tended to decrease. In addition, the differences in the SE of the four systems in response to a stochastic event minus that of the respective basal states were less pronounced in the systems fed with Se:Hg molar ratios lower than one (C 3 and C 4 ). These results indicate that the SE may be a suitable indicator for the prediction of seafood safety and fish health (i.e., the Se:Hg molar ratio and not the Hg concentration alone) prior to the displaying of pathological symptoms. We hope that this work can serve as a first step for further investigations to confirm and validate the present results prior to their potential implementation in practical settings.

The Shannon Entropy Trend of a Fish System Estimated by a Machine Vision Approach Seems to Reflect the Molar Se:Hg Ratio of Its Feed