LAUSR

Abstract Since the availability of petroleum and derivatives has great impact over the world economy, the oil industry lies in both the formation and the maintenance of modern industrial economy. Petroleum exploration, transport, distribution and storage activities can compromise water resources and provide serious consequences to exposed organisms due to the risk of accidental spillage of oil and refinery effluents. Perna perna mussels are acknowledged for their sentinel characteristics being affected by slight environmental changes and one of the promising species in the aquaculture world. Thus, this study aimed to demonstrate that the behavior of Perna perna mussels is a suitable biomarker of exposure to petroleum and derivatives. The present research proposes the construction of an online aquatic pollution biosensor based on the behavioral analysis of Perna perna mussels network. Thirty-nine mussels instrumented with Hall Effect sensors and magnets were exposed to 0 (control), 5%, and 20% of Water-Accommodated Fraction (WAF) of Diesel S-500 for up to 42 hours. The sensors network outputs were used to evaluate the behavioral parameters average amplitude, filtration activity, transition frequency, amount of motion reversals and weighted average of the ten largest Fourier magnitudes after the first 12 hours of experiment using 6-hours intervals. The employment of the behavioral parameters weighted average of the ten largest Fourier magnitudes and transition frequency provided greater efficacy in distinguishing groups of animals exposed to contaminants in relation to the control group with significant differences in at least 80% of the analyzed intervals.