Behavioral Responses in Zebrafish (Danio rerio) Exposed to Heavy Metal and Insecticide Induced Stress

Background: Changes in fish behavior can help identify accidental chemical pollution. Heavy metals and pesticides are two of the most found pollutants to investigate the different behavioral responses of fish to these two types of pollutants exposure. Methods: Real-time computer imaging was utilized to record parameters of fish behaviors, including swimming speed, turning frequency, depth and distance between fish. Deltamethrin and cadmium were 0.015 ppm and 3.5 ppm, respectively. It was conducted for a total period of 180 min. Fish behaviors were recorded with dechlorinated water during the first 60 mins, then deltamethrin and cadmium was introduced to observe behavioral responses of zebrafish during the next 120 mins. Result: As a result of increased swimming activity, the first response of zebrafish is avoidance followed by a changed distribution in the test chamber. The duration of hyperactivity during deltamethrin exposure was lasted 35 minutes larger than Cd exposure and the average swimming depth showed totally different trends with increased from 140 mm to 226 mm during deltamethrin exposure but decreased from 161 to 84 mm during cadmium exposure. It is proved that these different responses do exist under in the two chemicals studied and this may contribute to the development of biological early warning system to separate accidental chemical pollution types.

Aquatic Toxic Analysis by Monitoring Fish Behavior Using Computer Vision: A Recent Progress

Video tracking based biological early warning system achieved a great progress with advanced computer vision and machine learning methods. Ability of video tracking of multiple biological organisms has been largely improved in recent years. Video based behavioral monitoring has become a common tool for acquiring quantified behavioral data for aquatic risk assessment. Investigation of behavioral responses under chemical and environmental stress has been boosted by rapidly developed machine learning and artificial intelligence. In this paper, we introduce the fundamental of video tracking and present the pioneer works in precise tracking of a group of individuals in 2D and 3D space. Technical and practical issues suffered in video tracking are explained. Subsequently, the toxic analysis based on fish behavioral data is summarized. Frequently used computational methods and machine learning are explained with their applications in aquatic toxicity detection and abnormal pattern analysis. Finally, advantages of recent developed deep learning approach in toxic prediction are presented.

Biomonitoring of coastal marine waters subject to anthropogenic use: development and application of the biosensor Mosselmonitor®

The overall objective of this study was to develop a biological early warning system (Mosselmonitor®) on offshore platform to detect critical environmental situations. The experiment was conducted on oil off-shore platform called Rospo Mare B. This structure is located in the area in front of Molise coast line (Italy, Adriatic Sea), characterized by a depth of about 77 m and a bathymetry between 65 and 80 m. The Mosselmonitor® works with eight mussels connected via specific sensors to PC for recording opening values of valves. A probe was installed inside the instrument to daily control of water pH, dissolved oxygen, salinity and temperature. Water samples are weekly analyzed for heavy metals, organochlorine pesticide and suspended matter. During the entire observation period, closure alarms were predominantly detected (99.9%) and a decrease of 65% in alarms maximum duration was recorded from the fifth week. During the first month, none changes in water physico-chemical parameters were observed so that affect the bivalves behavior. The only chemical parameter steadily detected in water was copper; its average concentrations were of 10 ppb. Detected alarms were not comparable to those recorded in the first month: this observation could be explained considering that mussels will be adapted to copper constant presence.