Study of fish swimming activity using acoustical Doppler velocimetry (ADV) techniques

Abstract

The suitability of using acoustic Doppler velocimetry (ADV) to study fish swimming activity is evaluated in this study. ADV makes it possible to detect and quantify the relationship between fish density and the turbulence generated by fish swimming activity and to show differences in fish swimming patterns during the scotophase (dark period) and photophase (light period), which has been previously described by other authors. Turbulence was evaluated using the root mean square of velocity (RMS) as an indicator of fish swimming activity, and an ADV probe with an internal sampling rate of 100 Hz, which took 25 velocity data per second.Experiments at the laboratory scale using zebra fish showed a positive correlation between turbulence (RMS), caused by fish swimming activity, and density. The relationship between density and RMS was strongly linear (r 2 = 0.964). In an ongrowing farm, daily turbulence patterns caused by fish swimming activity were evaluated with sea bass at two densities: 35.5 kg m À3 (average weight of 48 g), and 11.8 kg m À3 (average weight of 11.7 g). Greater activity was detected during the photophase, indicating that light has a substantial affects sea bass swimming activity. Average RMS at a density of 35.5 kg m À3 was 3.632 and 2.428 cm s À1during photophase and scotophase, respectively, while working at a density of 11.8 kg m À3, average RMS was 1.728 and 1.419 cm s À1 during the photophase and scotophase, respectively. ADV is a rapid and reliable method to evaluate fish swimming activity at laboratory scales as well as at commercial facilities. However, ADV configuration parameters must be properly chosen in order to obtain the highest possible number of good velocity data. Data post-processing was done by filtering velocity data using correlation (COR > 70), signal-to-noise ratio (SNR > 5) and despiking filters. COR provides a measure of quality of each velocity data, ranging from 0 to 100, and SNR indicates the intensity of the reflected acoustic signal expressed in dB. Finally, despiking filter eliminates spikes generated by fish located near the probe or between the probe and point of measurement. Post-processing showed that COR filter eliminated the higher number of velocity data. #

Influence of fish swimming on the flow pattern of circular tanks

“…All the measurements were made when the steady-state was reached. A detailed description of the post-processing data can be found in Masaló et al (2008).…”

“…In a tank with fish, where turbulence due to fish movement is introduced (Masaló et al, 2008;Plew et al, 2015) and mixing is enhanced (Rasmussen et al, 2005;Lunger et al, 2006) velocity profile is changed, and also resistance to water circulation. Recent studies pointed out that average velocity is reduced and turbulence is increased in circular tanks with fish (Plew et al, 2015), and as a consequence high resistance to water circulation and changes in velocity distributions were observed.…”

Flow pattern in aquaculture circular tanks: Influence of flow rate, water depth, and water inlet & outlet features

“…Correlation coefficient (COR) above 70, and signal-tonoise ratio (SNR) above 5 were used. A more detailed description about post-processing can be found in Masaló et al (2008). Each measurement lasted 2 min, with readings taken every 0.04 s. The average of the 3000 values obtained provided the time-averaged velocity for each point.…”

Information fusion in aquaculture: a state-of the art review

“…The results showed the quantifiable effect of stocking density on these three variables, but in true aquaculture conditions it is difficult to measure these alterations. Masaló et al [76] measured the turbulence at different densities and quantified the swimming behavior. Although ADV is reliable for measuring the quantitative results of turbulence, it eliminates some measurements because fish larger than 48 g are of a higher density.…”