Lakshmi Shankar
Analysis of salmon behaviour is a successful method for detecting environmental toxins that have a negative impact on salmon survival, production, and quality. Large volumes of non-linear data are produced when tracking individual and group behaviour, necessitating the use of specialised computing techniques to interpret and manage the data. Measures of operational complexity (FD) and predictability (entropy) are provided by two categories of nonlinear analysis approaches called fractal dimension (FD) and entropy. Changes in FD and entropy values can obviously be incorporated into biological early warning systems (BEWS), which are particularly accurate, because behavioural complexity and predictability can be modified by pollutants. There are various salmon farming environments and situations where it can be useful. for keeping an eye on wild populations. The study looked into a wide range of environmental pollutants, including pesticides, persistent pollutants, heavy metals (lead, copper, and mercury), heavy metals (lead, copper, and mercury), stimulants (caffeine), anaesthetics, and antibiotics. gives a summary of the effects of drugs. Studies on the population and individual behavioural reactions of different salmon species' HFD and entropy levels. With early changes in the tendency to develop their values before they significantly diverge from control values, all revised investigations show the value of both FD and entropy to identify the presence of pollutants. the importance of taking H into account. While pollutants are prevalent, it is still possible to spot them and keep salmon healthy and intact.
KeywordsAquaculture; Aquatic pollutants; Entropy; Salmon behaviour
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