Analytical techniques are crucial in aquaculture for assessing water quality, fish health, and feed efficiency. Data analysis helps identify trends, forecast production rates, and assess environmental impact. Techniques such as spectrometry, chromatography, and PCR testing are used to detect pathogens and contaminants in water. Additionally, sensors provide real-time data on temperature, pH, and oxygen levels, which are essential for maintaining optimal growing conditions. Advanced data analysis tools, including machine learning, analyze large datasets to identify patterns that improve efficiency and predict disease outbreaks. Data-driven insights aid farmers in making informed decisions, optimizing resources, and maintaining sustainable aquaculture systems that benefit both producers and the environment.
Title : Application of artificial intelligence and NISAR satellite to study the air sea CO2 exchange and aquatic toxicology to develop ‘Aquatic Pollution Remediation Technologies’(PART)
Virendra Goswami, Indian Institute of Technology, India
Title : DNA barcoding as a tool for biodiversity and ecological assessment in african freshwater systems: A case study of upper section of River Mpanga, Uganda
Basooma Rose, BOKU University, Austria
Title : Spatial refuge and reproductive potential of the vulnerable the picked dogfish (Squalus acanthias) in the Georgian black sea: Evidence from experimental trawl survey
Guranda, National Environmental Agency, Georgia
Title : Seasonal habitat shifts and purse seine dependence of mene maculata in the Taiwan strait: Early indicators of climate driven ecosystem change
Ipsita Biswas, National Taiwan Ocean University, Taiwan
Title :
Kidanie Misganaw Bezabih, University of Gondar, Ethiopia
Title : Eco friendly bioremediation: Azolla pinnata as a natural shield against hexaconazole toxicity in cyprinus carpio (LINNAEUS, 1758)
Mandeep Kaur, Panjab University, India