The integration of data science and bioinformatics into aquaculture is transforming the industry by enhancing productivity, sustainability, and species management. Data Science and Bioinformatics in Aquaculture focuses on leveraging big data, machine learning, and genomic tools to optimize breeding programs, monitor fish health, and predict environmental conditions. With the help of genomic sequencing, aquaculture producers can select desirable traits, such as disease resistance and faster growth, improving the overall efficiency of farming systems. Real-time data collection, combined with advanced analytics, allows for better decision-making in feeding schedules, water quality management, and disease prevention. Additionally, bioinformatics helps track microbial communities and their role in maintaining aquatic health. By integrating these cutting-edge technologies, aquaculture can become more precise, efficient, and resilient, ensuring a sustainable future for the industry.
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 : 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
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Kidanie Misganaw Bezabih, University of Gondar, Ethiopia
Title : National action plan for sustainable and resilient fisheries aquaculture system in Pakistan
Nazia Sher, National Institute of Maritime Affairs, Pakistan
Title : Conditionally pathogenic microparasites (Microsporidia and Myxosporea) of mullet fish potential objects of mariculture in the black and azov seas
Violetta M Yurakhno, A. O. Kovalevsky Institute of Biology of the Southern Seas of Russian Academy of Sciences, Russian Federation
Title : Variations in nutritional and bioactive properties of North Atlantic sea cucumber (Cucumaria frondosa): Role of seasonality, location, and processing
Amit Das, Memorial University of Newfoundland, Canada