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 : Utilizing art to enhance learning STEM subjects required for aquaculture
Joni Lee Giovanna Hesley, Emerita CropKing, United States
Title : Advancing disease resistance in largemouth bass: Effects of ß glucan on immunity and survival rates
Liang Liu, KEMIN, Belgium
Title : Antimicrobial resistance and biosecurity in aquaculture
Pani Prasad Kurcheti, Fisheries University, India
Title : Haringhata fish: A concept of responsible farming with sensible marketing for better livelihood and sustainable development
Subhas Das, The University of Burdwan, India
Title : Effect of acute toxicity of formalin on orechromis niloticus
Azuibuke Adams Chris , Nigeria police academy wudil Kano University, Nigeria
Title : Foresight, market and financial analysis of microalgae for aquaculture feed: use of Chlorella sorokiniana biomass in a hypothetical diet formulation for Pacific white shrimp (Penaeus vannamei)
Sergio Saraiva Nazareno dos Anjos, Brazilian Agricultural Research Corporation (Embrapa), Brazil