Science Wednesday: ML unpacks water quality for prawns
Commercial prawn farmers know that managing water quality well is vital to efficient production. Ponds that are side-by-side on the same farm can yield very differently depending on the salinity, temperature, turbidity and dissolved oxygen of the water.
A new paper in Biosystems Engineering by the Digiscape Future Science Platform’s Aquaculture project, and led by Mashud Rana, has used machine learning techniques to examine not just which water quality parameters are most important to the growth and yield of prawns in a commercial setting, but also when in the season each water-quality parameter is important:
The precise relationships are likely to be farm-specific, but because the techniques in teh paper are data-driven they can be used to gather local insights wherever pond water quality is being monitored. |
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