If you’ve ever flown over a shrimp farm or even looked at satellite pictures of one, you see a range of colors from bright green to dark brown. And if you look at the same set of ponds the next day, they won’t all be the same. Some will have changed in shade and others even in color entirely.
So why is that? And what does it mean for farmers? We explore that in this week’s post.
Microbiology is the Driver of the Pond
Outdoor ponds are not a constant environment, especially not when they are being controlled by a farmer with nitrogen (food) added into them every day. They change and shift depending on a series of factors and the driver of this change is whatever microbiological species is dominant at the time. How species interact with the pond and the animals in it is key to both the type of outcome a farmer will see, positive or negative, from that cycle, and how consistent their crops are cycle to cycle.
Outdoor ponds, especially those without a specific microbiological intervention like Bio-floc or aqua mimicry are known for having a progression of microbiological species with specific ones dominant at different times. In the beginning of a cycle, the water is generally fresh which gives room for more algal-based species to take over. But as nutrients build up in the pond, more bacterial species take over and the pond can transition to brown.
This is the general pattern, but it is far from predictable and the norms. The times that farmers often need to take the most care is in watching their ponds is when these transitions occur where one species suddenly dies and another rises in its place.
Water Color + Turbidity
The way farmers can watch for shifts in the microbiology in the pond is in the water color and turbidity of it as they will turn the pond a different color and introduce other particles that the water will reflect off of.
What we are excited about with Osmobot is that we will actually have a lens into the water color and turbidity of the pond and can start tracking these changes from within the pond in real time.