The coming freshwater supply crisis prompts a need to design food-growing methods that require less water than current methods do. Hydroponics provides one such method. Here I report on my recent effort to design and build a hydroponic strawberry grower.
But first, what does this have to do with data science? Not much at the moment, but I envision data scientists will soon model freshwater supply and demand as the crisis accelerates, from ecological, economic, and military viewpoints. It is likely that one of us will incorporate hydroponics into such a model. Similarly, large commercial growers using hydroponics will require systems modeling to optimize production, an engineering task well suited for data science talent.
Here is a photo of my first-generation grower design:
This design uses a “flood and drain” method where nutrient solution (compost tea) is allowed to saturate the growing media, and then excess nutrient solution is drained and stored for later use. A small amount of nutrient solution remains in the grower after draining the excess, which the growing media “wicks” up to the plants’ roots.
I’ll report in future posts how this is going.