Case Study

Ponix: Math Meets Food Security

Using regression analysis and a USDA grant to build hydroponic systems and feed my community.

The Challenge

I received a grant from Ponix in conjunction with the USDA to build hydroponic towers in my community. The towers were straightforward to build — but growing food efficiently wasn't.

The problem: calculating ideal nutritional growth environments for plants. Too many variables — pH, nutrient ratios, light cycles, temperature — to rely on guesswork.

What I Built

1

Hydroponic Towers

Built physical growing systems on site using the USDA grant. Vertical tower design for space efficiency and modular expansion.

2

Growth Modeling

Used trial-and-error combined with regression analysis to calculate optimal nutritional environments for plants. Tracked pH, nutrient concentration, and light exposure.

3

Food Distribution

Grew hydroponic lettuce and distributed produce to local food drives. Fresh, soil-free greens for families who needed them.

4

Data Pipeline

Tracked growth variables across harvest cycles, ran regressions on yield data, iterated on growing conditions to maximize output per tower.

The Results

USDA
Grant Secured
Ponix partnership
Regression Models
Growth optimization
Food Drives
Community fed
🌱
Systems Built
Hydroponic towers

What I Learned

  • Real data is messy — regressions work anyway if you ask the right question. Lab-perfect conditions don't exist outdoors. The model adapted.
  • Math applied to biology feels different than math on paper. The plants don't care about your model, only the results. If your predictions don't match reality, the model is wrong.
  • Community impact makes the math feel like it matters. Calculating nutrient ratios isn't abstract when it means someone gets fresh lettuce.

Want to see what else I've built?