We are a land of ranchers, roughnecks, foresters, and farmers.
We have tilled the earth through unforgiving prairie winters and we have thrived while doing it.
Our beautiful prairie landscape is painted yellow with budding canola.
yOIL is a multi-faceted attack on the green seed problem.
The system utilizes water-soluble-chlorophyll binding proteins emulsified in water droplets to remove chlorophyll molecules from oil. The captured chlorophyll will then be repurposed into pheophorbide, an experimental photosensitizer with potential as an anti-fungal agent.
To address ambiguities that arise when farmers take their seeds to be graded, our team developed a standardized seed grading platform, lovingly called "Mean Green Machine" which automates the grading process. We took the Mean Green Machine (MGM) to The Canadian Grain Commission where they gave us vital feedback to help move MGM closer to a fully-implemented product.
Inclement weather is what causes green seed, and knowing the weather lets farmers make crucial decisions regarding their crop. We cannot control the weather, but we can create tools to predict it. After all, everyone could use more Sunny Days. Based on Recurrent Neural Networks and Principal Component Analysis, Sunny Days is a weather predictive algorithm capable of predicting the weather 180 days into the future with a mean absolute error of 2.0 degrees.
An All-Encompassing Solution to the Green Seed Problem
We have submitted 28 new parts to the Biobrick registry, created 7 models which informed our project design and held over 35 meetings with stakeholders, not to mention the innumerable number of hours in the lab (plus an extra 8 to travel to Boston).
After all is said and done, it is our privilege to present