Photosynthesis diversity dataset collection

Trait Discovery

We’re assembling the world’s most diverse plant performance and genetics datasets.

These unique datasets allow us to build models with unprecedented predictive power in crop plants.

By working backwards from real phenotypes, we develop traits that are already proven to work in nature and adapt them for crops.

Rapid Screening

Our evolutionary hypotheses give us testable mechanistic predictions at the cellular level.

We iteratively test our predictions in rapid crop cell assays.

This helps us prioritize successful designs, allowing us to move directly into elite crop varieties and bypassing the need for model plants.

Wheat protoplasts isolated for testing trait designs
Precision bred wheat plantlets in regeneration

Variety Creation

Our traits are designed to be stackable and translational across crops.

For each crop, we select the optimal variety x trait stack(s) to maximize crop performance.

We introduce these optimized designs into elite crops by modern precision breeding techniques developed at Wild.

Field Performance

We use a global network of trial locations to accelerate evaluation of our varieties where it matters – in farmers’ fields.

Data generated at each step is fed back into our AI models to create a continuously improving feedback loop.

Drone data taken at a soybean field trial in Argentina