Case Study: LIAT achieves 95% model accuracy for strawberry yield forecasting with V7 Labs

LIAT boosts strawberry yield prediction accuracy to 95% with V7 Labs

The University of Lincoln's LIAT, a team developing technologies for the food chain, faced the challenge of accurately predicting strawberry yields. Historically unreliable forecasts led to high labor costs and supply chain waste. They turned to V7 Labs and its V7 Darwin platform to build a computer vision system for this difficult task.

V7 Labs' solution provided advanced data labeling and versioning tools, which LIAT used to annotate image data and train AI models. This implementation improved the model's accuracy from 85% to 95% and extended yield prediction times from 3 to 5 weeks ahead. The result was higher profits for farmers, reduced crop waste, and industry-leading performance for the university's project.

LIAT