Data-driven agronomy: Key metrics and how AI can power the future

The future of agronomy is data‑driven — but success starts with understanding and mastering the right metrics. In this class, we will dive into the critical KPIs that underpin modern turf management and how AI can help unlock even greater potential.

We will review essential agronomic metrics such as Growing Degree Days (GDD), Clipping Yield Volume, Nitrogen Use Efficiency (NUE), Soil Moisture Dynamics, Evapotranspiration (ET), and Field Capacity / Irrigation Thresholds.

The class will then explore how AI‑powered tools can transform the use of these indices, providing predictive insights, enhancing decision‑making, and optimising interventions with real‑world examples and case studies.

Attendees will be equipped with a practical checklist of data metrics to monitor, and show how AI can enhance interpretation, efficiency, and performance outcomes.