See Disease Before It Strikes: AI-Powered Protection for Vineyards
How Deep Planet Predicts Vineyard Disease with AI and Satellites
In viticulture, disease disrupts entire growing seasons. Early detection is key to protecting yields, maintaining grape quality, and avoiding unnecessary input costs.
But traditional methods for identifying disease in vineyards are reactive, slow, and expensive. They rely on manual sampling; agronomists walking rows and inspecting the canopy, ultimately extrapolating risk from limited physical data. It’s time-consuming, labour-intensive, and often too late.
At Deep Planet, we’re taking a proactive, data-driven approach that uses artificial intelligence, satellite imagery, and ground truth data to forecast disease probability and reduce detection times compared to traditional methods.
The Problem: Disease Doesn’t Wait
Growers are especially vulnerable when:
Recent weather events raise the risk of infection
In-field early disease detection requires significant expertise
Resources are limited and action must be precise
The Solution: AI-Powered Disease Probability Maps
Deep Planet’s disease prediction tool provides:
Per-pixel disease risk maps across entire vineyard blocks
Updated predictions available at near daily frequency
Accurate detection of the 3 most prevalent diseases:
Downy Mildew (Plasmopara viticola)
Powdery Mildew (Uncinula necator)
Botrytis Cinerea
AI models trained using:
Sentinel-2 (10m) and PlanetScope (3m) imagery
Vegetation indices (e.g., NDVI, GNDVI, SIPI)
Weather, soil, and terrain data
Ground-truth observations collected by agronomists
Near-90% detection accuracy in field trials
(89.6% DM, 93.7% PM, 91.5% Botrytis)
These maps highlight where it’s likely to emerge, helping growers focus scouting and treatment directly where needed.
How It Works
Using our AI models, we simulate a predictive disease scenario that shows spatial variation in risk across your vineyard:
Environmental triggers (rain, humidity, heat) increase the probability of infection
Spectral imagery identifies early stress signals in vegetation
Our ML pipeline combines this data with grower-specific factors to produce disease likelihood maps
Growers act: Target sampling, apply treatments, and avoid blanket spraying
Why This Matters for Growers
Avoid over-spraying by targeting only the blocks at risk
Improve scouting efficiency and reduce labour
Save time by catching early-stage infections before visual symptoms are identified
Use your own field data to refine the model further
And most importantly: this tool empowers growers to be in control, rather than reacting after the damage is done.
Results You Can Trust
In field trials across four UK vineyards (Chardonnay & Pinot Noir), our AI models were validated using European disease protocols and ground-truth data collected from August to October 2024.
Models accurately flagged early-stage infection zones
Growers used maps to refine spraying and sampling
Risk maps were updated regularly to account for changing conditions
“Supported by our Prototyping and Demonstrator Fund and access to the Wine Innovation Centre, Deep Planet has created a precision viticulture solution that helps growers identify disease patterns, optimise harvesting, and improve crop quality—bringing their technology to market in under a year.”
— Dr. Belinda Kemp, Group Leader for Viticulture and Oenology Research, NIAB East Malling
Our real-time insight allows growers to adapt with precision whether they’re managing outbreaks triggered by weather or fine-tuning treatment at the block level.
Ready to Predict Before You React?
Don’t wait for disease to appear. Let Deep Planet help you spot it early—with confidence and precision.
Book a demo today to see your vineyard through the lens of AI: https://calendly.com/hello-deepplanet/30min?month=2025-09