Proactive disease management with AI
How Deep Planet Predicts Disease with AI and Satellites
In agriculture, disease disrupts entire growing seasons. Early detection is key to protecting yields, maintaining crop quality, and avoiding unnecessary input costs.
But traditional methods for identifying disease 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
Powdery Mildew
Botrytis
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 partners
The results
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?
Proactive management of assets at risk
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
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 at an accuracy > 90%
Growers used maps to refine spraying and sampling
Risk maps were updated regularly to account for changing conditions
Our real-time insight allows businesses to adapt with precision whether they’re managing outbreaks triggered by weather or fine-tuning treatment.
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