About Global Crop Radar
See risk earlier. Understand it better. Act at the right time.
Global Crop Radar was created around a simple idea: farmers should not have to wait until a crop problem becomes visible to understand that conditions for disease or pest development are already building.
The platform is powered by SysAgria’s proprietary agronomic intelligence, developed through more than 14 years of continuous agronomic research, field experience, statistical analysis and model development. This accumulated knowledge is combined with real-time and forecast environmental data to transform complex information into clear, localized crop-risk intelligence.
Our goal is to help farmers, agronomists and crop advisers understand:
- what is happening now;
- how risk is evolving;
- why it is changing;
- what could happen next;
- when attention or intervention may be required.
Global Crop Radar brings together meteorological, environmental and field data, updated as new source data becomes available, and processes it through SysAgria’s agronomic knowledge base and crop disease and pest models.
The result is a dynamic view of crop risk, from individual monitoring locations to wider geographic areas.
From weather data to agronomic intelligence
Weather data alone does not tell a farmer what is happening to a crop.
Temperature, humidity, rainfall, leaf wetness, wind and other environmental parameters become useful when interpreted in the context of:
- the crop;
- the disease or pest;
- biological development conditions;
- infection and incubation dynamics;
- historical patterns;
- current and forecast conditions.
Global Crop Radar recalculates this interpretation automatically, according to source and model update schedules.
Instead of simply showing environmental measurements, the platform helps answer more useful questions:
- What is the current risk?
- Is the risk increasing or decreasing?
- What is driving the change?
- What could happen over the coming days?
- When should I pay attention or consider taking action?
One global radar. Multiple data sources. One agronomic intelligence engine.
Global Crop Radar is designed to be independent of any single weather-station manufacturer or meteorological provider.
The platform can combine data from:
- physical agricultural weather stations;
- virtual weather stations;
- professional meteorological data providers;
- satellite and environmental datasets;
- compatible third-party sensor networks;
- additional agricultural data sources as they become available.
These different inputs are normalized and processed through the SysAgria agronomic intelligence engine.
This architecture allows the Radar to use the most appropriate available data for each location while maintaining a consistent agronomic methodology.
An open monitoring network
More than 850 physical agricultural weather stations already contribute real field measurements to the network.
But Global Crop Radar is designed to grow beyond any single proprietary station network.
Compatible weather-station and agricultural-sensor manufacturers can connect their infrastructure through API integrations and contribute data to the platform.
This means existing agricultural hardware can become part of a much larger crop-intelligence network without needing to be replaced.
Any compatible station can contribute.
As the network expands, Global Crop Radar can combine physical measurements, virtual monitoring and additional environmental data across increasingly large geographic areas.
Built to grow with agriculture
Global Crop Radar is not designed around a permanently fixed catalogue of crops, diseases or pests.
Agriculture is too diverse and dynamic for that.
Different countries grow different crops. New pests migrate into new regions. Disease pressure changes. Climate conditions evolve. New monitoring technologies become available.
The platform is therefore designed so that new:
- crops;
- diseases;
- pests;
- agronomic models;
- environmental parameters;
- data sources
can be incorporated into the Radar as they become available.
When a relevant new crop, disease or pest needs to be monitored, the intelligence layer can be extended with the corresponding model.
The Radar grows with the needs of agriculture.
From individual virtual stations to a continuous risk picture
A virtual station calculates risk for a specific monitoring location.
Where sufficient compatible monitoring stations are available, Global Crop Radar can combine nearby observations to interpolate risk between virtual stations and create a broader local risk picture.
This allows users to move beyond isolated measurements and understand how disease pressure varies spatially across an agricultural area.
The objective is not simply to collect more data.
It is to turn distributed agricultural data into useful spatial intelligence.
Intelligence that explains itself
Knowing that risk is high is useful.
Understanding why it is high is more useful.
Global Crop Radar helps users understand the environmental factors contributing to risk, follow how conditions evolve and compare current conditions with forecast development.
This makes the platform a decision-support system rather than simply an alerting service.
Meet LoveToGrowâ„¢, your AI agronomic assistant
Global Crop Radar also includes LoveToGrowâ„¢, an AI-powered agronomic assistant designed to make the intelligence generated by the platform easier to understand and use.
LoveToGrow combines the SysAgria agronomic knowledge base with information available from the user’s monitoring environment.
Farmers and agronomists can ask questions such as:
- Why is disease risk increasing in this field?
- Which conditions are driving the current risk?
- What is expected over the next 48 hours?
- Which virtual stations require my attention?
- What should I consider doing next?
The assistant is available through the platform and, for supported subscription plans, can also be connected through WhatsApp, allowing the conversation with the farm’s agronomic intelligence to continue outside the application.
The Radar does not only alert you. You can talk to it.
Why Global Crop Radar exists
Crop-protection decisions are often made under uncertainty.
Intervene too early and resources may be used unnecessarily.
Intervene too late and the crop may already be exposed to avoidable damage.
Global Crop Radar is designed to reduce that uncertainty by helping users:
Identify favourable conditions earlier
Identify favorable conditions before a problem becomes clearly visible in the field.
Understand what is changing
Follow risk evolution instead of relying on a single measurement.
Monitor exactly where it matters
Create virtual monitoring locations for individual fields and production areas.
Prioritize attention
Quickly identify locations and crops where risk is highest or increasing fastest.
Improve intervention timing
Use risk evolution and environmental conditions to support better-timed crop-protection decisions.
Reduce unnecessary interventions
Avoid treating simply because of a calendar date or generalized regional warning.
Protect yield and investment
Make crop-protection decisions with more information and less uncertainty.
Our Vision
Our vision is to build a global crop-risk intelligence layer capable of operating across multiple agricultural data networks.
A farmer should not need a particular brand of weather station to benefit from advanced disease intelligence.
A sensor manufacturer should not need to develop an entire global disease-modelling platform to make its data more valuable.
An agronomist should not need to manually interpret thousands of environmental measurements to identify which fields require attention.
Global Crop Radar connects these worlds.
Environmental data comes in.
Agronomic intelligence transforms it.
Clear crop-risk information comes out.
As more virtual stations, physical stations, crops, disease models and data networks become connected, the Radar can provide an increasingly comprehensive view of crop risk across regions and countries.
Make advanced crop-risk intelligence accessible anywhere agriculture happens.