PEST AND DISEASE PREDICTION
Optimized pesticide usage and better crop quality using digitized prediction models
Recommendations on disease control
By combining built-in prediction models with environmental data, information on pests and disease appearance is created according to their life cycle and plant growing period. Recommendations on when and what type of pesticide to use are provided.
Environmental conditions monitoring
Measurements visualization from installed weather stations (air temperature, air humidity, precipitation, wind speed and wind direction, solar radiation…).
Smart pheromone traps and advanced analytics for optimized insecticide usage
Monitoring insects’ activities
Smart pheromone traps are used to monitor insect activities. Traps are equipped with camera that takes images of caught insects. Images are automatically processed.
Automatically counting the number of caught insects
Advanced algorithms count the number of caught insects thus providing insight into population dynamics.
Combining real-time field measurements with crop-specific advanced analytics methods to optimize irrigation
“Irrigation recipes” creating
By combining specific crop water requirements, with the soil type characteristics, measured soil moisture, forecast precipitation and temperature, irrigation recipe is created to provide instructions for the optimum time to irrigate as well as the amount of water to be used.
Soil conditions monitoring
Real time monitoring of soil moisture, soil temperature and soil salinity on different depths providing insight into soil conditions for crop growing.
Gives the tentative amount of used water according to the daily evapotranspiration and plants’ coefficients.
When to protect crops and avoid frost damages
Monitoring environmental conditions
Measuring wet and dry air temperature to predict frost appearing.
Early warning when conditions for frost appearing are fulfilled taking into account plant sensitivity during different phenopases.
SATELLITE BASED FIELDS MONITORING
Increased observation accuracy and creating variable fertilization maps
Monitoring crop conditions and stress levels
Satellite images and different vegetation indices are used to provide information about crop vitality, homogeneity/heterogeneity of crop development over the field, field zones with different chlorophyll/nitrogen and water content, soil moisture zones etc.
Creating variable soil maps
Creating customized maps for soil sampling based on different vegetation indices for preparing variable fertilization maps.
Tracking agricultural machinery to optimize costs
Monitoring machinery activities thus having insight into quality of taken activities and additionally fuel consumption, driving style, working hours, etc.
Planning of machinery usage
Real time insights into whereabouts and activities of the machinery enables more efficient planning of their usage.
Recording all finished activities to improve planning new ones
Simple and easy recording of all activities during agricultural production thus providing traceability during the production process and better insight into indicators of successful production.
Reports are created to provide complete overview of all activities and costs, possibility for comparing different vegetation periods and better planning upcoming seasons.