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List of technologies

Variable soil treatment

Selection of soil treatment depth based on physical and chemical properties of soil (compaction, lumpiness, pH, soil conductivity, etc.)

Variable application of plant protection products according to the map of occurrence of harmful factors

Shutdown of sprinkler sections, plant protection according to the map of occurrence of harmful factors, desiccation according to the application map.

Utilization of drones for application of plant protection mixture

The use of unmanned aerial vehicles (UAV drones) especially for the selective application of pesticides.

Using satellite imagery for management of crop production

The use of satellite imagery to monitor the condition of vegetation (estimate yield, uneven emergence, damage caused by erosion, animals, weather), including the processing and interpretation of results.

Using field robots in fruit and vegetable production

It includes a wide range of operations: planting, pruning, bundling, harvesting, sorting, etc.

Use of unmanned vehicles for the management of crop production

Use of drones or other unmanned means to monitor crop status (yield estimate, uneven development, damage caused by erosion, wildlife, weather), including the processing and interpretation of results.

Telematics for tractors and other agricultural machinery

Continuous collection of traffic data, storing and subsequent evaluation - eg. fuel consumption, tensile strength, slippage, working and nonworking drives, etc.

Monitoring of wildlife animals on farmland and in forests using drones

The use of unmanned aerial vehicles (drones) for monitoring wildlife to detect size of their population, for planning measures to reduce damages etc.

Monitoring of outputs from cereal and oilseed harvests

The equipment of harvesters by GPS receiver and yield sensors, creating and interpreting yield maps.

Mapping the quality of harvested crops during harvesting of cereals and forage crops

Equipping combine harvesters and cutter harvester with GPS receiver and product quality sensor (to measure moisture, damage, N-substance, etc.).

Mapping harvest yields of root crops

Equipment of potato harvesters and beet harvesters with GPS signal receivers and yield sensors, generation and interpretation of yield maps.

Guided drive of tractors and agricultural machinery on parcel with 2 cm accuracy

Selecting the trajectory of machines on the basis of GPS coordinates and RTK corrections, (A-B line, optimization based on the shape of the plot, movement along the contour line, controlled traffic farming etc.

Guided drive of tractors and agricultural machinery on parcel

Selecting the trajectory of machines on the basis of GPS coordinates with accuracy in meters (A-B line, optimization based on the shape of the plot, moving along the contour lines, etc.).

Creation of maps of physical and chemical properties of soil

Compaction, lumpiness, pH, soil conductivity, etc., which are then used for variable soil treatment.

Creating application maps for fertilization

System for the collection and processing of data on soil usage eg. agrochemical soil testing, yield maps, etc., resulting in the application map for basic fertilization

Autonomous guiding of agricultural machinery

Automatic machinery guidance by the edge of vegetation, forage harvesters by current state of vegetation, and machinery for tillage by plants or according to the land relief (ridges), etc.

Automatic setting of fertilization dosage based on current state of vegetation

Automatic on-the-fly dose fertilization setting according to the data from optical sensors (eg. N-Sensors).

Automatic regulation of row seeding based on seeding map

E.g. cereals. Automatic seeder settings (seed rate, sowing depth) by planting maps, site conditions, guiding the drill by soil preparation

Automatic regulation of fertilization dosage based on fertilization map

Regulation of dosage controlled by an embedded fertilization map created on the basis of previous data on nutrient supply.

Automatic control of precision sowing according to sowing map

E.g. corn, beets. Automatic seeding machine setup (speed, depth of sowing) according to sowing map, site conditions, seed drill guidance according to soil preparation

COORDINATOR

Czech University of Life Sciences Prague
Center of Precision Agriculture
Kamýcká 129, Prague, 165 21, Czech republic
E-mail: info@utipa.info

PARTNERS

Slovak University of Agriculture in Nitra Tr. A. Hlinku 2, 949 76 Nitra
Slovakia
www.uniag.sk