1. QUO VADIS PRECISION FARMING
International Conference on Precision Farming
St Luis Missouri,
QUO VADIS PRECISION FARMING
K. Charvát, T. Řezník, V. Lukas, K. Charvát Jr., Š. Horáková, M. Kepka, M. Šplíchal

2. How is defined Precision Farming?
The management practice with the potential to increase profits by utilizing more precise information about agricultural resources
The application of technologies and principles to manage spatial and temporal variability associated with all aspects of agricultural production for the purpose of improving crop performance and environmental quality
The new agriculture technology designed to monitor, analyses and control plant production to optimize costs and ecological effects
High precision positioning systems (like GPS, Automated steering systems, Geomapping, Sensors and remote sensing, Integrated electronic communications Variable rate technology (VRT)
Intensive sensing of environmental conditions in the crop, Extensive data handling and processing, Use of decision support systems (DSS), Control of farm machinery in the field.

3. Question? Are these definitions broad enough?
Cover real all aspects of Precision Farming?
Are they really focused on future challenges?
And one provocative question more:
“Is really precision farming new concept?”

4. Future Challenges for Farming Sector
Climate changes.
Demographic (Growing population, Urbanisation and land abandonment).
Energy cost.
New demands on quality of food (Food quality and safety).
Aging population and health problems.
Ethnical and cultural changes.
Innovative drivers (Knowledge based bio economy, Research and development, Information and communication, Education, Investment).
Policies (Subsidies, Standardisation and regulation, National strategies for rural development).
Economy (Economical instruments, Partnerships, Cooperation and Integration and voluntary agreements).
Sustainability and environmental issue (Valuation of ecological performances, Development of sustainable agriculture).
Public opinion (Press, International Organisation, Politicians).

5. Knowledge management levels
Macro level, which includes management of external information, for example about market, subsidies system, weather prediction, global market and traceability systems, etc.)
Farm level, which include for example economical systems, crop rotation, decision supporting system.
Field level including site specific farming, collection of information about traceability and in the future also robotics.

6. Challenges versus information flow

7. Broader understanding of Future Precision Farming
Utilization of effective knowledge management for decision processes on the farm based on:
External information
Farm Information
Filed information

8. Challenges Interoperability Access to data Big data
Social organization of farmers’ decision-making
Trust of information

9. Interoperability

10. Access to data For farmers is difficult to access external data
Open data policies has to help farmers with better access to different data (weather, ortophotos, satellite, sensors)

11. Big data Local weather data, GPS data from machinery Soil sampling
Ortophotos and drons
Satellite imagery
Soil specifics,
Soil conductivity,
Seed
Environmental protection data
Machinery characteristics
Fertilizer and crop protectant specifications
Market needs
Subsidies systems
and many more.

12. Social organization of farmers’ decision-making
Are farmers able to manage all this information
Probably not
So it will require added value chain of services, who will be able to support farmers
But this services has to be financially reasonable and need to brings financial benefit for famers
Question is, which from expected services will be really accepted by farmers

13. Trust Data privacy will be one from key aspects of future
To achieve the acceptation of any platform by farmers, the data privacy needs to be guaranteed.
Data ownership and data privacy is a major issue with regard to data used and produced on the farm, and forest.
Multiple sources of data need to be integrated in order to be useful, and ownership and control become major issues, quite apart from the technical challenge of allocating value in such complex scenarios.
Data produced by farmers and forest owners needs to be suitably protected both for reasons of privacy and ownership.
This task will combine legal, ethical and technical approaches to make data usage both possible and attractive to the relevant actors.

14. Examples of solutions, where we are working on
Tactical planning
Sensors
Farm Telemetry
Delineation of management zones based on satellite remote sensing

15. Tactical planning
The main purpose of tactical planning is to recommend optimal production and land use for next seasons to maximize expected profit.
The problem could be described such as a farmer has a number of parcels with different properties available for his production.
It is possible to grow different kinds of products on these lands. On each of these lands it is possible to grow maximum one product using different production methods

16. Sensors

17. Farm Telemetry

18. Delineation of management zones based on satellite remote sensing