PILOT : PRECISION AGRICULTURE IN OLIVES, FRUITS, GRAPES AND VEGETABLES

This pilot is targeting towards providing a set of smart farming services to the farmer utilizing available precision agriculture techniques. The services will be provided as advices, which need many prerequisites and primary material in order to be accurate.

Data is the raw material and there are three different means of collecting data, which will be exploited within the pilot activities:

• data directly from the field, collected from a network of telemetric IoT stations called GAIAtrons;
• remotely with image sensors on in-orbit platforms;
• and by monitoring the application of inputs and outputs in the farm (e.g. in-situ measurements, farm logs, farm profile).

Every data source has unique characteristics with relevant impact on the very content of this data. Field sensing provides real-time accurate direct measures of many physical parameters of the soil (soil temperature, humidity), atmosphere microclimate of the field crop and plant (ambient temperature, humidity, barometric pressure, solar radiation, leaf wetness, rainfall volume, wind speed and direction) with temporal continuity. Remote sensing provides indirect measures of some physical properties of plants and soil with spatial continuity in medium to large spatial scale.

Combining this information can provide a good knowledge of the most important physical parameters of soil, microclimate, plants and water (which are all the environmental resources, which govern farming) in both spatial and temporal dimensions.

Monitoring the application of inputs and outputs on the farm is a data element that is necessary to assess the correctness of the given advice and use it as feedback to improve the system over time.

This pilot will combine advanced data handling techniques (i.e. assimilation, fusion and spatio-temporal interpolation) to transform the collected data into actionable advice.

In order for this advice to reflect the actual situation at a given field, we will deploy scientific models and we will seek to incorporate the human experience of the farmer or certified advisors.

The main expected results of this pilot are:

• to raise the awareness of the farmers, agronomists, agricultural advisors, farmer cooperatives and organizations (e.g. group of producers) on how new technological tools could optimize farm profitability and offer a significant advantage on a highly competitive sector.
• to promote sustainable farming practices over a better control and management of the resources (water, fertilizers, etc.).
• to increase the technological capacity of the involved partners through a set of pilot activities that involves management of big data for high value crops.

The main KPIs of the pilot are:

• reduction potential in operational costs for performing the same farming activities (through better management of resources) following the advisory irrigation, fertilization, pest/disease management services vs what would be the operational costs following standard farming practices based on historical data: Quantify % reduction potential in operational costs for all three crop types (in fresh water/fertilizer usage, sprays following the aforementioned advisory services).
• Increase in farm yield following the advisory irrigation, fertilization, pest/ disease management services vs what would be the yield following standard farming practices based on historical data: Quantify % increase in farm yield for all three crop types.