ESA title


  • ACTIVITYKick-start Activity
  • STATUSCompleted
  • THEMATIC AREAAI & BigData, Food & Agriculture

Objectives of the service

DAPPO addresses the needs of potato processing companies, storage facilities operators and traders that have long-term agreements with potato growers. The service enables to analyse crop conditions and provides accurate forecasts on potato yield and harvest dates, which are enhanced by the use of AI algorithms. DAPPO can be accessed via a web-based platform or a mobile application. 

Users and their needs

Two customer segments are targeted by the service:

  • Potato processing industry (producers of chips, crisps, flakes, starch etc.) contracting potatoes on a long-term basis, but also growing part of crops on their own or rented fields. Managers of these entities cooperate with farmers and are responsible for analysing and reporting expected yields of tubers for quality management.  
  • Companies that operate potato storage facilities and organize transport and distribution of potato tubers. Managers of these facilities are responsible for securing a regular purchase of high-quality potatoes.

Both groups of users need improved potato crop monitoring and yield forecasting capabilities to improve organisation of potato purchase, transportation and storage. This knowledge is also necessary to assess whether yields from contracted fields fully meet demand, or whether additional supplies are required.

The service addresses the Polish market, but can target other countries where the cultivation and processing of potatoes plays an important role.

Service/ system concept

The proposed service provides users with the following products:

  • potato yield (in kg/ha) estimated at an early stage of the growing season and expected at its end,
  • forecasted harvest date in early and middle part of the season (taking into account weather conditions prevailing during the season),
  • monitoring of conditions (with use of vegetation indices) and development stage (in BBCH scale) of plants in fields,
  • alerts regarding problems with vegetation in certain fields or farms.

In order to provide the above-mentioned functionalities, the service uses satellite data, weather modelling and machine learning algorithms. Predictive issues in the service are implemented using a Multilayer Perceptron neural network.

DAPPO system architecture

Space Added Value

Space assets that will be used in the proposed service are: Earth Observation and GNSS.

Multispectral optical sat-EO data (mainly Sentinel-2) is used to monitor crop parameters. It is also used as input data for AI-based algorithms and models that estimate forecasted potato yield and predict the most optimal harvest date. The technology can provide spatially continuous information that refers to each of the fields in various regions of the country.

Monitoring of a potato field located in central Poland throughout 2020 growing season using Sentinel-2 data.

The dedicated application for mobile devices uses GNSS to locate users on the field and allow to make in-situ measurements and observations.

Current Status

During the Kick-start study service requirements were defined, and the technical feasibility and economic sustainability of the service were assessed. The Kick-start was successfully completed in March 2021.

Status Date

Updated: 09 March 2021