Premium Grain Chain (PGC)

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Premium Grain Chain (PGC)

Key Objective

Create an industry-wide data-enabled quality label for premium grain-based food and beverage products

Challenge Addressed

  • How to manage data flows and infrastructure for data categories: Sustainability, Food Quality, Traceability
  • How to realize premium grain chain data-enables quality label?
  • How to build trust and positive engagement with novel solutions in the food sector

Type of Stakeholders

PGC is branded as a common activity of the members of the AgriFood Data Space Finland (AFDSF) ecosystem that currently has over 50 members of the AgriFood Data Space Finland which includes: farmers, farming cooperatives, farming machinery, soil analytics services, food processing companies, retailers, IT solution providers, etc.
Case Study Acronym:PGC
Long Title of the Case Study:Premium Grain Chain
Case Study Main Contact:

Marko Turpeinen,
1001 Lakes 

Countries involved and main place of the Case Study:Multiple locations in Finland
Part of the Food System addressed:Farming, food processing, food retail and exports

Case Study Summary

Our case study contributes to creation of new sustainable business thinking for the agrifood sector based on an open ecosystem concept that emphasizes holistic member value creation rather than individual interests and desires. The case study can be used as an example of data space put in practice to concretely help the agrifood industry.

Multiple user groups will benefit from the use case. Farmers can leverage their data as a community (our data) and seek market power and product market value through data-driven collaboration. Food processing industry can verify market claims based on data and increase the market value of their products. Agricultural machinery and tech solution providers become can operate in and exploit the data space environments to their business benefits.

We apply the Sitra Fair Data Economy Rulebook model for the Premium Grain Chain use case to create an agrifood-specific rulebook that addresses the business, legal, ethical, and technical aspects of data sharing in the value chain.

Motivation and key expected Outcome

The expected outcome is that a premium quality label can be based on the systematic collection and use of the following types of shared data:

Key Sustainability Indicators include:
  • CO2 emissions
  • Biodiversity
  • Water footprint
  • Ecotoxicity
These indicators will be calculated using modular and extensible methods that combine measurements taken from sattelites, drones and IoT data.

Aspects of grain variety (weight, yield, protein%, moisture% etc.) data made available; Data needed to verify premium product quality parameters (organic, nutrient richness, health effects, gluten free) measured; Collecting batch-level data from the farm to verify whether the quality criteria are met, for example for the needs of spirits industry.


Combining traceability capabilities with detailed quality and sustainability indicator calculation results; QR-code based tracking back to the individual farm & batch; Using the "Grain Passport" consignment note in transferring the data when a batch of crop is sold and delivered


Farm cooperative situational awareness of supply and demand; Virtual warehouse combining individual farm data on current and expected grain availability; Joint order process management for grain export.

Main Partners of the Case Study

1001 Lakes Oy
Case study coordinator and data space experts

Contact: Marko Turpeinen

Luonnonvarakeskus (Luke)
Case study data and domain knowledge experts

Contact: Liisa Pesonen

Other Stakeholders involved in the Case Study realisation, but not direct project partners
  • DataSpace Europe Oy
  • University of Helsinki
  • The Central Union of Agricultural Producers
  • Forest Owners (MTK)

Food Value Chain

Farming, food processing, food retail and exports actors, with case study focus on grain-based food and beverage products where there is a clear business advantage to be able to show that the desired quality criteria have been met. Examples include grain-based spirits, processed oat-based food and drinks.

Cross collaboration
with other Projects or Initiatives

The use case has been shortlisted by one of the top three key use cases of the AgriFood Data Space Finland (AFDSF) ecosystem. It has strong support of the ecosystem actors and will be a showcase for recently established data space intermediary company DataSpace Europe Oy that is focussing on agrifood.

The use case is also aiming to link with other use cases in Data4Food2030, and especially with use case #3 (AgData-Interoperability – TEUDS).

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