Data for growth and farm performance

The project aims to establish South Ostrobothnia as a pioneering region in agricultural data economy. The goal is to produce widely scalable, machine-readable, and cost-effective mass data for use by farms, the food chain, and society. The project integrates satellite and drone data with yield quantity and quality data measured from harvesters, which are utilized in machine learning models. This enables the development of cost-efficient and high-quality information and software solutions that can be directly applied on farms.

The production, storage, integration, and analysis of large datasets and point clouds—and their application in cultivation decisions or machine automation—require new data, expertise, and collaboration. Practical cooperation and technology models will be built to help farms adopt artificial intelligence and data analytics to support decision-making. For example, intelligent analysis of soil surface and biomass data enhances cultivation practices, automation of field machinery saves fuel and reduces soil degradation, and precision fertilization minimizes environmental impacts.

The results can be replicated in other regions, and the data can also be utilized in other sectors, such as natural resource monitoring and climate-smart planning. The actions support rural vitality, sustainable development, and agricultural profitability. They improve farms’ ability to utilize data and AI in practice, and lay the foundation for new product development, business opportunities, and international collaboration.

As South Ostrobothnian farms produce new datasets required by both traditional and AI-based software, the resulting services will also be developed in South Ostrobothnia. This is significant, as the region itself is not a major player in international commercial agricultural software and AI development. After the project, farms will have access to data tools that help improve production quality, reduce risks, and develop climate-resilient farming.