Tender

Our aim is to improve the health of soils, reverse degradation and promote sustainable soil management and soil protection.
Within the project, we have developed a laboratory methodology and a soil health decision support expert advice system based on a modern machine learning based algorithm and thus a service that will be commercialised.
The system is novel not only in terms of the measurement and decision-support methodology designed, but also in the fact that the algorithms are based on a large, nationally-covered base database, and thanks to machine learning, the prediction is continuously improving as the database grows, which allows it to provide increasingly complex and reliable advice to producers and advisors.
The primary target audience of the product is the 234,000 farmers who currently farm 4.8M ha in Hungary, but it also provides professional organisations, integrators and traders with a tool to sell products and tools to farmers in a more targeted way, not only to achieve greater farmer satisfaction, but also to contribute to sustainability.

The system created in the framework of the project is not only able to support nutrient management, like most traditional and precision farming advisory systems (Yield Service, PGR), but also to provide new indicators of complex soil condition, health and parameters (microbiological community, numerically described aggregate structure and morphology, organic matter quality, activity), can provide a basis for good and sustainable soil management, bacterial fertilization, cover crop varieties and mixtures, and can provide expert advice supported by a database. It also measures elements that are not part of traditional crop advice but are important to know in terms of their toxicity and soil impact. Concerning physical parameters, the system also includes a new parameter group for the determination of particle size, an important but rarely measured parameter in agricultural advice. By providing more relevant information for the measurement of aggregate shape and size, our system allows the physical and morphological analysis of soils as a primary indicator of the impact of tillage, physical degradation of soils and soil health. In the case of microbiological indicators, the mapping of soil-dwelling colonies by DNA sequencing has provided the basis for targeted microbiological formulation advice, soil harvesting technologies and tillage principles, which have not been substantially represented in expert advice systems so far.

The tools developed during the project provide fast and accurate data on the physical and chemical parameters of the soils under study, partly replacing the use of wet chemistry. The system will reduce the time needed to analyse soil samples by 70%, without generating hazardous waste.

The different soil types occurring in our country have been extensively studied under different farming systems and microclimatic conditions to create a database of unprecedented complexity and size, allowing not only the physical, chemical, soil structure and morphological classification of soils, but also a complex soil health report based on the current farming practices, which will be used as a basis for the development of best available technology recommendations for improving chemical, physical and morphological properties and for stimulating soil life.

The project provides the farmer with a nutrient management plan, a soil management recommendation, a bacterial fertilisation plan, a cover crop recommendation, a complex soil health improvement recommendation, and a long-term sustainable management plan.