PUNURMIO
Automatic method for grass biomass estimation and prediction
The national EIP project PUNURMIO develops a method that enables farmers to automatically assess and predict grass biomass growth. The aim of the project is to improve grass yield, support climate-smart agriculture, and reduce the carbon footprint of milk and meat products.
Official name
Development of automatic methods for grass biomass estimation, monitoring and prediction – PUNURMIO
Duration
5/2024–12/2026
Persons in charge
Joni Kukkamäki, project manager (HAMK); Satu Koivisto, project coordinator (HAMK)
Organisations
Häme University of Applied Sciences HAMK, Finnish Meteorological Institute FMI, Baltic Sea Action Group BSAG, and Gofore Oyj
Funder
European Agricultural Fund for Rural Development (EAFRD)
European Innovation Partnership (EIP)
Funding granted by: Häme Centre for Economic Development, Transport and the Environment (ELY Centre)
Grass biomass estimation and prediction automatically
Agricultural emission reduction targets affect farmers due to both the reduction demands set by the food industry and the climate goals and subsidy policies of the public sector. Simultaneously, the rapid increase in farm sizes and the pressure to improve production efficiency push producers to enhance their operations in an environmentally sustainable way. High grass yields generally have a positive effect on carbon sequestration in the soil, thereby reducing the carbon footprint of the final products. This factor is crucial in climate-smart milk and meat production, where optimizing grass yields plays a key role.
The goal of the PUNURMIO project is to develop a method for the automatic, field-specific assessment, monitoring, and prediction of grass biomass growth. The method is using machine learning and based on locally collected data from images taken with a phone camera and other sources, such as local weather forecasts and soil data. Farmers submit the images and data via a mobile interface, and the resulting assessments and forecasts are delivered back to the farmer. The method will be tested on pilot farms and selected test fields through a partner network, and the results will also be compared to biomass estimates derived from satellite imagery-based modeling.
Project objectives:
- Develop an automated method for estimating grass biomass quantity based on images and other agricultural data.
- Explore possibilities for assessing the nutrient content (D-value) of grass biomass using image-based methods.
- Build a prototype of a mobile tool (application or web interface) suitable for farmers to use, which is easy to operate and enables smooth and user-friendly functionality in field conditions.
- Test and validate the developed method on pilot farms selected for the project and on other suitable test fields.
- Disseminate information about the project’s activities, measures, and results to its target groups, the research and development community, and the general public.
Contact
Project manager: Joni Kukkamäki, HAMK, joni.kukkamaki@hamk.fi
Project coordinaator: Satu Koivisto, satu.koivisto@hamk.fi
Finnish Meteorological Institute: Layla Höckerstedt, layla.hockerstedt@fmi.fi
PROJECT PARTNERS
