Development of ground based and Remote Sensing, automated ‘real-time’ grass quality measurement techniques to enhance grassland management information platforms (GrassQ)

The focus of this project is to develop and enable an intelligent system that will apply precision management to whole farm grassland and grazing systems. The goal is to optimize grass quality, utilization efficiency, and ultimately profitability, with minimal labour requirement and maximum objectivity. To precisely allocate to the cow herd the absolutely correct area of grass, it is necessary to have an accurate ‘real-time’ measure of grass quality and quantity. GrassQ-project will use two fundamentally different techniques to derive this grass quality measure, either by automated grass quality data capture by a near infrared spectroscopy (NIRS) sensor at ground level or by Remote Sensing image data captured using satellite or unmanned aerial vehicles (UAVs) and subsequent predictive modelling. This project provides a unique opportunity for these two techniques to be operated in parallel. The output or product of this research will be the provision of high quality, ‘real-time’, geo-tagged information in the form of herbage mass, and specifically grass quality, through a user friendly software package on a Smartphone App or web-based decision support system (DSS).

Contact persons
Keywords
remote sensing
photogrammetry
radiometry
UAV laser scanning
Duration
Research area
Research groups
Funding organisation or partners
FGI
EU
Other funding sources
EU-rahoituslähde: ICT-AGRI ERA-NET/maa- ja metsätalousministeriö
Project partners
TEAGASC - Agriculture and Food Development Authority (Irlanti), SEGES P/S (Tanska), Cork Institute of Technology (Tanska), Maynooth University (Irlanti), TrueNorth Technologies (Irlanti), AgroTech A/S (Tanska), TreeMetrics Ltd (Irlanti)
Luonnonvarakeskus Luke (Suomi), Work, Buildings and System Evaluation (Sveitsi), ASCENDXYZ (Denmark)