The proposed project will undertake fundamental and innovative research to provide information to enable accurate decision-making for precision grazing management. The output product of this research will be the provision af high quality, 'real-time' information in the form af herbage mass, and specifically grass quality, through a userfriendly software package an a Smartphone App or web-based decision support system (DSS).
The research will present a solution in the form af an automated measure af grass quality as defined by % dry matter (DM), % organic matter digestibility (OMD) and % crude protein (CP), which can be conducted in a 'real-time' manner (presented to the end-user by the Smartphone App/DSS). Two very different techniques will be used to derive this grass quality measure, both af which represent new research, 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 ariel vehicles (UAVs).
This project provides a unique opportunity for these two techniques to be operated in parallel.