GrassQ is an ICT-Agri Era-Net funded EU project aimed at developing and combining precision grass measurement systems into a web based decision platform to aid precision grassland management. Novel and conventional systems of measuring grass yield and quality were developed and refined in Ireland, Denmark, Finland and Switzerland. The measurement parameters were compressed sward height (CSH, mm), herbage mass (HM, kg DM ha-1), dry matter (DM, g kg-1) and crude protein (CP, g kg-1). A protocol was developed for the rising plate meter (RPM), for grass measurement optimisation. Initial evaluation indicates mean CSH can be predicted to ± 5% SE using 35 samples ha-1. Region, sward and seasonal specific HM prediction models are being developed to further increase the accuracies of the RPM (R2 > 0.7). A preliminary lab based near infrared spectroscopy (NIRS) fresh grass quality calibration was developed with positive results (R2 > 0.94 and R2 > 0.90, for DM and CP). An alternative technology of multispectral sensing was carried out using a range of airborne methods including an Unmanned Aircraft System (or Drone) and data from the EU Sentinel 2 satellite were also acquired. Grass biomass was estimated at a reasonable level by processing Sentinel-2 and Drone multispectral data using partial least square regression (PLSR) and at a moderate level using stepwise multilinear regression (MLR). In Finland, estimations for grass silage swards using Random Forest (RF) analysis with 3D features and based on point cloud and image spectral features, indicated R2 values similar to those obtained in Ireland. The prototype GrassQ web platform using data from the aforementioned models, is now operational and currently under evaluation.