Abstract
Knowledge of forage quality is of pivotal importance to farmers in order to provide animals with a suitable ration. e quality of green forage of permanent meadows can be estimated by means of statistical predictive models taking climatic and meteorological variables, as well as additional information about botanical composition, geomorphologic factors, soil properties and management practices into account. Within the ERDF-project webGRAS such predictive models, developed for 19 parameters with a prediction accuracy (R 2) ranging between 0.32 and 0.71, were implemented into a user-friendly web-application, in order to enable farmers and advisors to estimate the forage quality at the rst cut of permanent meadows in South Tyrol (Italy). e estimation is partly based on data automatically retrieved from geodatabases and partly on information known to the user, of which the knowledge of the date of the stem elongation stage (15 cm growing height) and the harvest date are the most relevant ones. e application is equipped with a back-end system that generates daily the required meteorological variables from the incoming data of the local weather stations network. A participatory approach, involving relevant local stakeholders and experts, was used along the development of the application to ensure an easy and broad use of the application in practice.