Research project T4/DD/29 (Research action T4)
Good farm management is only possible as far as raw material availability and quality are known. In animal husbandry, these raw materials are mainly forage produced in the exploitation. Therefore, the estimate of forage stocks and quality is of prime importance in such farming system.
To do so, dynamic models, describing the relationship between crop growth (yield), crop quality and environmental factors (solar irradiance, temperature, nutrient availability) has been set up (Ogre 1994; Gustavsson et al. 1995). However these models often appear to fail when growing conditions are not optimal (Clevers 1997). One solution is to calibrate the modelling with some information on the actual status of the crop during the season. Information such as the leaf area index (LAI), that could be provided by remote sensing (Clevers 1997), an other solution is to define an empirical relation between a variable measurement during the growing season at a fixed phenological period, through remote sensing, and the yield of the crop at the end of the season. Clevers (1997) proposes the use of the fraction of the photosynthetically active radiation that is absorbed as such a parameter (fAPAR).
The aim of the present project is to use this double approach in order to predict forage yield and quality at the field scale. Once calibrated this tool will be developed in order to be directly available for the farmer.
