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Prediction of forage crop yield and quality based on both optical remote sensing data and dynamic growth model: help to the farmer for forage stocks management

Research project T4/DD/67 (Research action T4)

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Description :

Good farm management is only possible as far as raw material disponibility and quality are knows. 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 relationships between crop growth (yield), crop quality and environmental factors (solar irradiance, temperature, nutrient availability) has been set up (Oger 1994, ustavsson 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) or the biomass estimated with the NDVI (Normalised Difference Vegetation Index), that could be provided by remote sensing (Clevers 1997).

The aim of the present project is to use this approach in order to predict forage yield and quality at the farm scale. Once calibrated this tool will be developed in order to be directly available to the farmer.

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