Comment la phase de décroissance de la surface verte de la plante nous renseigne sur le rendement final
Summary
The prediction of cereal-crop yield is considered as a priority in most crop research programmes due to the relevance of food grain to feeding the world population. Today, a large number of agrometeorological models for crop yield assessment are available with various levels of complexity and empiricism. But, currently the development of wheat yield forecasting models in conventional operational systems do not reflect the loss of active green leaf area and its relation to biotic and abiotic processes implicated in the crop production situation.
In 2009 a large field campaign in the Grand-Duchy of Luxembourg was realized to assess the validity of leaf-green-area approach to further improve the yield prediction. Hemispherical photography were taken above the canopy (between 0,60 and 1 meter) in winter wheat fields during the crop cycle, preferentially from inflorescence emergence to maturity. The variable of interest, the Green Area Index (GAI), was retrieved after image analyses using the CAN-EYE software. The regression-based models calculated with metrics derived from the decreasing curves of GAI showed that the final yield could be estimated with satisfactory precision: range of the coefficient of determination (R²) varies from 0.73 to 0,86 and RMSE (root mean square error) is varying between 0,43 and 0,56 t.ha-1.
The validation of such approach at the scale of an agricultural zone or region is currently under progress, by using green area index temporal profiles and information on the phenology of winter wheat. Such simple models may be considered as a first step towards yield estimation that may be completed by other agrometeorological models in order to provide a better integrated and more accurate yield assessment.
Key words: Wheat, Yield estimates, Green Area Index, Senescence, Hemispherical images.
