Biotechnologie, Agronomie, Société et Environnement (Jan 2013)
Gestion de la fertilisation azotée des cultures de plein champ. Perspectives d'amélioration de l'efficience d'utilisation de l'azote sur base du suivi du statut azoté de la biomasse aérienne
Abstract
Nitrogen fertilization management of open-field crops. Opportunities for improvement of nitrogen use efficiency based on crop nitrogen status monitoring. The improvement of nitrogen use efficiency in crops is currently an important issue in farming due to current and future economical and environmental constraints. Splitting of N fertilizer application is the most suitable approach for providing an optimal match of N need and supply. The implementation of monitoring methods to assess crop N status is required to define the relevant amounts and periods required for split applications. This paper discusses the available methods of split N fertilizer application and their mode of use and implementation. After a short overview of the concept of crop N status, the main existing methods to estimate nitrogen needs are examined for their accuracy, specificity and sensitivity based on research conducted at CRA-W (Production and Sectors Department, Crop Production Systems Unit) over the last two decades, focusing specifically on the potato crop. The methods and the results described relate to the petiole sap nitrate concentration test assessed via a reflectometer, the measurement of leaf chlorophyll concentration with a handheld chlorophyll meter, leaf chlorophyll fluorescence readings with handheld fluorimeters, and the measurement of crop light reflectance with a handheld radiometer (ground-based remote sensing) or with satellite imagery (spatial remote sensing). Conditions for implementing such methods within decision support systems are briefly described, by focusing on the need to use relative values rather than raw values taken from the readings, and also on the requirement for threshold value definition. The integration of crop nitrogen status values into N fertilization recommendation models is illustrated through a Decision Support System created at CRA-W for the potato crop.
