Crop yield varies spatially and maps produced by the yield monitor systems are evidence of the degree of within-field variability. Interpretation of the information contained in a yield map according to technical and economic aspects is not always clear to farmers. Determining the optimum prescription for a location within a field is challenging. Process oriented crop simulation models, such as the SALUS, integrate the effects of temporal and multiple stress interactions on crop growth processes under varying environmental and management conditions. It is rather obvious that crop simulations cannot be performed everywhere in a field given that the cost and the availability of detailed inputs would be prohibitive. A more balanced approach to the application of crop simulation models to precision agriculture would be to delineate zones within the field of similar crop performance. This project will use microdrone (UAVs) for deployment of high-resolution proximal sensing systems for delineate zones within the field of similar crop performance. The UAV will provide images of spectral reflectance which will be transformed in vegetation indices (VI). VI will be interpreted for converting information in canopy cover, leaf area index (LAI), and plant nutritional status, and could further allow the discrimination of different crop stress factors such as nitrogen, water stresses, weeds, or pest. The SALUS model (System Approach to Land Use Sustainability) will be used to reproduce the measured yield variability for the selected field sites to evaluate alternative management strategies.
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