A sensor based approach to understand spatial variability in orchards

Abstract

Input requirements in an orchard vary in space and time due to the variability of climate, soil and plant growth. Measurements were carried out in Prunus domestica (plum) orchard in the Werder fruit production area in Brandenburg, Germany. Soil zones in the orchard were identified by means of electrical conductivity. Plant data were captured on the tree and organ level: laser-scanner hits show highest values for trees with enhanced canopy size and, consequently, a high leaf area ratio (LAR). Aiming at fruit characterization, indices of the chlorophyll content (normalized difference vegetation index, NDVI) and the visual appearance were considered. The sensor data provide a better insight in the spatially-resolved capacity of tree growth based on the LAR ratio as well as fruit NDVI and quality. Advanced sensors and automated data mining will be further developed and evaluated in the framework of the project 3D-Mosaic (ICTAGRI ERA-Net, European program FP7).