diagnosis in field - big data driven reason clarification of satellite captured differences in field location The main objective of the project 'BigPicture - Diagnosis in the field: Big-Data-based determination of causes for satellite-image-derived and site-specific variations.” which is to be conducted from August 2016 until January 2019, is to use the characteristics or symptoms of plants detected by satellite sensors to derive distinct diagnoses to their causes. The goal is to make appropriate crop treatment decisions based on this information.

Generation of agricultural maps for yield potential by fusion of yield mapping, remote sensing, digital relief maps and cultivation data One of the most important parameter for agricultural crop production is the expected yield potential of a specific crop species at each location. Based on the yield potential an optimization of the cultivation method and the specific production intensity can be performed.

Development of a electronic SmartHarvest-System for damage-free sugarbeet harvest# In 2017, the current sugar market regime will cut-off, and the acreage of the German sugar beet crop will substantially increase, thereby enabling a longer processing campaign and cost reduction per unit of sugar. As a consequence, the amount of beets stored in field piles for up to 3 month will increase. Under such conditions, long-term storage assuring low sugar losses is paramount. Storage losses and invert sugar formation are known to increase if the beets were damaged at harvest.