technologies for monitoring crop development are of particular interest in the agricultural sector. Within this context, the detection and identification of plant diseases or the detection and management of weeds
is a fundamental task in sustainable crop production. An accurate estimation of disease incidence, disease severity and negative effects on yield quality and quantity is important for precision crop production
or plant breeding. Assessment of weed plants and automatic differentiation from the sugar beet plants will support a selective spraying or mechanical weeding. Several technological innovations have been
developed and evaluated from interdisciplinary research groups. In particular, optical sensors from remote sensing, such as spectral or thermal imaging offer the potential to observe sugar beet fields and to identify
plant diseases, weeds or abiotic stress. Combining these technologies with up to date approaches from robotics and data analysis routines is most promising. Precision agriculture approaches for a site-specific
handling of fields will benefit from this. Besides, also plant breeding processes will be supported by a so-called digital phenotyping. Thus, it is envisaged to support monitoring and rating of variety trials by
non-invasive and objective imaging techniques. Even though precision or smart farming technologies and digital phenotyping are still in their infancies, the sugar beet sector will significantly benefit from both as
they mature.