Easy-to-capture and robust plant status indicators are important factors when implementing precision agriculture techniques on fields. In this study, aerial red, green and blue color space (RGB) photography and near-infrared (NIR) photography was performed on an experimental field site with nine different cover crops. A lightweight unmanned aerial system (UAS) served as platform, consumer cameras as sensors. Photos were photogrammetrically processed to orthophotos and digital surface models (DSMs). In a first validation step, the spatial precision of RGB orthophotos (x and y, ± 0.1 m) and DSMs (z, ± 0.1 m) was determined. Then, canopy cover (CC), plant height (PH), normalized differenced vegetation index (NDVI), red edge inflection point (REIP), and green red vegetation index (GRVI) were extracted. In a second validation step, the PHs derived from the DSMs were compared with ground truth ruler measurements. A strong linear relationship was observed (R 2 = 0.80-0.84). Finally, destructive biomass samples were taken and compared with the remotely-sensed characteristics. Biomass correlated best with plant height (PH), and good approximations with linear regressions were found (R 2 = 0.74 for four selected species, R 2 = 0.58 for all nine species). CC and the vegetation indices (VIs) showed less significant and less strong overall correlations, but performed well for certain species. It is therefore evident that the use of DSM-based PHs provides a feasible approach to a species-independent non-destructive biomass determination, where the performance of VIs is more species-dependent.

A major concern related to the adoption of genetically modified (GM) crops in agricultural systems is the possibility of unwanted GM inputs into non-GM crop production systems. Given the increasing commercial cultivation of GM crops in the European Union (EU), there is an urgent need to define measures to prevent mixing of GM with non-GM products during crop production. Cross-fertilization is one of the various mechanisms that could lead to GM-inputs into non-GM crop systems. Isolation distances between GM and non-GM fields are widely accepted to be an effective measure to reduce these inputs. However, the question of adequate isolation distances between GM and non-GM maize is still subject of controversy both amongst scientists and regulators. As several European countries have proposed largely differing isolation distances for maize ranging from 25 to 800 m, there is a need for scientific criteria when using cross-fertilization data of maize to define isolation distances between GM and non-GM maize. We have reviewed existing cross-fertilization studies in maize, established relevant criteria for the evaluation of these studies and applied these criteria to define science-based isolation distances. To keep GM-inputs in the final product well below the 0.9% threshold defined by the EU, isolation distances of 20 m for silage and 50 m for grain maize, respectively, are proposed. An evaluation using statistical data on maize acreage and an aerial photographs assessment of a typical agricultural landscape by means of Geographic Information Systems (GIS) showed that spatial resources would allow applying the defined isolation distances for the cultivation of GM maize in the majority of the cases under actual Swiss agricultural conditions. The here developed approach, using defined criteria to consider the agricultural context of maize cultivation, may be of assistance for the analysis of cross-fertilization data in other countries.

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