The efficient use of nitrogen fertilizer is a crucial problem in modern agriculture. Fertilization has to be minimized to reduce environmental impacts but done so optimally without negatively affecting yield. In June 2017, a controlled experiment with eight different nitrogen treatments was applied to winter wheat plants and investigated with the UAV-based hyperspectral pushbroom camera Resonon Pika-L (400-1000 nm). The system, in combination with an accurate inertial measurement unit (IMU) and precise gimbal, was very stable and capable of acquiring hyperspectral imagery of high spectral and spatial quality. Additionally, in situ measurements of 48 samples (leaf area index (LAI), chlorophyll (CHL), and reflectance spectra) were taken in the field, which were equally distributed across the different nitrogen treatments. These measurements were used to predict grain yield, since the parameter itself had no direct effect on the spectral reflection of plants. Therefore, we present an indirect approach based on LAI and chlorophyll estimations from the acquired hyperspectral image data using partial least-squares regression (PLSR). The resulting models showed a reliable predictability for these parameters (R 2 LAI = 0.79, RMSE LAI [m 2 m −2 ] = 0.18, R 2 CHL = 0.77, RMSE CHL [µg cm −2 ] = 7.02). The LAI and CHL predictions were used afterwards to calibrate a multiple linear regression model to estimate grain yield (R 2 yield = 0.88, RMSE yield [dt ha −1 ] = 4.18). With this model, a pixel-wise prediction of the hyperspectral image was performed. The resulting yield estimates were validated and opposed to the different nitrogen treatments, which revealed that, above a certain amount of applied nitrogen, further fertilization does not necessarily lead to larger yield.From the farmer's perspective, the most important economic parameter is achieved yields. An overdose of N fertilizer, within the legal limits, results higher costs without adding value in terms of additional yield. Further possible regulations for the application of fertilizers should only have a limited negative impact on yields. With controlled experiments, directly comparing the harvested yield resulting from different N applications, one can identify the effects of reduced fertilization. Moreover, new concepts of monitoring these effects during vegetative growth enables the development of precision farming applications, especially created for efficient N fertilization [3].Remote sensing technology at various scales has often proved to be a suitable tool for agricultural crop monitoring [4]. In particular, UAV-supported remote sensing enables very precise monitoring of individual areas through lower flight altitudes and high-resolution data [5]. In recent years, the development of UAV-based hyperspectral recording systems has made rapid progress [6]. In comparison to manned aircraft based systems, the sensors are smaller, lighter, and less costly during acquisition and processing [7]. The great potential of this technology has been demonstrated [8].Hyper...

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Groundwater pollution with nitrate is a big challenge for drinking water abstraction in regions with intensive agricultural land-use, specifically with high livestock densities on sandy soils in humid climates. Karst aquifers with high water flow velocities are extremely vulnerable to this problem. To cope with this situation, a field trial with an installation of ceramic suction cups under a randomised block design with a typical north-German cropping sequence of silage maize–winter wheat–winter barley was established in a karst water protection zone. Over three years, reduced nitrogen (N) application rates and N type (mineral or combined organic + mineral fertilisation) were tested for their effects on crop yields and leachate water quality below the root zone. Results showed no significant reductions in crop yields with 10/20% reduced N rates for cereals/maize and only slight reductions in cereal protein content. Nitrate concentration from adapted N rates was significantly lower in treatments with an application of organic fertilisers (−7.74 mg NO3-N l−1) with greatest potential after cultivation of maize; in only mineral fertilised plots the effect was smaller (−3.80 mg NO3-N l−1). Cumulative leaching losses were positively correlated with post-harvest soil mineral nitrogen content but even in unfertilised control plots losses >50 kg N ha−1 were observed in some crop-years. Reduced N rates led to decreased leaching losses of 14% (6.3 kg N ha−1 a−1) with mineral and 29% (20.1 kg N ha−1 a−1) with organic + mineral fertilisation on average overall cops and years. The presented study revealed the general potential of adapted fertilisation strategies with moderately reduced N applications (−10/−20%) to increase leachate water quality without affecting significantly crop yields. However, regionally typical after-effects from yearlong high N surpluses in livestock intensive farming systems are a limiting factor.

Despite intensive efforts motivated by the European Water Framework Directive, many water bodies still suffer from poor water quality in Germany. Intensively drained agricultural areas are still a critical source for nitrate which is responsible for negative effects on aquatic ecosystems. Basic measures such as the fertiliser ordinance are expected to be not sufficient to completely eliminate nitrate exports via drainage tiles and ditches. Consequently, there is the demand to manage the reduction of nitrate concentrations with new additional end of pipe solutions. For this, the presented study focuses on a simply to implement reactive ditch for denitrification, which is installed into drainage ditches to reduce nitrate concentrations. An existing drainage ditch that is fed by tile drainage water was filled with wood chips to keep installation efforts as simple and cheap as possible. In situ parameters and nutrient concentrations were determined at the inflow and the outflow of the reactive ditch for 2 years.The results reveal a promising potential for wood chipbased filters to reduce nitrate concentrations by 28 % on average over all seasons. Within the filter, favourable conditions for denitrification were predominantly found without flooding of surrounding areas. Investigations revealed decreasing nitrate concentrations especially in cases of low flow rates and high temperatures. These encouraging results demonstrate the successful application of reactive ditches under German lowland conditions in general. Since tile drainages are installed for many agricultural areas in this region, there seems to be high potential for the application of this easily implementable type of bioreactor.

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Today, the demand for soybean for feed industry and food production in Germany is met by imports from South and North America. Soybean cultivation in Germany, although challenging, will be of interest in the future due to an increasing demand for non-genetically modified (NGM) soybeans. To meet this rising demand for NGM soybeans and to increase resource use efficiency there is a need to reduce soybean harvest losses arising from harvesting with combine harvester. The height of the first pod can be a major factor affecting harvest losses, especially when it is not possible to maintain a sufficiently low cutting height. From 2011 to 2013, six soybean varieties were cultivated using two cropping systems (conventional 'CON' and organic 'ORG') at the Osnabrück University of Applied Sciences in a randomized block design with four replications to investigate the effect of first pod height and plant length on harvest losses and the effect of the cropping system on these parameters. Before harvesting with an experimental harvester, 1.5 m 2 per plot were harvested manually as a reference. First pod height, number of pods per plant and plant length were determined on 10 plants per plot. Over the three years of the study, the first pod height (10.4 cm) and plant length (81.4 cm) were on average higher under conventional conditions compared to organic cultivation (7.3 cm; 60.9 cm). On average, lower harvest losses (25.6% vs. 39.2%) and higher grain yields (20.8 dt ha −1 vs. 16.9 dt ha −1) were also observed under conventional cultivation. Varieties differed significantly in grain yield, first pod height and plant length. A high first pod height was related to a longer plant length and lower harvest losses at both sites. However, a high first pod height and a high plant length did not lead to higher grain yields on any of the plots. These results indicate that harvest efficiency can be improved by choosing varieties with long plant lengths if it is not possible to maintain a low cutting height when harvesting with a combine harvester.

Pumpkins are economically and nutritionally valuable vegetables with increasing popularity and acreage across Europe. Successful commercialization, however, require detailed pre-harvest information about number and weight of the fruits. To get a non-destructive and cost-effective yield estimation, we developed an image processing methodology for high-resolution RGB data from Unmanned aerial vehicle (UAV) and applied this on a Hokkaido pumpkin farmer’s field in North-western Germany. The methodology was implemented in the programming language Python and comprised several steps, including image pre-processing, pixel-based image classification, classification post-processing for single fruit detection, and fruit size and weight quantification. To derive the weight from two-dimensional imagery, we calculated elliptical spheroids from lengths of diameters and heights. The performance of this processes was evaluated by comparison with manually harvested ground-truth samples and cross-checked for misclassification from randomly selected test objects. Errors in classification and fruit geometry could be successfully reduced based on the described processing steps. Additionally, different lighting conditions, as well as shadows, in the image data could be compensated by the proposed methodology. The results revealed a satisfactory detection of 95% (error rate of 5%) from the field sample, as well as a reliable volume and weight estimation with Pearson’s correlation coefficients of 0.83 and 0.84, respectively, from the described ellipsoid approach. The yield was estimated with 1.51 kg m−2 corresponding to an average individual fruit weight of 1100 g and an average number of 1.37 pumpkins per m2. Moreover, spatial distribution of aggregated fruit densities and weights were calculated to assess in-field optimization potential for agronomic management as demonstrated between a shaded edge compared to the rest of the field. The proposed approach provides the Hokkaido producer useful information for more targeted pre-harvest marketing strategies, since most food retailers request homogeneous lots within prescribed size or weight classes.