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- ItemStudy of Water Productivity of Industrial Hemp under Hot and Dry Conditions in Brandenburg (Germany) in the Year 2018(Basel : MDPI, 2020) Drastig, Katrin; Flemming, Inken; Gusovius, Hans-Jörg; Herppich, Werner B.Hemp (Cannabis sativa L.) is a high-yielding multi-purpose crop, but its hydrological functioning is poorly understood. Studies on the interception processes in hemp have been lacking so far. This study contributes to the understanding of the influences of evaporation of intercepted water and other hydrological fluxes within plants of two cultivars, “Santhica 27” and “Ivory”, on the water productivity. To determine water productivity and evaporation from interception, field measurements were conducted on plants of both cultivars at different stages of development. Precipitation (P), throughfall (TF), transpiration (T), and volumetric water content (VWC) were measured along with leaf area index (LAI) and yield of selected plant components. For the entire vegetation period, the cumulative P of 44 mm was converted into 13 mm TF (30%). The inferred evaporation of intercepted water (I) was high at 31 mm (71%). For the assessment water fluxes, the evaporation of intercepted water must be considered in the decision-making process. Besides the LAI, the plant architecture and the meteorological conditions during the cropping cycle seem to be the main factors determining I in the case of plants of both cultivars. Water productivity (WPDM) of the whole plant varied between 3.07 kg m−3 for Ivory and 3.49 for Santhica 27. In the case of bast yield, WPDM was 0.39 kg m-3 for Santhica 27 and 0.45 kg m−3 for Ivory. After the propagation of the uncertainties, the bandwidth of the WPDM of the whole plant was between 0.42 kg m−3 and 2.57 kg m−3. For bast fiber a bandwidth of the WP between 0.06 kg m−3 and 0.33 kg m−3 was calculated. The results show furthermore that even with a precise examination of water productivity, a high bandwidth of local values is revealed on different cultivars. However, generic WP values for fiber crops are not attainable.
- ItemMonitoring Agronomic Parameters of Winter Wheat Crops with Low-Cost UAV Imagery(Basel : MDPI, 2016) Schirrmann, Michael; Giebel, Antje; Gleiniger, Franziska; Pflanz, Michael; Lentschke, Jan; Dammer, Karl-HeinzMonitoring the dynamics in wheat crops requires near-term observations with high spatial resolution due to the complex factors influencing wheat growth variability. We studied the prospects for monitoring the biophysical parameters and nitrogen status in wheat crops with low-cost imagery acquired from unmanned aerial vehicles (UAV) over an 11 ha field. Flight missions were conducted at approximately 50 m in altitude with a commercial copter and camera system—three missions were performed between booting and maturing of the wheat plants and one mission after tillage. Ultra-high resolution orthoimages of 1.2 cm·px−1 and surface models were generated for each mission from the standard red, green and blue (RGB) aerial images. The image variables were extracted from image tone and surface models, e.g., RGB ratios, crop coverage and plant height. During each mission, 20 plots within the wheat canopy with 1 × 1 m2 sample support were selected in the field, and the leaf area index, plant height, fresh and dry biomass and nitrogen concentrations were measured. From the generated UAV imagery, we were able to follow the changes in early senescence at the individual plant level in the wheat crops. Changes in the pattern of the wheat canopy varied drastically from one mission to the next, which supported the need for instantaneous observations, as delivered by UAV imagery. The correlations between the biophysical parameters and image variables were highly significant during each mission, and the regression models calculated with the principal components of the image variables yielded R2 values between 0.70 and 0.97. In contrast, the models of the nitrogen concentrations yielded low R2 values with the best model obtained at flowering (R2 = 0.65). The nitrogen nutrition index was calculated with an accuracy of 0.10 to 0.11 NNI for each mission. For all models, information about the surface models and image tone was important. We conclude that low-cost RGB UAV imagery will strongly aid farmers in observing biophysical characteristics, but it is limited for observing the nitrogen status within wheat crops.