8 results
Search Results
Now showing 1 - 8 of 8
- 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 systemāthree missions were performed between booting and maturing of the wheat plants and one mission after tillage. Ultra-high resolution orthoimages of 1.2 cmĀ·pxā1 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 Ć 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.
- ItemPrecise Navigation of Small Agricultural Robots in Sensitive Areas with a Smart Plant Camera(Basel : MDPI, 2015) Dworak, Volker; Huebner, Michael; Selbeck, JoernMost of the relevant technology related to precision agriculture is currently controlled by Global Positioning Systems (GPS) and uploaded map data; however, in sensitive areas with young or expensive plants, small robots are becoming more widely used in exclusive work. These robots must follow the plant lines with centimeter precision to protect plant growth. For cases in which GPS fails, a camera-based solution is often used for navigation because of the system cost and simplicity. The low-cost plant camera presented here generates images in which plants are contrasted against the soil, thus enabling the use of simple cross-correlation functions to establish high-resolution navigation control in the centimeter range. Based on the foresight provided by images from in front of the vehicle, robust vehicle control can be established without any dead time; as a result, off-loading the main robot control and overshooting can be avoided.
- ItemComparison of Calibration Approaches in Laser-Induced Breakdown Spectroscopy for Proximal Soil Sensing in Precision Agriculture(Basel : MDPI, 2019) Riebe, Daniel; Erler, Alexander; Brinkmann, Pia; Beitz, Toralf; Lƶhmannsrƶben, Hans-Gerd; Gebbers, RobinThe lack of soil data, which are relevant, reliable, affordable, immediately available, and sufficiently detailed, is still a significant challenge in precision agriculture. A promising technology for the spatial assessment of the distribution of chemical elements within fields, without sample preparation is laser-induced breakdown spectroscopy (LIBS). Its advantages are contrasted by a strong matrix dependence of the LIBS signal which necessitates careful data evaluation. In this work, different calibration approaches for soil LIBS data are presented. The data were obtained from 139 soil samples collected on two neighboring agricultural fields in a quaternary landscape of northeast Germany with very variable soils. Reference analysis was carried out by inductively coupled plasma optical emission spectroscopy after wet digestion. The major nutrients Ca and Mg and the minor nutrient Fe were investigated. Three calibration strategies were compared. The first method was based on univariate calibration by standard addition using just one soil sample and applying the derived calibration model to the LIBS data of both fields. The second univariate model derived the calibration from the reference analytics of all samples from one field. The prediction is validated by LIBS data of the second field. The third method is a multivariate calibration approach based on partial least squares regression (PLSR). The LIBS spectra of the first field are used for training. Validation was carried out by 20-fold cross-validation using the LIBS data of the first field and independently on the second field data. The second univariate method yielded better calibration and prediction results compared to the first method, since matrix effects were better accounted for. PLSR did not strongly improve the prediction in comparison to the second univariate method.
- ItemThe Use of a Pressure-Indicating Film to Determine the Effect of Liner Type on the Measured Teat Load Caused by a Collapsing Liner(Basel : MDPI, 2017-4-13) Demba, Susanne; Paul, Viktoria; Ammon, Christian; Rose-Meierhƶfer, SandraDuring milking the teat cup liner is the interface between the teat of a dairy cow and the milking system, so it should be very well adapted to the teat. Therefore, the aim of the present study was to determine the effect of liner type on the directly measuring teat load caused by a collapsing liner with a pressure-indicating film. The Extreme Low pressure-indicating film was used to detect the effect of six different liners on teat load. For each liner, six positions in the teat cup were specified, and six repetitions were performed for each position with a new piece of film each time. Analysis of variance was performed to detect differences between the six liners, the positions within a liner, and the measuring areas. The pressure applied to the teat by a liner depends on the technical characteristics of the liner, especially the shape of the barrel, and for all tested liners, a higher teat load was found at the teat end. In conclusion, with the help of pressure-indicating film, it is possible to determine the different effects of liner type by directly measuring teat load due to liner collapse. Ā© 2017 by the authors. Licensee MDPI, Basel, Switzerland.
- ItemGoverning Transactions and Interdependences between Linked Value Chains in a Circular Economy: The Case of Wastewater Reuse in Braunschweig (Germany)(Basel : MDPI, 2018-4-9) MaaĆ, Oliver; Grundmann, PhilippReusing wastewater in agriculture has attracted increasing attention as a strategy to support the transition towards the circular economy in the water and agriculture sector. As a consequence, there is great interest in solutions for governing the transactions and interdependences between the associated value chains. This paper explores the institutions and governance structures for coordinating transactions and interdependences between actors in linked value chains of wastewater treatment and crop production. It aims to analyze how transactions and interdependences shape the governance structures for reusing wastewater at the local level. A transaction costs analysis based on data from semi-structured interviews and a questionnaire is applied to the agricultural wastewater reuse scheme of the Wastewater Association Braunschweig (Germany). The results show that different governance structures are needed to match with the different properties and requirements of the transactions and activities between linked value chains of wastewater treatment and crop production. Interdependences resulting from transactions between wastewater providers and farmers increase the need for hybrid and hierarchical elements in the governance structures for wastewater reuse. The authors conclude that aligning governance structures with transactions and interdependences is key to efficiently governing transactions and interdependences between linked value chains in a circular economy. Ā© 2018 by the authors.
- ItemWeed Mapping with UAS Imagery and a Bag of Visual Words Based Image Classifier(Basel : MDPI, 2018-9-24) Pflanz, Michael; Nordmeyer, Henning; Schirrmann, MichaelWeed detection with aerial images is a great challenge to generate field maps for site-specific plant protection application. The requirements might be met with low altitude flights of unmanned aerial vehicles (UAV), to provide adequate ground resolutions for differentiating even single weeds accurately. The following study proposed and tested an image classifier based on a Bag of Visual Words (BoVW) framework for mapping weed species, using a small unmanned aircraft system (UAS) with a commercial camera on board, at low flying altitudes. The image classifier was trained with support vector machines after building a visual dictionary of local features from many collected UAS images. A window-based processing of the models was used for mapping the weed occurrences in the UAS imagery. The UAS flight campaign was carried out over a weed infested wheat field, and images were acquired between a 1 and 6 m flight altitude. From the UAS images, 25,452 weed plants were annotated on species level, along with wheat and soil as background classes for training and validation of the models. The results showed that the BoVW model allowed the discrimination of single plants with high accuracy for Matricaria recutita L. (88.60%), Papaver rhoeas L. (89.08%), Viola arvensis M. (87.93%), and winter wheat (94.09%), within the generated maps. Regarding site specific weed control, the classified UAS images would enable the selection of the right herbicide based on the distribution of the predicted weed species. Ā© 2018 by the authors.
- ItemQuantity- and Quality-Based Farm Water Productivity in Wine Production: Case Studies in Germany(Basel : MDPI, 2017-2-1) Peth, Denise; Drastig, Katrin; Prochnow, AnnetteThe German wine sector has encountered new challenges in water management recently. To manage water resources responsibly, it is necessary to understand the relationship between the input of water and the output of wine, in terms of quantity and quality. The objectives of this study are to examine water use at the farm scale at three German wineries in Rhenish Hesse, and to develop and apply, for the first time, a quality-based indicator. Water use is analyzed in terms of wine production and wine-making over three years. After the spatial and temporal boundaries of the wineries and the water flows are defined, the farm water productivity indicator is calculated to assess water use at the winery scale. Farm water productivity is calculated using the AgroHyd Farmmodel modeling software. Average productivity on a quantity basis is 3.91 L wine per m3 of water. Productivity on a quality basis is 329.24 Oechsle per m3 of water. Water input from transpiration for wine production accounts for 99.4%-99.7% of total water input in the wineries, and, because irrigation is not used, precipitation is the sole source of transpired water. Future studies should use both quality-based and mass-based indicators of productivity. Ā© 2017 by the authors.
- ItemNew Tropical Peatland Gas and Particulate Emissions Factors Indicate 2015 Indonesian Fires Released Far More Particulate Matter (but Less Methane) than Current Inventories Imply(Basel : MDPI, 2018-3-21) Wooster, Martin J.; Gaveau, David L.A.; Salim, Mohammad A.; Zhang, Tianran; Xu, Weidong; Green, David C.; Huijnen, Vincent; Murdiyarso, Daniel; Gunawan, Dodo; Borchard, Nils; Schirrmann, Michael; Main, Bruce; Sepriando, AlponDeforestation and draining of the peatlands in equatorial SE Asia has greatly increased their flammability, and in September-October 2015 a strong El NiƱo-related drought led to further drying and to widespread burning across parts of Indonesia, primarily on Kalimantan and Sumatra. These fires resulted in some of the worst sustained outdoor air pollution ever recorded, with atmospheric particulate matter (PM) concentrations exceeding those considered "extremely hazardous to health" by up to an order of magnitude. Here we report unique in situ air quality data and tropical peatland fire emissions factors (EFs) for key carbonaceous trace gases (CO2, CH4 and CO) and PM2.5 and black carbon (BC) particulates, based on measurements conducted on Kalimantan at the height of the 2015 fires, both at locations of "pure" sub-surface peat burning and spreading vegetation fires atop burning peat. PM2.5 are the most significant smoke constituent in terms of human health impacts, and we find in situ PM2.5 emissions factors for pure peat burning to be 17.8 to 22.3 gĀ·kg-1, and for spreading vegetation fires atop burning peat 44 to 61 gĀ·kg-1, both far higher than past laboratory burning of tropical peat has suggested. The latter are some of the highest PM2.5 emissions factors measured worldwide. Using our peatland CO2, CH4 and CO emissions factors (1779 Ā± 55 gĀ·kg-1, 238 Ā± 36 gĀ·kg-1, and 7.8 Ā± 2.3 gĀ·kg-1 respectively) alongside in situ measured peat carbon content (610 Ā± 47 g-CĀ·kg-1) we provide a new 358 Tg (Ā± 30%) fuel consumption estimate for the 2015 Indonesian fires, which is less than that provided by the GFEDv4.1s and GFASv1.2 global fire emissions inventories by 23% and 34% respectively, and which due to our lower EFCH4 produces far less (~3Ć) methane. However, our mean in situ derived EFPM2.5 for these extreme tropical peatland fires (28 Ā± 6 gĀ·kg-1) is far higher than current emissions inventories assume, resulting in our total PM2.5 emissions estimate (9.1 Ā± 3.5 Tg) being many times higher than GFEDv4.1s, GFASv1.2 and FINNv2, despite our lower fuel consumption. We find that two thirds of the emitted PM2.5 come from Kalimantan, one third from Sumatra, and 95% from burning peatlands. Using new geostationary fire radiative power (FRP) data we map the fire emissions' spatio-temporal variations in far greater detail than ever before (hourly, 0.05Ā°), identifying a tropical peatland fire diurnal cycle twice as wide as in neighboring non-peat areas and peaking much later in the day. Our data show that a combination of greatly elevated PM2.5 emissions factors, large areas of simultaneous, long-duration burning, and very high peat fuel consumption per unit area made these Sept to Oct tropical peatland fires the greatest wildfire source of particulate matter globally in 2015, furthering evidence for a regional atmospheric pollution impact whose particulate matter component in particular led to millions of citizens being exposed to extremely poor levels of air quality for substantial periods. Ā© 2018 by the authors.