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    Rapid determination of lime requirement by mid-infrared spectroscopy: A promising approach for precision agriculture
    (Weinheim : Wiley-VCH, 2019) Leenen, Matthias; Welp, Gerhard; Gebbers, Robin; Pätzold, Stefan
    Mid-infrared spectroscopy (MIRS) has proven to be a cost-effective, high throughput measurement technique for soil analysis. After multivariate calibration mid-infrared spectra can be used to predict various soil properties, some of which are related to lime requirement (LR). The objective of this study was to test the performance of MIRS for recommending variable rate liming on typical Central European soils in view of precision agriculture applications. In Germany, LR of arable topsoils is commonly derived from the parameters organic matter content (SOM), clay content, and soil pH (CaCl2) as recommended by the Association of German Agricultural Analytical and Research Institutes (VDLUFA). We analysed a total of 458 samples from six locations across Germany, which all revealed large within-field soil heterogeneity. Calcareous topsoils were observed at some positions of three locations (79 samples). To exclude such samples from LR determination, peak height at 2513 cm−1 of the MIR spectrum was used for identification. Spectra-based identification was accurate for carbonate contents > 0.5%. Subsequent LR derivation (LRSPP) from MIRS-PLSR predictions of SOM, clay, and pH (CaCl2) for non-calcareous soil samples using the VDLUFA look-up tables was successful for all locations (R2 = 0.54–0.82; RMSE = 857–1414 kg CaO ha−1). Alternatively, we tested direct LR prediction (LRDP) by MIRS-PLSR and also achieved satisfactory performance (R2 = 0.52–0.77; RMSE = 811–1420 kg CaO ha−1; RPD = 1.44–2.08). Further improvement was achieved by refining the VDLUFA tables towards a stepless algorithm. It can be concluded that MIRS provides a promising approach for precise LR estimation on heterogeneous arable fields. Large sample numbers can be processed with low effort which is an essential prerequisite for variable rate liming in precision agriculture. © 2019 The Authors. Journal of Plant Nutrition and Soil Science published by WILEY-VCH Verlag GmbH & Co. KGaA
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    Methoden für die präzise obstbauliche Produktion
    (Darmstadt : KTBL, 2012) Zude, Manuela; Peeters, Aviva; Selbeck, Jörn; Käthner, Jana; Gebbers, Robin; Bengal, Alon; Hetzroni, Amots; Jaeger-Hansen, Claes; Griepentrog, Hans-Werner; Pforte, Florian; Rozzi, Paolo; Torricelli, Alessandro; Spinelli, Lorenzo; Ünlü, Mustafa; Kanber, Riza
    Der Ansatz von Precision Horticulture im Obstbau lehnt sich an das aus dem Ackerbau stammende Konzept der Präzisionslandwirtschaft bzw. der teilflächenspezifischen Bewirtschaftung an. Hierbei sollen präzise an das individuelle Gehölzwachstum angepasste Pflegemaßnahmen die bislang praktizierte einheitliche Behandlung aller Bäume in einer Anlage ablösen. Voraussetzungen hierfür sind u. a. Bodenkarten und Informationen zum Pflanzenwachstum. Das Ziel ist es, den informationsgestützten Obstbau voranzutreiben und durch ein räumlich und zeitlich differenziertes Management eine effizientere und nachhaltigere Bewirtschaftung zu erreichen.
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    Proximal Soil Sensing - A Contribution for Species Habitat Distribution Modelling of Earthworms in Agricultural Soils?
    (San Francisco, California, US : PLOS, 2016) Schirrmann, Michael; Joschko, Monika; Gebbers, Robin; Kramer, Eckart; Zörner, Mirjam; Barkusky, Dietmar; Timmer, Jens
    Background: Earthworms are important for maintaining soil ecosystem functioning and serve as indicators of soil fertility. However, detection of earthworms is time-consuming, which hinders the assessment of earthworm abundances with high sampling density over entire fields. Recent developments of mobile terrestrial sensor platforms for proximal soil sensing (PSS) provided new tools for collecting dense spatial information of soils using various sensing principles. Yet, the potential of PSS for assessing earthworm habitats is largely unexplored. This study investigates whether PSS data contribute to the spatial prediction of earthworm abundances in species distribution models of agricultural soils. Methodology/Principal Findings: Proximal soil sensing data, e.g., soil electrical conductivity (EC), pH, and near infrared absorbance (NIR), were collected in real-time in a field with two management strategies (reduced tillage / conventional tillage) and sandy to loam soils. PSS was related to observations from a long-term (11 years) earthworm observation study conducted at 42 plots. Earthworms were sampled from 0.5 x 0.5 x 0.2 m³ soil blocks and identified to species level. Sensor data were highly correlated with earthworm abundances observed in reduced tillage but less correlated with earthworm abundances observed in conventional tillage. This may indicate that management influences the sensor-earthworm relationship. Generalized additive models and state-space models showed that modelling based on data fusion from EC, pH, and NIR sensors produced better results than modelling without sensor data or data from just a single sensor. Regarding the individual earthworm species, particular sensor combinations were more appropriate than others due to the different habitat requirements of the earthworms. Earthworm species with soil-specific habitat preferences were spatially predicted with higher accuracy by PSS than more ubiquitous species. Conclusions/Significance: Our findings suggest that PSS contributes to the spatial modelling of earthworm abundances at field scale and that it will support species distribution modelling in the attempt to understand the soil-earthworm relationships in agroecosystems.
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    Terahertz spectroscopy for proximal soil sensing: An approach to particle size analysis
    (Basel : MDPI, 2017) Dworak, Volker; Mahns, Benjamin; Selbeck, Jörn; Gebbers, Robin; Weltzien, Cornelia
    Spatially resolved soil parameters are some of the most important pieces of information for precision agriculture. These parameters, especially the particle size distribution (texture), are costly to measure by conventional laboratory methods, and thus, in situ assessment has become the focus of a new discipline called proximal soil sensing. Terahertz (THz) radiation is a promising method for nondestructive in situ measurements. The THz frequency range from 258 gigahertz (GHz) to 350 GHz provides a good compromise between soil penetration and the interaction of the electromagnetic waves with soil compounds. In particular, soil physical parameters influence THz measurements. This paper presents investigations of the spectral transmission signals from samples of different particle size fractions relevant for soil characterization. The sample thickness ranged from 5 to 17 mm. The transmission of THz waves was affected by the main mineral particle fractions, sand, silt and clay. The resulting signal changes systematically according to particle sizes larger than half the wavelength. It can be concluded that THz spectroscopic measurements provide information about soil texture and penetrate samples with thicknesses in the cm range.
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    Application of Terahertz radiation to soil measurements: Initial results
    (Basel : MDPI, 2011) Dworak, Volker; Augustin, Sven; Gebbers, Robin
    Developing soil sensors with the possibility of continuous online measurement is a major challenge in soil science. Terahertz (THz) electromagnetic radiation may provide the opportunity for the measurement of organic material density, water content and other soil parameters at different soil depths. Penetration depth and information content is important for a functional soil sensor. Therefore, we present initial research on the analysis of absorption coefficients of four different soil samples by means of THz transmission measurements. An optimized soil sample holder to determine absorption coefficients was used. This setup improves data acquisition because interface reflections can be neglected. Frequencies of 340 GHz to 360 GHz and 1.627 THz to 2.523 THz provided information about an existing frequency dependency. The results demonstrate the potential of this THz approach for both soil analysis and imaging of buried objects. Therefore, the THz approach allows different soil samples to be distinguished according to their different absorption properties so that relations among soil parameters may be established in future.
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    Soil pH mapping with an on-the-go sensor
    (Basel : MDPI, 2011) Schirrmann, Michael; Gebbers, Robin; Kramer, Eckart; Seidel, Jan
    Soil pH is a key parameter for crop productivity, therefore, its spatial variation should be adequately addressed to improve precision management decisions. Recently, the Veris pH ManagerTM, a sensor for high-resolution mapping of soil pH at the field scale, has been made commercially available in the US. While driving over the field, soil pH is measured on-the-go directly within the soil by ion selective antimony electrodes. The aim of this study was to evaluate the Veris pH ManagerTM under farming conditions in Germany. Sensor readings were compared with data obtained by standard protocols of soil pH assessment. Experiments took place under different scenarios: (a) controlled tests in the lab, (b) semicontrolled test on transects in a stop-and-go mode, and (c) tests under practical conditions in the field with the sensor working in its typical on-the-go mode. Accuracy issues, problems, options, and potential benefits of the Veris pH ManagerTM were addressed. The tests demonstrated a high degree of linearity between standard laboratory values and sensor readings. Under practical conditions in the field (scenario c), the measure of fit (r2) for the regression between the on-the-go measurements and the reference data was 0.71, 0.63, and 0.84, respectively. Field-specific calibration was necessary to reduce systematic errors. Accuracy of the on-the-go maps was considerably higher compared with the pH maps obtained by following the standard protocols, and the error in calculating lime requirements was reduced by about one half. However, the system showed some weaknesses due to blockage by residual straw and weed roots. If these problems were solved, the on-the-go sensor investigated here could be an efficient alternative to standard sampling protocols as a basis for liming in Germany.
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    Vertical soil profiling using a galvanic contact resistivity scanning approach
    (Basel : MDPI, 2014) Pan, Luan; Adamchuk, Viacheslav I.; Prasher, Shiv; Gebbers, Robin; Taylor, Richard S.; Dabas, Michel
    Proximal sensing of soil electromagnetic properties is widely used to map spatial land heterogeneity. The mapping instruments use galvanic contact, capacitive coupling or electromagnetic induction. Regardless of the type of instrument, the geometrical configuration between signal transmitting and receiving elements typically defines the shape of the depth response function. To assess vertical soil profiles, many modern instruments use multiple transmitter-receiver pairs. Alternatively, vertical electrical sounding can be used to measure changes in apparent soil electrical conductivity with depth at a specific location. This paper examines the possibility for the assessment of soil profiles using a dynamic surface galvanic contact resistivity scanning approach, with transmitting and receiving electrodes configured in an equatorial dipole-dipole array. An automated scanner system was developed and tested in agricultural fields with different soil profiles. While operating in the field, the distance between current injecting and measuring pairs of rolling electrodes was varied continuously from 40 to 190 cm. The preliminary evaluation included a comparison of scan results from 20 locations to shallow (less than 1.2 m deep) soil profiles and to a two-layer soil profile model defined using an electromagnetic induction instrument.
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    Micro UAV based georeferenced orthophoto generation in VIS + NIR for precision agriculture
    (München : European Geopyhsical Union, 2013) Bachmann, Ferry; Herbst, Ruprecht; Gebbers, Robin; Hafner, Verena V.
    This paper presents technical details about georeferenced orthophoto generation for precision agriculture with a dedicated selfconstructed camera system and a commercial micro UAV as carrier platform. The paper describes the camera system (VIS + NIR) in detail and focusses on three issues concerning the generation and processing of the aerial images related to: (i) camera exposure time; (ii) vignetting correction; (iii) orthophoto generation.
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    Comparison 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; Löhmannsröben, Hans-Gerd; Gebbers, Robin
    The 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.
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    Evaluating Soil-Borne Causes of Biomass Variability in Grassland by Remote and Proximal Sensing
    (Basel : MDPI AG, 2019) Vogel, Sebastian; Gebbers, Robin; Oertel, Marcel; Kramer, Eckart
    On a grassland field with sandy soils in Northeast Germany (Brandenburg), vegetation indices from multi-spectral UAV-based remote sensing were used to predict grassland biomass productivity. These data were combined with soil pH value and apparent electrical conductivity (ECa) from on-the-go proximal sensing serving as indicators for soil-borne causes of grassland biomass variation. The field internal magnitude of spatial variability and hidden correlations between the variables of investigation were analyzed by means of geostatistics and boundary-line analysis to elucidate the influence of soil pH and ECa on the spatial distribution of biomass. Biomass and pH showed high spatial variability, which necessitates high resolution data acquisition of soil and plant properties. Moreover, boundary-line analysis showed grassland biomass maxima at pH values between 5.3 and 7.2 and ECa values between 3.5 and 17.5 mS m−1. After calibrating ECa to soil moisture, the ECa optimum was translated to a range of optimum soil moisture from 7% to 13%. This matches well with to the plant-available water content of the predominantly sandy soil as derived from its water retention curve. These results can be used in site-specific management decisions to improve grassland biomass productivity in low-yield regions of the field due to soil acidity or texture-related water scarcity.