A SOS3 homologue maps to HvNax4, a barley locus controlling an environmentally sensitive Na+ exclusion trait

Genes that enable crops to limit Na+ accumulation in shoot tissues represent potential sources of salinity tolerance for breeding. In barley, the HvNax4 locus lowered shoot Na+ content by between 12% and 59% (g−1 DW), or not at all, depending on the growth conditions in hydroponics and a range of soil types, indicating a strong influence of environment on expression. HvNax4 was fine-mapped on the long arm of barley chromosome 1H. Corresponding intervals of ∼200 kb, containing a total of 34 predicted genes, were defined in the sequenced rice and Brachypodium genomes. HvCBL4, a close barley homologue of the SOS3 salinity tolerance gene of Arabidopsis, co-segregated with HvNax4. No difference in HvCBL4 mRNA expression was detected between the mapping parents. However, genomic and cDNA sequences of the HvCBL4 alleles were obtained, revealing a single Ala111Thr amino acid substitution difference in the encoded proteins. The known crystal structure of SOS3 was used as a template to obtain molecular models of the barley proteins, resulting in structures very similar to that of SOS3. The position in SOS3 corresponding to the barley substitution does not participate directly in Ca2+ binding, post-translational modifications or interaction with the SOS2 signalling partner. However, Thr111 but not Ala111 forms a predicted hydrogen bond with a neighbouring α-helix, which has potential implications for the overall structure and function of the barley protein. HvCBL4 therefore represents a candidate for HvNax4 that warrants further investigation

UAV or Drones for Remote Sensing Applications in GPS/GNSS Enabled and GPS/GNSS Denied Environments

The design of novel UAV systems and the use of UAV platforms integrated with robotic sensing and imaging techniques, as well as the development of processing workflows and the capacity of ultra-high temporal and spatial resolution data, have enabled a rapid uptake of UAVs and drones across several industries and application domains.This book provides a forum for high-quality peer-reviewed papers that broaden awareness and understanding of single- and multiple-UAV developments for remote sensing applications, and associated developments in sensor technology, data processing and communications, and UAV system design and sensing capabilities in GPS-enabled and, more broadly, Global Navigation Satellite System (GNSS)-enabled and GPS/GNSS-denied environments.Contributions include:UAV-based photogrammetry, laser scanning, multispectral imaging, hyperspectral imaging, and thermal imaging;UAV sensor applications; spatial ecology; pest detection; reef; forestry; volcanology; precision agriculture wildlife species tracking; search and rescue; target tracking; atmosphere monitoring; chemical, biological, and natural disaster phenomena; fire prevention, flood prevention; volcanic monitoring; pollution monitoring; microclimates; and land use;Wildlife and target detection and recognition from UAV imagery using deep learning and machine learning techniques;UAV-based change detection

Confocal Laser Scanning Microscopy for Spectroscopic Studies of Living Photosynthetic Cells

Self-fluorescence of light-harvesting complex is a powerful tool for investigation of living photosynthetic microorganisms. As the physiological state of single cells of such microorganisms is closely related to the operation and activity of photosynthetic system, any variations in spectroscopic properties of their self-fluorescence indicate the changes in their physiological state. In this chapter, we present several applications of confocal laser scanning microscopy (CLSM) for investigation of living photosynthetic cells. A set of ordinary CLSM techniques will be applied for studying of cyanobacteria (or blue-green algae) such as 3D imaging, spectral imaging, microscopic spectroscopy, and fluorescence recovery after photobleaching (FRAP). Cyanobacteria were chosen as a model microorganism due to their great importance for different scientific and biotechnological applications. Cyanobacteria are the most ancient photosynthetic microorganisms on Earth. Nowadays, cyanobacteria are one of the most wide-spreaded organisms in nature, and the ecological aspect in their investigation is quite valuable. On the other hand, thousand strains belonging to different species are cultivated in biolaboratories all over the world for different biotechnological applications such as biofuel cells, food production, pharmaceuticals, fertilizers, etc. Thus, the noninvasive spectroscopic methods are quite important for monitoring of physiological state of cyanobacterial cultures and other photosynthetic microorganisms

Predictive Modeling of Organic Pollutant Leaching and Transport Behavior at the Lysimeter and Field Scales

Soil and groundwater pollution has become a global issue since the advent of industrialization and mechanized agriculture. Some contaminants such as PAHs may persist in the subsurface for decades and centuries. In a bid to address these issues, protection of groundwater must be based on the quantification of potential threats to pollution at the subsurface which is often inaccessible. Risk assessment of groundwater pollution may however be strongly supported by applying process-based simulation models, which turn out to be particularly helpful with regard to long-term predictions, which cannot be undertaken by experiments. Such reliable predictions, however, can only be achieved if the used modeling tool is known to be applicable. The aim of this work was threefold. First, a source strength function was developed to describe the leaching behavior of point source organic contaminants and thereby acting as a time-dependent upper boundary condition for transport models. For general application of these functions dimensionless numbers known as Damköhler numbers were used to characterize the reaction of the pollutants with the solid matrix. Two functions were derived and have been incorporated into an Excel worksheet to act as a practical aid in the quantification of leaching behavior of organic contaminant in seepage water prognoses. Second, the process based model tool SMART, which is well validated for laboratory scale data, was applied to lysimeter scale data from two research centres, FZJ (Jülich) and GSF (München) for long term predictions. Results from pure forward model runs show a fairly good correlation with the measured data. Finally, the derived source term functions in combination with the SMART model were used to assess groundwater vulnerability beneath a typical landfill at Kwabenya in Ghana. The predicted breakthrough time after leaking from the landfill was more than 200 years considering the operational time of the facility (30 years). Considering contaminant degradation, the landfill would therefore not cause groundwater pollution under the simulated scenarios and the SMART model can be used to establish waste acceptance criteria for organic contaminants in the landfill at KwabenyaSeit dem Beginn der Industrialisierung und der mechanisierten Landwirtschaft wurde die Boden- und Grundwasserverschmutzung zu einem weltweiten Problem. Einige Schadstoffe wie z. B. PAK können für Jahrzehnte oder Jahrhunderte im Untergrund bestehen. Um diese Probleme behandeln zu können, muss der Schutz des Grundwassers basierend auf der Quantifizierung potentieller Gefährdungen des zumeist unzugänglichen Untergrundes erfolgen. Risikoabschätzungen von Grundwasserverschmutzungen können jedoch durch die Anwendung prozess-basierter Simulationsmodelle erheblich unterstützt werden, die sich besonders im Hinblick auf Langzeitvorhersagen als hilfreich erweisen und nicht experimentell ermittelbar sind. Derart zuverlässige Vorhersagen können jedoch nur erhalten werden, wenn das verwendete Modellierwerkzeug als anwendbar bekannt ist. Das Ziel dieser Arbeit bestand aus drei Teilen. Erstens wurde eine Quellstärke-funktion entwickelt, die das Ausbreitungsverhalten organischer Schadstoffe aus einer Punktquelle beschreibt und dadurch als zeitabhängige obere Randbedingung bei Transportmodellen dienen kann. Im Hinblick auf die allgemeine Anwendbarkeit dieser Funktion werden als Damköhler-Zahlen bekannte, dimensionslose Zahlen verwendet, um die Reaktion von Schadstoffen mit Feststoffen zu charakterisieren. Zwei Funktionen wurden abgeleitet und in ein Excel-Arbeitsblatt eingefügt, das ein praktisches Hilfsmittel bei der Quantifizierung des Freisetzungsverhaltens organischer Schadstoffe im Rahmen der Sickerwasserprognose darstellt. Der zweite Teil dieser Arbeit beinhaltet die Anwendung des prozessbasierten und mittels Laborexperimenten validierten Modellwerkzeugs SMART für Langzeitprognosen auf der Lysimeterskala anhand von Daten zweier Forschungszentren, FZJ (Jülich) und GSF (München). Ergebnisse reiner Vorwärtsmodellierungsläufe zeigten gute Übereinstimmungen mit den gemessenen Daten. Im dritten Teil wurden die erhaltenen Quellstärkefunktionen in Kombination mit dem SMART-Modell eingesetzt, um das Grundwassergefährdungspotential unter einer typischen Deponie in Kwabenya, Ghana, einzuschätzen. Die vorhergesagten Durchbruchszeiten nach einer Leckage in der Deponie betragen über 200 Jahre bei einer Betriebszeit von 30 Jahren. Unter Berücksichtigung des Schadstoffabbaus verursacht die Deponie somit keine Grundwasserverunreinigung im Rahmen der simulierten Szenarien und das SMART-Modell kann verwendet werden, um Schadstoffgrenzwerte für organische Schadstoffe in der Deponie in Kwabenya festzulegen

Photogrammetric techniques for across-scale soil erosion assessment: Developing methods to integrate multi-temporal high resolution topography data at field plots

Soil erosion is a complex geomorphological process with varying influences of different impacts at different spatio-temporal scales. To date, measurement of soil erosion is predominantly realisable at specific scales, thereby detecting separate processes, e.g. interrill erosion contrary to rill erosion. It is difficult to survey soil surface changes at larger areal coverage such as field scale with high spatial resolution. Either net changes at the system outlet or remaining traces after the erosional event are usually measured. Thus, either quasi-point measurements are extrapolated to the corresponding area without knowing the actual sediment source as well as sediment storage behaviour on the plot or erosion rates are estimated disrupting the area of investigation during the data acquisition impeding multi-temporal assessment. Furthermore, established methods of soil erosion detection and quantification are typically only reliable for large event magnitudes, very labour and time intense, or inflexible. To better observe soil erosion processes at field scale and under natural conditions, the development of a method is necessary, which identifies and quantifies sediment sources and sinks at the hillslope with high spatial resolution and captures single precipitation events as well as allows for longer observation periods. Therefore, an approach is introduced, which measures soil surface changes for multi-spatio-temporal scales without disturbing the area of interest. Recent advances regarding techniques to capture high resolution topography (HiRT) data led to several promising tools for soil erosion measurement with corresponding advantages but also disadvantages. The necessity exists to evaluate those methods because they have been rarely utilised in soil surface studies. On the one hand, there is terrestrial laser scanning (TLS), which comprises high error reliability and retrieves 3D information directly. And on the other hand, there is unmanned aerial vehicle (UAV) technology in combination with structure from motion (SfM) algorithms resulting in UAV photogrammetry, which is very flexible in the field and depicts a beneficial perspective. Evaluation of the TLS feasibility reveals that this method implies a systematic error that is distance-related and temporal constant for the investigated device and can be corrected transferring calibration values retrieved from an estimated lookup table. However, TLS still reaches its application limits quickly due to an unfavourable (almost horizontal) scanning view at the soil surface resulting in a fast decrease of point density and increase of noise with increasing distance from the device. UAV photogrammetry allows for a better perspective (birds-eye view) onto the area of interest, but possesses more complex error behaviour, especially in regard to the systematic error of a DEM dome, which depends on the method for 3D reconstruction from 2D images (i.e. options for additional implementation of observations) and on the image network configuration (i.e. parallel-axes and control point configuration). Therefore, a procedure is developed that enables flexible usage of different cameras and software tools without the need of additional information or specific camera orientations and yet avoiding this dome error. Furthermore, the accuracy potential of UAV photogrammetry describing rough soil surfaces is assessed because so far corresponding data is missing. Both HiRT methods are used for multi-temporal measurement of soil erosion processes resulting in surface changes of low magnitudes, i.e. rill and especially interrill erosion. Thus, a reference with high accuracy and stability is a requirement. A local reference system with sub-cm and at its best 1 mm accuracy is setup and confirmed by control surveys. TLS and UAV photogrammetry data registration with these targets ensures that errors due to referencing are of minimal impact. Analysis of the multi-temporal performance of both HiRT methods affirms TLS to be suitable for the detection of erosion forms of larger magnitudes because of a level of detection (LoD) of 1.5 cm. UAV photogrammetry enables the quantification of even lower magnitude changes (LoD of 1 cm) and a reliable observation of the change of surface roughness, which is important for runoff processes, at field plots due to high spatial resolution (1 cm²). Synergetic data fusion as a subsequent post-processing step is necessary to exploit the advantages of both HiRT methods and potentially further increase the LoD. The unprecedented high level of information entails the need for automatic geomorphic feature extraction due to the large amount of novel content. Therefore, a method is developed, which allows for accurate rill extraction and rill parameter calculation with high resolution enabling new perspectives onto rill erosion that has not been possible before due to labour and area access limits. Erosion volume and cross sections are calculated for each rill revealing a dominant rill deepening. Furthermore, rill shifting in dependence of the rill orientation towards the dominant wind direction is revealed. Two field plots are installed at erosion prone positions in the Mediterranean (1,000 m²) and in the European loess belt (600 m²) to ensure the detection of surface changes, permitting the evaluation of the feasibility, potential and limits of TLS and UAV photogrammetry in soil erosion studies. Observations are made regarding sediment connectivity at the hillslope scale. Both HiRT methods enable the identification of local sediment sources and sinks, but still exhibiting some degree of uncertainty due to the comparable high LoD in regard to laminar accumulation and interrill erosion processes. At both field sites wheel tracks and erosion rills increase hydrological and sedimentological connectivity. However, at the Mediterranean field plot especially dis-connectivity is obvious. At the European loess belt case study a triggering event could be captured, which led to high erosion rates due to high soil moisture contents and yet further erosion increase due to rill amplification after rill incision. Estimated soil erosion rates range between 2.6 tha-1 and 121.5 tha-1 for single precipitation events and illustrate a large variability due to very different site specifications, although both case studies are located in fragile landscapes. However, the susceptibility to soil erosion has different primary causes, i.e. torrential precipitation at the Mediterranean site and high soil erodibility at the European loess belt site. The future capability of the HiRT methods is their potential to be applicable at yet larger scales. Hence, investigations of the importance of gullys for sediment connectivity between hillslopes and channels are possible as well as the possible explanation of different erosion rates observed at hillslope and at catchment scales because local sediment sink and sources can be quantified. In addition, HiRT data can be a great tool for calibrating, validating and enhancing soil erosion models due to the unprecedented level of detail and the flexible multi-spatio-temporal application