5 resultados para Field-measurements

em Universitätsbibliothek Kassel, Universität Kassel, Germany


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For millennia oasis agriculture has been the backbone of rural livelihood in the desertic Sultanate of Oman. However, little is known about the functioning of these oasis systems, in particular with respect to the C turnover. The objective was to determine the effects of crop, i.e. alfalfa, wheat and bare fallow on the CO2 evolution rate during an irrigation cycle in relation to changes in soil water content and soil temperature. The gravimetric soil water content decreased from initially 24% to approximately 16% within 7 days after irrigation. The mean CO2 evolution rates increased significantly in the order fallow (27.4 mg C m^−2 h^−1) < wheat (45.5 mg C m^−2 h^−1) < alfalfa (97.5 mg C m^−2 h^−1). It can be calculated from these data that the CO2 evolution rate of the alfalfa root system was nearly four times higher than the corresponding rate in the wheat root system. The decline in CO2 evolution rate, especially during the first 4 days after irrigation, was significantly related to the decline in the gravimetric water content, with r = 0.70. CO2 evolution rate and soil temperature at 5 cm depth were negatively correlated (r = -0.56,n = 261) due to increasing soil temperature with decreasing gravimetric water content.

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Summary: Productivity, botanical composition and forage quality of legume-grass swards are important factors for successful arable farming in both organic and conventional farming systems. As these attributes can vary considerably within a field, a non-destructive method of detection while doing other tasks would facilitate a more targeted management of crops, forage and nutrients in the soil-plant-animal system. This study was undertaken to explore the potential of field spectral measurements for a non destructive prediction of dry matter (DM) yield, legume proportion in the sward, metabolizable energy (ME), ash content, crude protein (CP) and acid detergent fiber (ADF) of legume-grass mixtures. Two experiments were conducted in a greenhouse under controlled conditions which allowed collecting spectral measurements which were free from interferences such as wind, passing clouds and changing angles of solar irradiation. In a second step this initial investigation was evaluated in the field by a two year experiment with the same legume-grass swards. Several techniques for analysis of the hyperspectral data set were examined in this study: four vegetation indices (VIs): simple ratio (SR), normalized difference vegetation index (NDVI), enhanced vegetation index (EVI) and red edge position (REP), two-waveband reflectance ratios, modified partial least squares (MPLS) regression and stepwise multiple linear regression (SMLR). The results showed the potential of field spectroscopy and proved its usefulness for the prediction of DM yield, ash content and CP across a wide range of legume proportion and growth stage. In all investigations prediction accuracy of DM yield, ash content and CP could be improved by legume-specific calibrations which included mixtures and pure swards of perennial ryegrass and of the respective legume species. The comparison between the greenhouse and the field experiments showed that the interaction between spectral reflectance and weather conditions as well as incidence angle of light interfered with an accurate determination of DM yield. Further research is hence needed to improve the validity of spectral measurements in the field. Furthermore, the developed models should be tested on varying sites and vegetation periods to enhance the robustness and portability of the models to other environmental conditions.

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In den letzten Jahrzehnten haben sich makroskalige hydrologische Modelle als wichtige Werkzeuge etabliert um den Zustand der globalen erneuerbaren Süßwasserressourcen flächendeckend bewerten können. Sie werden heutzutage eingesetzt um eine große Bandbreite wissenschaftlicher Fragestellungen zu beantworten, insbesondere hinsichtlich der Auswirkungen anthropogener Einflüsse auf das natürliche Abflussregime oder der Auswirkungen des globalen Wandels und Klimawandels auf die Ressource Wasser. Diese Auswirkungen lassen sich durch verschiedenste wasserbezogene Kenngrößen abschätzen, wie z.B. erneuerbare (Grund-)Wasserressourcen, Hochwasserrisiko, Dürren, Wasserstress und Wasserknappheit. Die Weiterentwicklung makroskaliger hydrologischer Modelle wurde insbesondere durch stetig steigende Rechenkapazitäten begünstigt, aber auch durch die zunehmende Verfügbarkeit von Fernerkundungsdaten und abgeleiteten Datenprodukten, die genutzt werden können, um die Modelle anzutreiben und zu verbessern. Wie alle makro- bis globalskaligen Modellierungsansätze unterliegen makroskalige hydrologische Simulationen erheblichen Unsicherheiten, die (i) auf räumliche Eingabedatensätze, wie z.B. meteorologische Größen oder Landoberflächenparameter, und (ii) im Besonderen auf die (oftmals) vereinfachte Abbildung physikalischer Prozesse im Modell zurückzuführen sind. Angesichts dieser Unsicherheiten ist es unabdingbar, die tatsächliche Anwendbarkeit und Prognosefähigkeit der Modelle unter diversen klimatischen und physiographischen Bedingungen zu überprüfen. Bisher wurden die meisten Evaluierungsstudien jedoch lediglich in wenigen, großen Flusseinzugsgebieten durchgeführt oder fokussierten auf kontinentalen Wasserflüssen. Dies steht im Kontrast zu vielen Anwendungsstudien, deren Analysen und Aussagen auf simulierten Zustandsgrößen und Flüssen in deutlich feinerer räumlicher Auflösung (Gridzelle) basieren. Den Kern der Dissertation bildet eine umfangreiche Evaluierung der generellen Anwendbarkeit des globalen hydrologischen Modells WaterGAP3 für die Simulation von monatlichen Abflussregimen und Niedrig- und Hochwasserabflüssen auf Basis von mehr als 2400 Durchflussmessreihen für den Zeitraum 1958-2010. Die betrachteten Flusseinzugsgebiete repräsentieren ein breites Spektrum klimatischer und physiographischer Bedingungen, die Einzugsgebietsgröße reicht von 3000 bis zu mehreren Millionen Quadratkilometern. Die Modellevaluierung hat dabei zwei Zielsetzungen: Erstens soll die erzielte Modellgüte als Bezugswert dienen gegen den jegliche weiteren Modellverbesserungen verglichen werden können. Zweitens soll eine Methode zur diagnostischen Modellevaluierung entwickelt und getestet werden, die eindeutige Ansatzpunkte zur Modellverbesserung aufzeigen soll, falls die Modellgüte unzureichend ist. Hierzu werden komplementäre Modellgütemaße mit neun Gebietsparametern verknüpft, welche die klimatischen und physiographischen Bedingungen sowie den Grad anthropogener Beeinflussung in den einzelnen Einzugsgebieten quantifizieren. WaterGAP3 erzielt eine mittlere bis hohe Modellgüte für die Simulation von sowohl monatlichen Abflussregimen als auch Niedrig- und Hochwasserabflüssen, jedoch sind für alle betrachteten Modellgütemaße deutliche räumliche Muster erkennbar. Von den neun betrachteten Gebietseigenschaften weisen insbesondere der Ariditätsgrad und die mittlere Gebietsneigung einen starken Einfluss auf die Modellgüte auf. Das Modell tendiert zur Überschätzung des jährlichen Abflussvolumens mit steigender Aridität. Dieses Verhalten ist charakteristisch für makroskalige hydrologische Modelle und ist auf die unzureichende Abbildung von Prozessen der Abflussbildung und –konzentration in wasserlimitierten Gebieten zurückzuführen. In steilen Einzugsgebieten wird eine geringe Modellgüte hinsichtlich der Abbildung von monatlicher Abflussvariabilität und zeitlicher Dynamik festgestellt, die sich auch in der Güte der Niedrig- und Hochwassersimulation widerspiegelt. Diese Beobachtung weist auf notwendige Modellverbesserungen in Bezug auf (i) die Aufteilung des Gesamtabflusses in schnelle und verzögerte Abflusskomponente und (ii) die Berechnung der Fließgeschwindigkeit im Gerinne hin. Die im Rahmen der Dissertation entwickelte Methode zur diagnostischen Modellevaluierung durch Verknüpfung von komplementären Modellgütemaßen und Einzugsgebietseigenschaften wurde exemplarisch am Beispiel des WaterGAP3 Modells erprobt. Die Methode hat sich als effizientes Werkzeug erwiesen, um räumliche Muster in der Modellgüte zu erklären und Defizite in der Modellstruktur zu identifizieren. Die entwickelte Methode ist generell für jedes hydrologische Modell anwendbar. Sie ist jedoch insbesondere für makroskalige Modelle und multi-basin Studien relevant, da sie das Fehlen von feldspezifischen Kenntnissen und gezielten Messkampagnen, auf die üblicherweise in der Einzugsgebietsmodellierung zurückgegriffen wird, teilweise ausgleichen kann.

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Sweet potato is an important strategic agricultural crop grown in many countries around the world. The roots and aerial vine components of the crop are used for both human consumption and, to some extent as a cheap source of animal feed. In spite of its economic value and growing contribution to health and nutrition, harvested sweet potato roots and aerial vine components has limited shelf-life and is easily susceptible to post-harvest losses. Although post-harvest losses of both sweet potato roots and aerial vine components is significant, there is no information available that will support the design and development of appropriate storage and preservation systems. In this context, the present study was initiated to improve scientific knowledge about sweet potato post-harvest handling. Additionally, the study also seeks to develop a PV ventilated mud storehouse for storage of sweet potato roots under tropical conditions. In study one, airflow resistance of sweet potato aerial vine components was investigated. The influence of different operating parameters such as airflow rate, moisture content and bulk depth at different levels on airflow resistance was analyzed. All the operating parameters were observed to have significant (P < 0.01) effect on airflow resistance. Prediction models were developed and were found to adequately describe the experimental pressure drop data. In study two, the resistance of airflow through unwashed and clean sweet potato roots was investigated. The effect of sweet potato roots shape factor, surface roughness, orientation to airflow, and presence of soil fraction on airflow resistance was also assessed. The pressure drop through unwashed and clean sweet potato roots was observed to increase with higher airflow, bed depth, root grade composition, and presence of soil fraction. The physical properties of the roots were incorporated into a modified Ergun model and compared with a modified Shedd’s model. The modified Ergun model provided the best fit to the experimental data when compared with the modified Shedd’s model. In study three, the effect of sweet potato root size (medium and large), different air velocity and temperature on the cooling/or heating rate and time of individual sweet potato roots were investigated. Also, a simulation model which is based on the fundamental solution of the transient equations was proposed for estimating the cooling and heating time at the centre of sweet potato roots. The results showed that increasing air velocity during cooling and heating significantly (P < 0.05) affects the cooling and heating times. Furthermore, the cooling and heating times were significantly different (P < 0.05) among medium and large size sweet potato roots. Comparison of the simulation results with experimental data confirmed that the transient simulation model can be used to accurately estimate the cooling and heating times of whole sweet potato roots under forced convection conditions. In study four, the performance of charcoal evaporative cooling pad configurations for integration into sweet potato roots storage systems was investigated. The experiments were carried out at different levels of air velocity, water flow rates, and three pad configurations: single layer pad (SLP), double layers pad (DLP) and triple layers pad (TLP) made out of small and large size charcoal particles. The results showed that higher air velocity has tremendous effect on pressure drop. Increasing the water flow rate above the range tested had no practical benefits in terms of cooling. It was observed that DLP and TLD configurations with larger wet surface area for both types of pads provided high cooling efficiencies. In study five, CFD technique in the ANSYS Fluent software was used to simulate airflow distribution in a low-cost mud storehouse. By theoretically investigating different geometries of air inlet, plenum chamber, and outlet as well as its placement using ANSYS Fluent software, an acceptable geometry with uniform air distribution was selected and constructed. Experimental measurements validated the selected design. In study six, the performance of the developed PV ventilated system was investigated. Field measurements showed satisfactory results of the directly coupled PV ventilated system. Furthermore, the option of integrating a low-cost evaporative cooling system into the mud storage structure was also investigated. The results showed a reduction of ambient temperature inside the mud storehouse while relative humidity was enhanced. The ability of the developed storage system to provide and maintain airflow, temperature and relative humidity which are the key parameters for shelf-life extension of sweet potato roots highlight its ability to reduce post-harvest losses at the farmer level, particularly under tropical climate conditions.

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A real-time analysis of renewable energy sources, such as arable crops, is of great importance with regard to an optimised process management, since aspects of ecology and biodiversity are considered in crop production in order to provide a sustainable energy supply by biomass. This study was undertaken to explore the potential of spectroscopic measurement procedures for the prediction of potassium (K), chloride (Cl), and phosphate (P), of dry matter (DM) yield, metabolisable energy (ME), ash and crude fibre contents (ash, CF), crude lipid (EE), nitrate free extracts (NfE) as well as of crude protein (CP) and nitrogen (N), respectively in pretreated samples and undisturbed crops. Three experiments were conducted, one in a laboratory using near infrared reflectance spectroscopy (NIRS) and two field spectroscopic experiments. Laboratory NIRS measurements were conducted to evaluate to what extent a prediction of quality parameters is possible examining press cakes characterised by a wide heterogeneity of their parent material. 210 samples were analysed subsequent to a mechanical dehydration using a screw press. Press cakes serve as solid fuel for thermal conversion. Field spectroscopic measurements were carried out with regard to further technical development using different field grown crops. A one year lasting experiment over a binary mixture of grass and red clover examined the impact of different degrees of sky cover on prediction accuracies of distinct plant parameters. Furthermore, an artificial light source was used in order to evaluate to what extent such a light source is able to minimise cloud effects on prediction accuracies. A three years lasting experiment with maize was conducted in order to evaluate the potential of off-nadir measurements inside a canopy to predict different quality parameters in total biomass and DM yield using one sensor for a potential on-the-go application. This approach implements a measurement of the plants in 50 cm segments, since a sensor adjusted sideways is not able to record the entire plant height. Calibration results obtained by nadir top-of-canopy reflectance measurements were compared to calibration results obtained by off-nadir measurements. Results of all experiments approve the applicability of spectroscopic measurements for the prediction of distinct biophysical and biochemical parameters in the laboratory and under field conditions, respectively. The estimation of parameters could be conducted to a great extent with high accuracy. An enhanced basis of calibration for the laboratory study and the first field experiment (grass/clover-mixture) yields in improved robustness of calibration models and allows for an extended application of spectroscopic measurement techniques, even under varying conditions. Furthermore, off-nadir measurements inside a canopy yield in higher prediction accuracies, particularly for crops characterised by distinct height increment as observed for maize.