Determination of yield and quality parameters of energy crops applying laboratory and field spectroscopy

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.

Development of thermo-analytical prediction and classification models for food in thermal devices using a multi sensor system and artificial neural networks

Die thermische Verarbeitung von Lebensmitteln beeinflusst deren Qualität und ernährungsphysiologischen Eigenschaften. Im Haushalt ist die Überwachung der Temperatur innerhalb des Lebensmittels sehr schwierig. Zudem ist das Wissen über optimale Temperatur- und Zeitparameter für die verschiedenen Speisen oft unzureichend. Die optimale Steuerung der thermischen Zubereitung ist maßgeblich abhängig von der Art des Lebensmittels und der äußeren und inneren Temperatureinwirkung während des Garvorgangs. Das Ziel der Arbeiten war die Entwicklung eines automatischen Backofens, der in der Lage ist, die Art des Lebensmittels zu erkennen und die Temperatur im Inneren des Lebensmittels während des Backens zu errechnen. Die für die Temperaturberechnung benötigten Daten wurden mit mehreren Sensoren erfasst. Hierzu kam ein Infrarotthermometer, ein Infrarotabstandssensor, eine Kamera, ein Temperatursensor und ein Lambdasonde innerhalb des Ofens zum Einsatz. Ferner wurden eine Wägezelle, ein Strom- sowie Spannungs-Sensor und ein Temperatursensor außerhalb des Ofens genutzt. Die während der Aufheizphase aufgenommen Datensätze ermöglichten das Training mehrerer künstlicher neuronaler Netze, die die verschiedenen Lebensmittel in die entsprechenden Kategorien einordnen konnten, um so das optimale Backprogram auszuwählen. Zur Abschätzung der thermische Diffusivität der Nahrung, die von der Zusammensetzung (Kohlenhydrate, Fett, Protein, Wasser) abhängt, wurden mehrere künstliche neuronale Netze trainiert. Mit Ausnahme des Fettanteils der Lebensmittel konnten alle Komponenten durch verschiedene KNNs mit einem Maximum von 8 versteckten Neuronen ausreichend genau abgeschätzt werden um auf deren Grundlage die Temperatur im inneren des Lebensmittels zu berechnen. Die durchgeführte Arbeit zeigt, dass mit Hilfe verschiedenster Sensoren zur direkten beziehungsweise indirekten Messung der äußeren Eigenschaften der Lebensmittel sowie KNNs für die Kategorisierung und Abschätzung der Lebensmittelzusammensetzung die automatische Erkennung und Berechnung der inneren Temperatur von verschiedensten Lebensmitteln möglich ist.

Spatial and harvesting influence on growth, yield, quality and economic potential of Kalmegh (Andrographis paniculata Wall Ex. Nees)

Andrographis paniculata, commonly known as Kalmegh, is used both in Ayurvedic and Unani system of medicines because of its immunological, antibacterial and hepatoprotective properties. This study was carried out to investigate the influence of four harvesting times (120,135,150 days after planting and at seed maturity) and four planting distances (30×15, 30×10, 20×15 and 20×10 cm) on growth, dry herbage biomass, seed yield and quality traits of Andrographis paniculata at CCS Haryana Agricultural University, Hisar, India in the two years 2005 and 2006. The treatments were laid out in a split plot design with three replications. The maximum values for dry herbage biomass yield (5.14 t ha^(-1)), net returns (760.00 EUR ha^(-1)), B:C ratio (2.59), andrographolide content (2.63%) and total yield (135.00 kg ha^(-1)) were detected 135 days after planting with an optimum planting distance of 30×15 cm. However, the maximum iron content was estimated 120 days after planting. The highest dry herbage (4.58 t ha^(-1)) and maximum seed yield (19.7 kg ha^(-1)) were registered at plants that were lined out with a distance of 20×10 cm.

Climate change and hunger as the challenges in the global food system

In the last decades, there has been a growing tendency towards international trade and globalisation, particularly leading to a significant increase in flows of agricultural commodities worldwide. From a macroeconomic perspective, the commodity projections are more optimistic than the previous years and the long run tendency shows an increasing demand for feedstock. However, the strong shifts of shocks and fluctuations (in terms of prices and volumes) are a concern to global food security, with the number of hungry people rising to nearly one billion. Agriculture is a main user of natural resources, and it has a strong link with rural societies and the environment. Forecasted impacts from climate change, limited productive endorsements and emerging rivals on crop production, such bio-energy, aggravate the panorama on food scarcity. In this context, it is a great challenge on farming and food systems to reduce global hunger and produce in sustainable ways adequate supplies for food, feed, and non-food uses. The main objective of this work is to question the sustainability of food and agriculture systems. It is particularly interesting to know its role and if it will be able to respond to a growing population with increasing food demand in a world where pressure on land, water and other natural resources are already evident, and, moreover, climate change will also condition and impact the outcome. Furthermore, a deeper focus will be set on developing countries, which are expected to emerge and take a leading role in the international arena. This short paper is structured as follows: Section I, “Introduction”, describes the social situation regarding hunger, Section II, “Global Context”, attempts to summarise the current scenario in the international trading scheme and present the emerging rivals for primary resources, and in Section III, “Climate Change”, presents an overview of possible changes in the sector and future perspectives in the field. Finally, in Section IV, “Conclusion”, the main conclusions are presented.

Contradictions within the Modern Food System: Nutritional Disbalance across the Globe, Its Main Drivers and Possible Ways Out

Contemporary food production, given the degree of technology being applied in it and the present state of scientific knowledge, should be able to feed the world. Corresponding statistics show that in fact the volumes of modern food production confirm this statement. Yet, the present nutritional situation across the globe leaves much to be desired: on the one hand the numbers of undernourished and malnourished people are still high and even growing in some regions, and on the other hand there is an increasing number of overweight and obese people who are experiencing (or are at risk of) adverse health impacts as consequences. The question arises how this situation is possible given the present state of food production and knowledge, and also in terms of nutrition basics when talking about the latter. When arguing about the main causes of the present situation with nutrition across the globe, it is the modern food system with its distortions that is often criticised with emphasis placed on inappropriate food distribution as one of the key problems. However it is not only food distribution that shapes inequalities in terms of food availability and accessibility – there is a number of other factors contributing to this situation including political influences. Each of the drivers of the present situation might affect more than one part and have outcomes in different dimensions. Therefore it makes sense to apply a holistic approach when viewing the modern food system, embracing all the elements and existing relationships between them for this will facilitate taking appropriate actions in order to target the desired outcome in the best possible way. Applying a systematic approach and linking various elements with corresponding interactions among them allows for picturing all the possible outcomes and hence finding the way for a better solution on global level – a solution to the present problem with nutritional disbalance across the globe.

More than irrigation - The Balinese Subak system as a unique form of cooperative water resource management in Indonesia

For over 1,000 years, the Balinese have developed a unique system of democratic and sustainable water irrigation. It has shaped the cultural landscapes of Bali and enables local communities to manage the ecology of terraced rice fields at the scale of whole watersheds. The Subak system has made the Balinese the most productive rice growers in Indonesia and ensures a high level of food sovereignty for a dense population on the volcanic island. The Subak system provides a vibrant example of a diverse, ecologically sustainable, economically productive and democratic water management system that is also characterized by its nonreliance on fossil fuel derivatives or heavy machinery. In 2012, UNESCO has recognized five rice terraces and their water temples as World Heritage site and supports its conservation and protection. However, the fragile Subak system is threatened for its complexity and interconnectedness by new agricultural practices and increasing tourism on the island.

Managing Quality Properties of Web Service Compositions

Web services from different partners can be combined to applications that realize a more complex business goal. Such applications built as Web service compositions define how interactions between Web services take place in order to implement the business logic. Web service compositions not only have to provide the desired functionality but also have to comply with certain Quality of Service (QoS) levels. Maximizing the users' satisfaction, also reflected as Quality of Experience (QoE), is a primary goal to be achieved in a Service-Oriented Architecture (SOA). Unfortunately, in a dynamic environment like SOA unforeseen situations might appear like services not being available or not responding in the desired time frame. In such situations, appropriate actions need to be triggered in order to avoid the violation of QoS and QoE constraints. In this thesis, proper solutions are developed to manage Web services and Web service compositions with regard to QoS and QoE requirements. The Business Process Rules Language (BPRules) was developed to manage Web service compositions when undesired QoS or QoE values are detected. BPRules provides a rich set of management actions that may be triggered for controlling the service composition and for improving its quality behavior. Regarding the quality properties, BPRules allows to distinguish between the QoS values as they are promised by the service providers, QoE values that were assigned by end-users, the monitored QoS as measured by our BPR framework, and the predicted QoS and QoE values. BPRules facilitates the specification of certain user groups characterized by different context properties and allows triggering a personalized, context-aware service selection tailored for the specified user groups. In a service market where a multitude of services with the same functionality and different quality values are available, the right services need to be selected for realizing the service composition. We developed new and efficient heuristic algorithms that are applied to choose high quality services for the composition. BPRules offers the possibility to integrate multiple service selection algorithms. The selection algorithms are applicable also for non-linear objective functions and constraints. The BPR framework includes new approaches for context-aware service selection and quality property predictions. We consider the location information of users and services as context dimension for the prediction of response time and throughput. The BPR framework combines all new features and contributions to a comprehensive management solution. Furthermore, it facilitates flexible monitoring of QoS properties without having to modify the description of the service composition. We show how the different modules of the BPR framework work together in order to execute the management rules. We evaluate how our selection algorithms outperform a genetic algorithm from related research. The evaluation reveals how context data can be used for a personalized prediction of response time and throughput.