Statistical evaluation of texture analysis from the biocrystallization method

The consumers are becoming more concerned about food quality, especially regarding how, when and where the foods are produced (Haglund et al., 1999; Kahl et al., 2004; Alföldi, et al., 2006). Therefore, during recent years there has been a growing interest in the methods for food quality assessment, especially in the picture-development methods as a complement to traditional chemical analysis of single compounds (Kahl et al., 2006). The biocrystallization as one of the picture-developing method is based on the crystallographic phenomenon that when crystallizing aqueous solutions of dihydrate CuCl2 with adding of organic solutions, originating, e.g., from crop samples, biocrystallograms are generated with reproducible crystal patterns (Kleber & Steinike-Hartung, 1959). Its output is a crystal pattern on glass plates from which different variables (numbers) can be calculated by using image analysis. However, there is a lack of a standardized evaluation method to quantify the morphological features of the biocrystallogram image. Therefore, the main sakes of this research are (1) to optimize an existing statistical model in order to describe all the effects that contribute to the experiment, (2) to investigate the effect of image parameters on the texture analysis of the biocrystallogram images, i.e., region of interest (ROI), color transformation and histogram matching on samples from the project 020E170/F financed by the Federal Ministry of Food, Agriculture and Consumer Protection(BMELV).The samples are wheat and carrots from controlled field and farm trials, (3) to consider the strongest effect of texture parameter with the visual evaluation criteria that have been developed by a group of researcher (University of Kassel, Germany; Louis Bolk Institute (LBI), Netherlands and Biodynamic Research Association Denmark (BRAD), Denmark) in order to clarify how the relation of the texture parameter and visual characteristics on an image is. The refined statistical model was accomplished by using a lme model with repeated measurements via crossed effects, programmed in R (version 2.1.0). The validity of the F and P values is checked against the SAS program. While getting from the ANOVA the same F values, the P values are bigger in R because of the more conservative approach. The refined model is calculating more significant P values. The optimization of the image analysis is dealing with the following parameters: ROI(Region of Interest which is the area around the geometrical center), color transformation (calculation of the 1 dimensional gray level value out of the three dimensional color information of the scanned picture, which is necessary for the texture analysis), histogram matching (normalization of the histogram of the picture to enhance the contrast and to minimize the errors from lighting conditions). The samples were wheat from DOC trial with 4 field replicates for the years 2003 and 2005, “market samples”(organic and conventional neighbors with the same variety) for 2004 and 2005, carrot where the samples were obtained from the University of Kassel (2 varieties, 2 nitrogen treatments) for the years 2004, 2005, 2006 and “market samples” of carrot for the years 2004 and 2005. The criterion for the optimization was repeatability of the differentiation of the samples over the different harvest(years). For different samples different ROIs were found, which reflect the different pictures. The best color transformation that shows efficiently differentiation is relied on gray scale, i.e., equal color transformation. The second dimension of the color transformation only appeared in some years for the effect of color wavelength(hue) for carrot treated with different nitrate fertilizer levels. The best histogram matching is the Gaussian distribution. The approach was to find a connection between the variables from textural image analysis with the different visual criteria. The relation between the texture parameters and visual evaluation criteria was limited to the carrot samples, especially, as it could be well differentiated by the texture analysis. It was possible to connect groups of variables of the texture analysis with groups of criteria from the visual evaluation. These selected variables were able to differentiate the samples but not able to classify the samples according to the treatment. Contrarily, in case of visual criteria which describe the picture as a whole there is a classification in 80% of the sample cases possible. Herewith, it clearly can find the limits of the single variable approach of the image analysis (texture analysis).

Efficient data mining based on formal concept analysis

Formal Concept Analysis is an unsupervised learning technique for conceptual clustering. We introduce the notion of iceberg concept lattices and show their use in Knowledge Discovery in Databases (KDD). Iceberg lattices are designed for analyzing very large databases. In particular they serve as a condensed representation of frequent patterns as known from association rule mining. In order to show the interplay between Formal Concept Analysis and association rule mining, we discuss the algorithm TITANIC. We show that iceberg concept lattices are a starting point for computing condensed sets of association rules without loss of information, and are a visualization method for the resulting rules.

Conceptual knowledge processing with formal concept analysis and ontologies

Among many other knowledge representations formalisms, Ontologies and Formal Concept Analysis (FCA) aim at modeling ‘concepts’. We discuss how these two formalisms may complement another from an application point of view. In particular, we will see how FCA can be used to support Ontology Engineering, and how ontologies can be exploited in FCA applications. The interplay of FCA and ontologies is studied along the life cycle of an ontology: (i) FCA can support the building of the ontology as a learning technique. (ii) The established ontology can be analyzed and navigated by using techniques of FCA. (iii) Last but not least, the ontology may be used to improve an FCA application.

Organic consumers' attitudes and preferences regarding alternatives to piglet castration without anaesthesia and analgesia in organic farming - an explorative analysis

In Germany and other European countries piglets are routinely castrated in order to avoid the occurrence of boar taint, an off-flavour and off-odour of pork. Sensory perception of boar taint varies; however, it is regarded as very unpleasant by many people. Surgical castration which is an effective means against boar taint has commonly been performed without anaesthesia or analgesia within the piglets’ first seven days of life. Piglet castration without anaesthesia has been heavily criticised, as the assumption that young piglets perceive less pain than older animals cannot be supported by scientific evidence. Consequently, surgical castration is only allowed with anaesthesia and/or analgesia in organic farming throughout the European Union since January 2012. Abandoning piglet castration without pain relief requires the implementation of alternative methods which improve animal welfare while maintaining sensory meat quality. There are three relevant alternatives: castration with anaesthesia and/or analgesia to reduce pain, a vaccination against boar taint (immunocastration) and the fattening of uncastrated male pigs (fattening of boars) combined with measures to reduce and detect boar taint in meat. Consumers’ attitudes and opinions regarding the alternatives are an important factor with regard to the implementation of alternatives, as they are finally supposed to buy the meat. The objective of this dissertation was to explore organic consumers’ attitudes, preferences and willingness-to-pay regarding piglet castration without pain relief and the three alternatives. Important aspects for the evaluation of the alternatives and influencing factors (e.g. information, taste) on preferences and willingness-to-pay should also be identified. In autumn 2009 nine focus group discussions were conducted each followed by a Vickrey auction including a tasting of boar salami. Overall, 89 consumers of organic pork participated in the study. Information on piglet castration and alternatives (in three variants) was provided as a basis for discussion. The focus group data were analysed using qualitative content analysis. In order to compare the focus group results with those from the auctions, an innovative approach applying an adapted scoring model to further analyse the data set was used. The majority of participants were not aware that piglets are castrated without anaesthesia in organic farming. They reacted shocked and disappointed on learning about this practice which did not fit into their image of animal welfare standards in organic farming. Overall, the results show, that for consumers of organic pork castration with anaesthesia and analgesia as well as the fattening of boars may be acceptable alternatives in organic farming. Considering the strong food safety concerns regarding immunocastration, acceptance of this alternative may be questioned. Communication regarding alternatives to piglet castration without anaesthesia and analgesia should take into account that the relevance of the aspects animal welfare, food safety, taste and costs differs between alternatives. Furthermore, it seems advisable not to address an unappetizing topic like piglet castration directly at the point of sale so as not to deter consumers from buying organic pork. The issue of piglet castration demonstrates exemplarily that it is important for the organic sector to implement and maintain high animal welfare standards and communicate them in an appropriate way, thereby trying to prevent strong discrepancies between consumers’ expectations regarding animal husbandry in organic farming and actual conditions. So, disappointment of consumers and a loss of image due to negative reports about animal welfare issues can be avoided.

Magneto-optische Oberflächenplasmonresonanzeffekte in austauschverschobenen Dünnschichtsystemen

Die Wechselwirkungen zwischen Biomolekülen spielen eine zentrale Rolle in der biochemischen und pharmazeutischen Forschung. In der biomolekularen Interaktionsanalyse sind dabei Biosensoren auf Basis des Oberflächenplasmonresonanzeffekts (SPR-Effekt) weitverbreitet. Seit Einführung der ersten kommerziellen SPR-Biosensoren Anfang der 1990er Jahre wurden verschiedenste Messanordnungen sowie Materialsysteme mit dem Ziel einer möglichst hohen Empfindlichkeit getestet. Eine Möglichkeit zur Steigerung der Empfindlichkeit klassischer SPR-Systeme bieten sogenannte magneto-optische SPR-Biosensoren (MOSPR-Biosensoren). Grundlage der Empfindlichkeitssteigerung ist die gleichzeitige Messung des SPR-Effekts und des transversalen magneto-optischen KERR-Effekts (tMOKE). Bisherige Untersuchungen haben sich meist auf den Einfluss der Magnetisierung freier ferromagnetischer Schichten beschränkt. Im Rahmen dieser Arbeit wurden erstmals austauschverschobene Dünnschichtsysteme (EB-Systeme), eine Kombination aus Ferromagnet und Antiferromagnet, hinsichtlich ihrer Eignung für SPR- und MOSPR-basierte biosensorische Anwendungen untersucht. Aufgrund der remanenten Magnetisierung der ferromagnetischen Schicht und ihrer magnetischen Strukturierbarkeit sind EB-Systeme eine hochinteressante Plattform zur Realisierung neuer Biosensorkonzepte. Zur Reduzierung der stark dämpfendenden Wirkung magnetischer Materialien wurde das hier betrachtete IrMn/Co EB-System zwischen zwei Goldschichten eingebettet. Eine Gegenüberstellung optimierter Au/ IrMn/Co/Au-Systeme mit einem reinen Au-System, wie es typischerweise in kommerziellen SPR-basierten Biosensoren eingesetzt wird, demonstriert, dass mit den entwickelten EB-Systemen vergleichbare Empfindlichkeiten in SPR-Sensor-Anwendungen erreicht werden können. Die magneto-optische Aktivität der untersuchten Dünnschichtsysteme liegt im Bereich der Literaturwerte für Au/Co/Au-Systeme, mit denen erhöhte Empfindlichkeiten gegenüber Standard-SPR-Biosensoren realisiert wurden. Auf Grundlage magnetisch strukturierter Au/IrMn/Co/Au-Systeme wurden neue Biosensorkonzepte entwickelt und getestet. Erste Experimente belegen, dass mit diesen Schichtsystemen eine gleichzeitige Detektion der magnetisierungsabhängigen Reflektivitäten in ortsauflösenden MOSPR-Messungen möglich ist. Eine solche Messanordnung profitiert von der erhöhten Empfindlichkeit MOSPR-basierter Biosensoren, hohen Messgeschwindigkeiten und einem verbesserten Signal-Rausch-Verhältnis. Weiterhin wurde der domänenwandassistierte Transport (DOWMAT) superparamagnetischer Partikel über der Oberfläche eines exemplarischen EB-Systems, zur Sensorintegration von Misch-, Reinigungs- und Aufkonzentrationsfunktionen erfolgreich getestet. Die Ergebnisse demonstrieren, dass ein Transport von Partikelreihen mit hohen Geschwindigkeiten bei moderaten externen Magnetfeldern über den entwickelten Schichtsystemen möglich ist. Die Agglomeration der Partikel wird dabei intrinsisch vermieden. Diese Beobachtungen verdeutlichen die Vorzüge des DOWMAT-Mechanismus für biosensorische Anwendungen. Die präsentierten Untersuchungen bilden die Grundlage auf dem Weg zur Umsetzung neuer vielversprechender Biosensorkonzepte, die eine Schlüsselfunktion in der medizinischen point-of-care-Diagnostik bei der Detektion kleinster Konzentrationen krankheitsrelevanter Biomarker einnehmen können.