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Automatisierte Fahrfunktionen haben sich fest in der Automobilindustrie etabliert. Insbesondere Einparkvorgänge lassen sich aufgrund der geringen Geschwindigkeiten und des vergleichsweise kleinen Betriebsraums sehr gut automatisieren. Um von den Insassen akzeptiert zu werden, muss eine Pkw-Parkfunktion jedoch souverän und mindestens so schnell agieren wie der Mensch. IPG Automotive, die Hochschule Kempten und MdynamiX zeigen, wie die eigenentwickelte Vehicle-in-the-Loop-Methode die durchgängige Bewertung automatisierter Fahrfunktionen unterstützen kann.
Obesity is one of the major challenges of modern societies. The food industry is under increasing pressure from government and the consumer side to reformulate foods to reduce the fat, sugar and salt content. However, if fat or sugar is reduced the overall flavor perception of the food is changed. In the case of fat reduction these changes are caused by a different aroma release during in mouth processing.
Additionally the texture is perceived as less creamy. It was recently found that aeration can increase aroma release and change texture perception in terms of creaminess.
The goal of this work is to study both effects in perspective of fat reduction in fermented dairy products.
Various mathematical models will be used to understand and describe the different effects involved. Since temperature is a critical parameter for aroma release and foam stability, heat transfer into a simplified mouth model for aroma release analysis was studied using the finite element method. In a second step the aroma release during foam collapse will be modelled and validated by aroma analysis data. In the last step the model linking the sensory perception of creaminess to the physical parameters of the foam (friction coefficient, viscosity, bubble size distribution) and the chemical attributes of the aroma substance (hydrophobicity, volatility) will be shown.
The findings from this work, both from the effect of aeration and the methodological approach may be transferred to other food categories as well.
Fat reduction is a major challenge for food manufacturers, because the desired calorie reduction goes along with a different aroma perception of low-fat products. To compensate for these changes, this work investigated the effect of foaming on aroma release from a fat-free dairy matrix. A mouth model and an analytical method based on HS-SPME-GC-IMS were designed and validated to quantify dynamic aroma release during thermally induced foam collapse. It was demonstrated that foaming significantly changes the release of aroma compounds. Depending on the hydrophobicity of the aroma substance, release was either increased or decreased after the inclusion of a gas phase.
Since aeration can increase aroma perception, it may be used to compensate the perceived aroma loss of low-fat dairy products. To be able to study the effect of aeration on aroma release systematically in the future, a temperature study was conducted on an in vitro model built to study aroma release at temperatures relevant for oral processing. The studied dairy foam contained 4% (w/w) milk protein and 0.75% (w/w) alginate and had a gas volume fraction of 71% after whipping. The temperature development during incubation of the foam at 40 °C was calculated using a numeric simulation. Thermal equilibrium was reached after 50 min. Sampling for dynamic aroma release was found to be ideal at 2, 7 and 15 min, because mean foam temperatures were 25, 30 and 35 °C. Experimental temperature analysis of the foam core was in good agreement with the simulation (R2 = 0.95).
When we are trying to decrease caloric intake by reducing fat content, aroma perception of the food is changed as well. Since previous studies indicated that foaming changes the aroma release, it was our goal to understand the physico-chemical background of this effect. Therefore, ten aroma compounds were added to a foamed acidified dairy matrix (4% milk protein, 1% gelatin, 60% gas volume). We simulated oral temperature conditions in a simplistic way through incubation at 40 °C and analyzed aroma release using headspace-solid phase microextraction-gas chromatography-ion mobility spectrometry. Significantly more highly hydrophobic aroma compounds were released from the foamed matrix than the unfoamed matrix, while compounds of intermediate hydrophobicity were released more from unfoamed matrix. The effect was independent from foam collapse and persisted for hours afterwards. Analytical results were complemented by orthonasal and retronasal sensory perception studies, which confirmed significant differences between aroma release behavior from foamed foods.
The production of food is highly complex due to the various chemo-physical and biological processes that must be controlled for transforming ingredients into final products. Further, production processes must be adapted to the variability of the ingredients, e.g., due to seasonal fluctuations of raw material quality. Digital twins are known from Industry 4.0 as a method to model, simulate, and optimize processes. In this vision paper, we describe the concept of a digital food twin. Due to the variability of the raw materials, such a digital twin has to take into account not only the processing steps but also the chemical, physical, or microbiological properties that change the food independently from the processing. We propose a hybrid modeling approach, which integrates the traditional approach of food process modeling and simulation of the bio-chemical and physical properties with a data-driven approach based on the application of machine learning. This work presents a conceptual framework for our digital twin concept based on explainable artificial intelligence and wearable technology. We discuss the potential in four case studies and derive open research challenges.
To understand aroma perception from complex food matrices‚ determination of dynamic aroma release during simulated oral processing is necessary. In this study optimization, validation and application of a novel method coupling headspace-solid phase microextraction (HS-SPME) with gas chromatography-ion mobility spectrometry (GC-IMS) is presented. Thirteen character impact compounds imparting different chemical properties are studied to understand capabilities and limitations of the method. It was shown for the first time that the temperature of the IMS sample inlet can be increased up to 200 °C without instrumental constraints. Linear calibration was possible for eleven of the thirteen compounds with one decade dynamic range. The limit of detection and quantitation were 2.1–63.0 ppb and 7.2–210.1 ppb, respectively. Diacetyl could be detected in negative polarity mode of IMS, however with lower precision compared to the compounds detected in positive mode. Limitations of the method were short HS-SPME extraction time, which in the case of caproic acid was not sufficient for reliable quantification. Additionally, δ-decalactone could not be detected due to maximum GC temperature of 200 °C. Application of the method to determine dynamic aroma release from a dairy matrix was successfully shown for nine compounds. Analysis of complex food matrix was performed with similar precision compared to analysis in aqueous solution, thus proving high robustness of the method towards matrix effects.
Eine Vielzahl von Produkten in den Supermarktregalen basiert auf Milch als Ausgangsprodukt. Dabei finden unterschiedliche Aufbereitungen der Rohmilch Anwendung. Der wohl wichtigste Prozess hierbei ist die Homogenisierung, welche vorrangig für die Stabilität des Produktes wichtig ist. An genau diesem Punkt kommt die Analyse der Partikelgröße ins Spiel.
Tensile properties of 2D braid reinforced composites are analyzed with regards to process-induced fiber architecture variations. First, a parametric study concerning the effect of radial braiding parameters on the braid characteristics is performed and a quantitative quality index based on visual attributes is introduced. Second, test laminates are produced with vacuum resin infusion to conduct tensile tests with biaxial and triaxial braids of varying qualities. To correlate fiber architecture variations with mechanical properties, each braided layer is scanned and analyzed by means of gray scale based image processing. This allows for determining specimen-specific fiber orientations and correlating them with mechanical properties. The results show strong correlations of measured fiber architectures and mechanical properties. Thus, the study suggests that detailed information about the (local) fiber architecture should allow for significantly improving the prediction of 2D braided composite properties.
This paper provides an approach for controlling the level of risk when operating highly automated transportation systems like cars, trains and similar. Such systems replace human perception and decision-making by employing highly sophisticated solutions based on electronics, IT, and AI. Such systems have demonstrated the potential for building highly automated vehicles, but, as of today, encounter challenges in correctly understanding the extremely complex open contexts, into which such vehicles could be deployed. Its key focus is on bounding the risks stemming from uncertainty in the perception of the environment.