Designing mesostructures for food functionality

We will discuss a few examples of the mutual couplings that exist between specific mesostructures (also typically present in foods) and their dispersing surrounding, and how these couplings across multiple scales dictate the mesostructural functionalities. Such a multi-scale dynamic approach is required in addressing processing, consumption and digestion of foods. We first consider the elasticity of a system consisting of fibrillar structures and discuss the contribution of a fibril to the elasticity as a function of the interaction with the surrounding fibrils (van der Linden and Parker 2005). Next we review how the surrounding of the fibril by means of its pH can affect the system robustness against phase separation, and how this can be altered by adding a surfactant like SDS (Jung, Savin et al. 2008; Kroes-Nijboer, Sawalha et al. 2012). We secondly consider a system of spherical assemblies of globular proteins and how the system’s structural evolution contributes to the elasticity. We discuss how this structural evolution can be influenced by altering the protein surrounding, yielding novel protein functionality (Sağlam, Venema et al. 2011). Finally we address the structural evolution of a more complex (mixed) system consisting of fibrillar and spherical mesostructures, and how multi-scale interdependences between these mesostructures and their surrounding are responsible for the functionality of each of the ingredients and of the overall complex system. We discuss our recent results on the stability emulsions that contain long semi-flexible structures that have a length equal to the diameter of the emulsions droplets. These recent results form an important extension of earlier work (Blijdenstein, Veerman et al. 2004). We also discuss our extensions to other sphere/fibril systems and point to an intricate issue on interpreting the stability of such systems. References: Blijdenstein, T. B. J., C. Veerman, et al. (2004). Depletion - flocculation in oil-in-water emulsions using fibrillar protein assemblies. Langmuir 20(12): 4881-4884. Jung, J. M., G. Savin, et al. (2008). Structure of heat-induced beta-lactoglobulin aggregates and their complexes with sodium-dodecyl sulfate. Biomacromolecules 9(9): 2477-2486. Kroes-Nijboer, A., H. Sawalha, et al. (2012). Stability of aqueous food grade fibrillar systems against pH change. Faraday Discussions 158: 125-138. Sağlam, D., P. Venema, et al. (2011). Preparation of high protein micro-particles using two-step emulsification. Food Hydrocolloids 25(5): 1139-1148. van der Linden, E. and A. Parker (2005). Elasticity due to semiflexible protein assemblies near the critical gel concentration and beyond. Langmuir 21(21): 9792-9794

The determinants of structural change in the European Union : a new application of RAS

The paper considers a (static) portfolio system that satisfies adding-up contraints and the gross substitution theorem. The paper shows the relationship of the two conditions to the weak dominant diagonal property of the matrix of interest rate elasticities. This enables to investigate the impact of simultaneous changes in interest rates on the asset demands.

Delivery of Functionality in Complex Food Systems: Physically Inspired Approaches from Nanoscale to Microscale, Wageningen 18–21 October 2009

The Wageningen Delivery of Functionality symposium covered all aspects involved with food structural design to arrive at high-quality foods which meet demanding customer expectations and regulatory requirements. The symposium integrated aspects from the structural organization of foods at molecular and supramolecular scales to dedicated techniques required to describe and visualize such structures, the gastro-intestinal events and how to model these in a laboratory setting, and finally the impact those food structures and ingredients have on the consumer’s physiology and on the human perception. As an interdisciplinary platform, bringing together more than 160 researchers from academia and industry, the symposium meanwhile fulfills an important role in the food science communit

Strengthening our grip on food security by encoding physics into AI

Climate change will jeopardize food security. Food security involves the robustness of the global agri-food system. This agri-food system is intricately connected to systems centering around health, economy, social-cultural diversity, and global political stability. A systematic way to determine acceptable interventions in the global agri-food systems involves analyses at different spatial and temporal scales. Such multi-scale analyses are common within physics. Unfortunately, physics alone is not sufficient. Machine learning techniques may aid. We focus on neural networks (NN) into which physics-based information is encoded (PeNN) and apply it to a sub-problem within the agri-food system. We show that the mean squared error of the PeNN is always smaller than that of the NNs, in the order of a factor of thousand. Furthermore, the PeNNs capture extra and interpolation very well, contrary to the NNs. It is shown that PeNNs need a much smaller data set size than the NNs to achieve a similar mse. Our results suggest that the incorporation of physics into neural networks architectures yields promise for addressing food security