Product model systems approach to study thermomechanical effects on wheat starch and protein

C. DON (1), M. Thomas (2), A. Dubat (3)

(1) Foodphysica, Driel, Netherlands; (2) Zetadec B.V., Wageningen, Netherlands; (3) CHOPIN Technologies, Villeneuve-la-Garenne, France

Cereal Foods World 57:A14

A product model system can be a small scale “production” model of the actual final product, but also lab-scale mimics of thermal and mechanical processes which are the intermediate steps towards the final product belong to the product model systems tool-box. The combination of a relatively small scale of testing, thermal-mechanical information, analytical information (e.g., insoluble vs. soluble), and physical properties provides the industrial product developer with information that can be turned into a powerful predictive tool for physical product quality. In this study we used a variety of flours that are used for bread-making, biscuit, baked snacks (pretzel, cheeseflavoured “twists”), and pasta. Both starting materials and benchmark products have been tested in the so-called product model systems analytical toolbox. The lab-tests included Differential Scanning Calorimetry (DSC), Chopin Mixolab, Light Microscopy (LM), Viscometry, Glutenin-Macro- Polymer content, water swelling capacity, and starch damage. The Mixolab tests and DSC tests clearly demonstrated the effects of proteins, temperature, moisture addition, and moisture loss on rheological properties (dough viscosity), gelatinization, and glass-transition. The light microscopy survey revealed changes in the structure of the starch phase, disaggregated and aggregated protein structures. The level of observable retro-gradation can be related to processing conditions but also shows a link with the texture of the benchmark products. Clearly, several physico-chemical transitions are key to the final physical properties of the product (e.g., texture). Furthermore, small-scale tests are more easily repeated, conditions more easily altered, than pilot-tests performed on an industrial scale. Hence this reveals that a model systems approach is crucial to understand, better predict, and control physical product quality. 

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