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Updated: Jul 25, 2026

Quantifying Mixing using Magnetic Resonance Imaging
Published on: January 25, 2012
Applications of magnetic resonance imaging to food research
1Department of Food Science and Technology, University of California, Davis 95616-8598, USA.
Abstract:
Global food markets are changing in response to consumer demands for more processed foods and higher quality foods. Consumers find processed foods convenient, less prone to spoilage, more portable, nutritionally efficient, and more consistent in quality level than fresh foods. These demands have resulted in food producers working to develop new types of foods and reformulate standard types of foods. A typical type of reformulation would be a reduced-calorie food or an all-natural food product. The characterization of food processes and products is most often accomplished through the use of averaged measurements. An averaged measurement provides a characterization of the process or product with a single value of one variable measured at a specific time. For example, the average moisture content of a food during drying or the shear viscosity of an emulsion at one temperature and one shear rate. Averaged measurements are useful in characterizing a given process and are in many cases sufficient for process design or product development. However, these single point measurements do not provide significant information on the phenomena responsible for controlling product properties during processing or storage. More information on the physical and chemical processes controlling or influencing process performance and product quality should result in both improved production efficiency, improved product quality, and novel products. Magnetic resonance imaging provides new methods and approaches to investigate and quantify the attributes of products as they vary in time and location within the product. The attributes that can be quantified range from the composition of a material (moisture content, fat content), to physical structure and to derived characterizations like the shear-stress shear-rate relationship in fluids.
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