E: FOOD ENGINEERING AND PHYSICAL PROPERTIES
Indirect Color Prediction of Amorphous Carbohydrate Melts as a Function of Thermal History
Article first published online: 22 MAY 2013
© 2013 Institute of Food Technologists®
Journal of Food Science
Volume 78, Issue 7, pages E1022–E1028, July 2013
How to Cite
van Sleeuwen, R. M. T., Gosse, A. J. and Normand, V. (2013), Indirect Color Prediction of Amorphous Carbohydrate Melts as a Function of Thermal History. Journal of Food Science, 78: E1022–E1028. doi: 10.1111/1750-3841.12153
- Issue published online: 18 JUL 2013
- Article first published online: 22 MAY 2013
- Manuscript Accepted: 6 APR 2013
- Manuscript Received: 14 DEC 2012
- heat treatment;
- predictive modeling
Glassy carbohydrate microcapsules are widely used for the encapsulation of flavors in food applications, and are made using various thermal processes (for example, extrusion). During manufacturing, these carbohydrate melts are held at elevated temperatures and color can form due to nonenzymatic browning reactions. These reactions can negatively or positively affect the color and flavor of microcapsules. The rate of color formation of maltodextrin and maltodextrin/sucrose melts at elevated temperatures was determined spectrophotometrically and was found to follow pseudo zero-order kinetics. The effect of temperature was adequately modeled by an Arrhenius relationship. Reaction rate constants and Arrhenius parameters were determined for individual wavelengths in the visible range (360 to 700 nm at 1 nm intervals). Transient processes (temperature changes with time) were modeled as a sequence of small isothermal events, and the equivalent thermal history at a reference temperature calculated using the Arrhenius relationship. Therefore, spectral transmittance curves could be predicted with knowledge of the time/temperature relationship. Validation was conducted by subjecting both melts to a transient thermal history. Experimental transmittance spectrum compared favorably against predicted values. These spectra were optionally converted to any desirable color space (for example, CIELAB, XYZ, RGB) or derived parameter (for example, Browning Index). The tool could be used to better control nonenzymatic browning reactions in industrial food processes.
Excessive nonenzymatic browning during thermal processing of carbohydrates in food or food ingredients can lead to out-of-specification products. In-process measurement and prediction of color is important to quickly detect or foresee product deviations and reduce losses. Flavor microcapsules are examples of carbohydrate-based ingredients that often need to provide visual appeal in food products (for example, colorants may be added). Browning reactions may not only lead to a brown appearance, but can give a change in color (for example, blue to green). The approach detailed in this article allows for such color changes to be predicted.