期刊
FOOD RESEARCH INTERNATIONAL
卷 40, 期 9, 页码 1129-1139出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/j.foodres.2007.06.008
关键词
in-line monitoring; color measurement; food extrusion; neural networks correlation; CIELAB colour space; spectrometer sensitivity
During food extrusion the degree of cooking and the quantity of expensive colorants used, both influence colour and the aesthetic appeal of the product. Thus, the use of a fiber optic equipped spectrophotometer for colour monitoring inside the extruder holds great potential for product characterization and effective quality control. However, this approach presents two difficulties: (1) inadequate sensitivity of the spectrophotometer to dark colours; and (2) the need to correlate the colour monitored inside the extruder (in-line) with that of the final product (off-line). In this paper, a method of spectrophotometer calibration, termed the virtual white reference, is shown to overcome the sensitivity and reproducibility problems related to dark-colour measurements. In addition, to predict the final-product colour based on in-line measurements, different artificial neural networks were tested. A multilayer feedforward network with three hidden neurons provided an acceptable correlation between the in-line and off-line colour measurements. (c) 2007 Elsevier Ltd. All rights reserved.
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