Raman hyperspectral imaging and analysis of fat spreads

被引:13
|
作者
van Dalen, G. [1 ]
van Velzen, E. J. J. [1 ]
Heussen, P. C. M. [1 ]
Sovago, M. [1 ]
van Malssen, K. F. [1 ]
van Duynhoven, J. P. M. [1 ,2 ]
机构
[1] Unilever R&D, Imaging & Spect, Olivier Noortlaan 120, NL-3133 AT Vlaardingen, Netherlands
[2] Wageningen Univ, Lab Biophys, Wageningen, Netherlands
关键词
confocal Raman imaging; fat spreads; emulsion; MCR-ALS; constraint; normalization; MULTIVARIATE CURVE RESOLUTION; ALTERNATING LEAST-SQUARES; SCANNING LASER MICROSCOPY; CRYSTAL NETWORKS; POLYMORPHIC FORMS; HARD CONSTRAINTS; FOOD RESEARCH; SPECTROSCOPY; IMAGES; CALIBRATION;
D O I
10.1002/jrs.5171
中图分类号
O433 [光谱学];
学科分类号
0703 ; 070302 ;
摘要
The microstructure of fat spreads is of fundamental importance to their sensorial properties such as texture, mouthfeel and spreadability. Fat spreads are water in oil emulsions, with a continuous phase supported by a fat crystal network. Confocal Raman microscopy offers the possibility for the spatialmapping of themicrostructure of fat spreads: It can distinguish the solid and liquid phases of the lipids and the emulsifiers present at the water-oil interface. A constraint multivariate curve resolution with an alternating least squares approach using a fixed set of pure component spectra is a suitable method to extract the spatial distribution information of each individual component present in the fat spread. A new normalization method provides semi-quantitative concentration maps, allowing good microstructural comparison. The technique was able to determine the spatial distribution of sunflower oil, water, emulsifier and solid fat in various investigated spreads. This method can be applied to a wide range of different food emulsions such as butter, margarine, mayonnaise and salad dressings. Copyright (C) 2017 John Wiley & Sons, Ltd.
引用
收藏
页码:1075 / 1084
页数:10
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