Raman and Fourier transform infrared hyperspectral imaging to study dairy residues on different surface

Q3 Chemistry Journal of Spectral Imaging Pub Date : 2019-01-14 DOI:10.1255/JSI.2019.A3
V. Caponigro, F. Marini, R. Dorrepaal, A. Herrero-Langreo, A. Scannell, A. Gowen
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引用次数: 4

Abstract

Milk is a complex emulsion of fat and water with proteins (such as caseins and whey), vitamins, minerals and lactose dissolved within. The purpose of this study is to automatically distinguish different dairy residues on substrates commonly used in the food industry using hyperspectral imaging. Fourier transform infrared (FT-IR) and Raman hyperspectral imaging were compared as candidate techniques to achieve this goal. Aluminium and stainless-steel, types 304-2B and 316-2B, were chosen as surfaces due to their widespread use in food production. Spectra of dried samples of whole, skimmed, protein, butter milk and butter were compared. The spectroscopic information collected was not only affected by the chemical signal of the milk composition, but also by surface signals, evident as baseline and multiplicative effects. In addition, the combination of the spectral information with spatial information can improve data interpretation in terms of characterising spatial variability of the selected surfaces.
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利用拉曼和傅里叶变换红外高光谱成像技术研究不同表面上的乳制品残留物
牛奶是脂肪和水的复杂乳液,其中溶解有蛋白质(如酪蛋白和乳清)、维生素、矿物质和乳糖。本研究的目的是使用高光谱成像自动区分食品工业常用基质上的不同乳制品残留物。傅立叶变换红外(FT-IR)和拉曼高光谱成像作为实现这一目标的候选技术进行了比较。选择304-2B和316-2B型铝和不锈钢作为表面,是因为它们在食品生产中广泛使用。比较了全脂、脱脂、蛋白质、牛油牛奶和黄油的干燥样品的光谱。所收集的光谱信息不仅受到牛奶成分的化学信号的影响,还受到表面信号的影响。此外,光谱信息与空间信息的组合可以改善数据解释,同时表征所选表面的空间可变性。
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来源期刊
Journal of Spectral Imaging
Journal of Spectral Imaging Chemistry-Analytical Chemistry
CiteScore
3.90
自引率
0.00%
发文量
11
审稿时长
22 weeks
期刊介绍: JSI—Journal of Spectral Imaging is the first journal to bring together current research from the diverse research areas of spectral, hyperspectral and chemical imaging as well as related areas such as remote sensing, chemometrics, data mining and data handling for spectral image data. We believe all those working in Spectral Imaging can benefit from the knowledge of others even in widely different fields. We welcome original research papers, letters, review articles, tutorial papers, short communications and technical notes.
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