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

机译:拉曼和傅立叶变换红外高光谱成像可研究不同表面上的乳制品残留

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Author Summary: 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.
机译:作者摘要:牛奶是脂肪和水与溶解在其中的蛋白质(例如酪蛋白和乳清),维生素,矿物质和乳糖形成的复杂乳液。这项研究的目的是使用高光谱成像技术自动区分食品工业中常用的基质上的不同乳制品残留。比较了傅立叶变换红外(FT-IR)和拉曼高光谱成像作为实现此目标的候选技术。 304-2B和316-2B型铝和不锈钢由于在食品生产中的广泛应用而被选为表面。比较了全脂,脱脂,蛋白质,黄油,牛奶和黄油的干燥样品的光谱。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,这些信号表现为基线和乘法效应。另外,光谱信息与空间信息的组合可以在表征所选表面的空间变异性方面改善数据解释。

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