量子级联激光光声光谱在米粉分析中的应用

A. Puiu, L. Fiorani, G. Giubileo, A. Lai, S. Mannori, W. R. Saleh
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引用次数: 2

摘要

本文将激光光声光谱技术应用于食品样品的分析。我们特别分析了不同的米粉样品(标准米粉和商用米粉)。为此,研制了基于量子级联激光器(QCL)的实验室系统并对其进行了表征。之后,收集所有水稻样品的LPAS光谱,标准误差小于实测值的2%,背景信号与样品信号相比可以忽略不计。所有实验LPAS光谱都具有丰富的光谱特征,且光谱特征之间存在明显差异。然后将实验光谱与我们实验室记录的FT-IR跃迁频率进行比较,以同意适当的分配。最后,为了证明不同水稻类型之间的微小差异,对记录的LPAS光谱进行了主成分分析(PCA),突出了5种不同类型样品对应的5个不同组。综上所述,本研究证明了LPAS技术对不同类型米粉样品的鉴别能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantum Cascade Laser Photoacoustic Spectroscopy Applied to Rice Flour Analysis
In the present work we applied laser photoacoustic spectroscopy (LPAS) to the analysis of food samples. In particular, we analyzed samples of different rice flours (standard and commercial ones). For this purpose, a laboratory system based on quantum cascade laser (QCL) has been developed and characterized. After that, the LPAS spectra of all the rice samples were collected with a standard error of less than 2% of the measured value and a background signal negligible compared to the sample signals. All the experimental LPAS spectra resulted to be rich in spectral features showing clear differences between each other. The experimental spectra were then analyzed by comparison with the FT-IR transition frequency recorded in our laboratory to consent a proper assignment. Finally, to put in evidence the small differences among the various rice types, the Principal Component Analysis (PCA) was applied to the recorded LPAS spectra highlighting five different groups corresponding to the five types of samples. In conclusion, the present work demonstrated the discriminating capability of LPAS technique in the case of different types of rice flour samples.
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