4.6 Article Proceedings Paper

Adulteration screening of botanical materials by a sensitive and model-free approach using infrared spectroscopic imaging and two-dimensional correlation infrared spectroscopy

期刊

JOURNAL OF MOLECULAR STRUCTURE
卷 1124, 期 -, 页码 262-267

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.molstruc.2015.10.011

关键词

Food adulteration; Herbal adulteration; Quality control; Fourier transform infrared spectroscopy; Crocus sativus L.

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Infrared (IR) spectroscopy is often used as a simple, fast, and green method for the adulteration screening of botanical materials for foods and herbs. However, the overlapping of absorption signals of various substances significantly decrease the sensitivity and specificity of IR spectroscopy in the detection of adulterated samples. In this research, a model-free approach is proposed for the sensitive and non targeted screening of botanical materials adulterated by adding other plant materials. First, the spectra of the entities in the test sample are collected by near-infrared spectroscopic imaging and clustered by unsupervised pattern recognition methods. The sample may be adulterated if there are two or more clusters of the entities. Next, the entities of different clusters are characterized by mid-infrared spectroscopy to interpret the chemical compositions to determine the clustering is caused whether by adulteration or other reasons. Second derivative spectroscopy and two-dimensional correlation spectroscopy are often needed to resolve the overlapped bands mathematically or experimentally to find the characteristic signals to identify the authentic and adulterant entities. The feasibility of this approach was proved by the simulated adulterated sample of saffron. In conclusion, botanical materials adulterated by adding other plant materials can be detected by a simple, fast, sensitive, and green screening approach using IR spectroscopic imaging, two-dimensional correlation spectroscopy, and necessary chemometrics techniques. (C) 2015 Elsevier B.V. All rights reserved.

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