Nondestructive detection of lead chrome green in tea by Raman spectroscopy

Raman spectroscopy was first adopted for rapid detecting a hazardous substance of lead chrome green in tea, which was illegally added to tea to disguise as high-quality. 160 samples of tea infusion with different concentrations of lead chrome green were prepared for Raman spectra acquirement in the range of 2804 cm−1–230 cm−1 and the spectral intensities were calibrated with relative intensity standards. Then wavelet transformation (WT) was adopted to extract information in different time and frequency domains from Raman spectra, and the low-frequency approximation signal (ca4) was proved as the most important information for establishment of lead chrome green measurement model, and the corresponding partial least squares (PLS) regression model obtained good performance in prediction with Rp and RMSEP of 0.936 and 0.803, respectively. To further explore the important wavenumbers closely related to lead chrome green, successive projections algorithm (SPA) was proposed. Finally, 8 characteristic wavenumbers closely related to lead chrome green were obtained and a more convenient and fast model was also developed. These results proved the feasibility of Raman spectroscopy for nondestructive detection of lead chrome green in tea quality control.

[1]  Jia Hong-liang.  Analysis on factors affecting colorimeter measurement accuracy in meat color determination , 2012 .

[2]  M. Mantler,et al.  A comparative analysis of five chrome green pigments based on different spectroscopic techniques , 2003 .

[3]  Yong He,et al.  Characterizing the Moisture Content of Tea with Diffuse Reflectance Spectroscopy Using Wavelet Transform and Multivariate Analysis , 2012, Sensors.

[4]  Ingrid Daubechies,et al.  The wavelet transform, time-frequency localization and signal analysis , 1990, IEEE Trans. Inf. Theory.

[5]  W. Cai,et al.  Multiblock partial least squares regression based on wavelet transform for quantitative analysis of near infrared spectra , 2010 .

[6]  Xueguang Shao,et al.  Wavelet unfolded partial least squares for near-infrared spectral quantitative analysis of blood and tobacco powder samples. , 2011, The Analyst.

[7]  Yan-de Liu,et al.  [Analysis of chlorophyll in Gannan navel orange with algorithm of GA and SPA based on hyperspectral]. , 2012, Guang pu xue yu guang pu fen xi = Guang pu.

[8]  S. Wold,et al.  The Collinearity Problem in Linear Regression. The Partial Least Squares (PLS) Approach to Generalized Inverses , 1984 .

[9]  Di Wu,et al.  Colour measurements by computer vision for food quality control – A review , 2013 .

[10]  Joseph Irudayaraj,et al.  A SERS DNAzyme biosensor for lead ion detection. , 2011, Chemical communications.

[11]  C. Frausto-Reyes,et al.  Raman spectroscopy for the identification of pigments and color measurement in Dugès watercolors. , 2009, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[12]  Richard R. Hark,et al.  Spectroscopic investigation of modern pigments on purportedly medieval miniatures by the ‘Spanish Forger’ , 2009 .

[13]  N. Ly,et al.  A submicromolar Cr(III) sensor with a complex of methionine using gold nanoparticles , 2015 .

[14]  Jinwook Lee,et al.  Lipophilic pigments differentially respond to drying methods in tea (Camellia sinensis L.) leaves , 2015 .

[15]  Li Zhao,et al.  A model predictive control approach with relevant identification in dynamic PLS framework , 2014 .

[16]  Hongfei Cheng,et al.  Raman spectroscopy of coal component of Late Permian coals from Southern China. , 2014, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[17]  P. Larkin,et al.  General Outline and Strategies for IR and Raman Spectral Interpretation , 2011 .

[18]  Y. Ozaki,et al.  Semiconductor-driven “turn-off” surface-enhanced Raman scattering spectroscopy: application in selective determination of chromium(vi) in water , 2014, Chemical science.

[19]  Howell G. M. Edwards,et al.  Raman spectroscopic database of azo pigments and application to modern art studies , 2000 .

[20]  Yong Wang,et al.  Chemical/Molecular Structure of the Dentin–Enamel Junction is Dependent on the Intratooth Location , 2009, Calcified Tissue International.

[21]  Alexander Kai-man Leung,et al.  Application of wavelet transform in infrared spectrometry: spectral compression and library search , 1998 .

[22]  J. Madariaga,et al.  Finnish wallpaper pigments in the 18th-19th century: presence of KFe3(CrO4)2(OH)6 and odd pigment mixtures. , 2013, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[23]  B. Kowalski,et al.  Partial least-squares regression: a tutorial , 1986 .

[24]  Victor I. Mikla,et al.  Raman Spectroscopy in Medicine , 2014 .

[25]  Mallat Stéphane.  CHAPTER 7 – Wavelet Bases , 2009 .

[26]  K. Yong,et al.  A Review on Functionalized Gold Nanoparticles for Biosensing Applications , 2011 .

[27]  Yun Zhang,et al.  Micro-Raman observation on the H2PO4(-) association structures in a supersaturated droplet of potassium dihydrogen phosphate (KH2PO4). , 2013, The Journal of chemical physics.

[28]  Peter Willett,et al.  What is a tutorial , 2013 .

[29]  Zoltan K. Nagy,et al.  Application of quantitative Raman spectroscopy for the monitoring of polymorphic transformation in crystallization processes using a good calibration practice procedure , 2014 .

[30]  P. Holakooei,et al.  Micro-Raman spectroscopy and X-ray fluorescence spectrometry on the characterization of the Persian pigments used in the pre-seventeenth century wall paintings of Masjid-i Jāme of Abarqū, central Iran. , 2015, Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy.

[31]  Fernando Agulló-Rueda,et al.  Raman spectroscopy analysis of pigments on Diego Velázquez paintings , 2013 .

[32]  S. N. White,et al.  Development of a laser Raman spectrometer for deep-ocean science , 2004 .

[33]  Yidan Bao,et al.  Rapid prediction of moisture content of dehydrated prawns using online hyperspectral imaging system. , 2012, Analytica chimica acta.

[34]  Na Li,et al.  Color and chemical stability of tea polyphenol (−)-epigallocatechin-3-gallate in solution and solid states , 2013 .

[35]  Di Wu,et al.  Determination of alpha-linolenic acid and linoleic acid in edible oils using near-infrared spectroscopy improved by wavelet transform and uninformative variable elimination. , 2009, Analytica chimica acta.

[36]  M. C. U. Araújo,et al.  The successive projections algorithm for variable selection in spectroscopic multicomponent analysis , 2001 .

[37]  Anthony Turner,et al.  Proceedings of the Society of Photo-Optical Instrumentation Engineers , 2004 .

[38]  S. Mallat.  A wavelet tour of signal processing , 1998 .

[39]  C. Zhang,et al.  Influence of absorption on quantitative analysis in Raman spectroscopy , 2006 .

[40]  S. Bi,et al.  DFT studies of Al–O Raman vibrational frequencies for aquated aluminium species , 2010 .