Near-infrared spectroscopy for rapid and simultaneous determination of five main active components in rhubarb of different geographical origins and processing

• Published in: Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy Vol. 205; pp. 419 - 427
• Main Authors: Jintao, Xue, Yongli, Shi, Liming, Ye, Quanwei, Yang, Chunyan, Li, Xingyi, Chen, Yun, Jing
• Format: Journal Article
• Language: English
• Published: England Elsevier B.V 05.12.2018
• Subjects: Artificial neural networks; China; Geographical region; Least-Squares Analysis; Linear Models; Near-infrared spectroscopy; Neural Networks (Computer); Partial least squares; Plant Extracts - analysis; Plant Extracts - chemistry; Processing; Reproducibility of Results; Rheum - chemistry; Rhubarb; Spectroscopy, Near-Infrared - methods; ANN; RMSEP; GFF; Geographical region; RPD; S-G; BP-MLP; Near-infrared spectroscopy; Processing; RMSECV; R; TLRN; PLS; RBF; COE; NIRS; Rcal; SLS; Rhubarb; MSC; Partial least squares; 1st D; MSE; Artificial neural networks; LVs; MMN; Rpre; 2nd D; VN; RN; TCM
• ISSN: 1386-1425; 1873-3557
• DOI: 10.1016/j.saa.2018.07.055

Rhubarb (Rhei Radix et Rhizoma) is a classic herbal laxative medicine in Europe and a very famous natural medicine in Asia, especially in China. In this study, near-infrared spectroscopy (NIRS) was first used for rapid and simultaneous analysis of five main active components (chrysophanol, aloe-emodin, rhein, emodin and physcion) in rhubarb of 6 geographical origins, processing and spurious samples. A total of 124 samples (73 raw, 40 processed and 11 spurious samples) were collected. With the reference values determined by HPLC, two calibration strategies, partial least squares (PLS) as a linear regression method and artificial neural networks (ANN) as a non-linear regression method, were studied. For the PLS strategy, 11 spectral pre-processing methods, 5 spectral regions and different latent variables (LVs) were systematically compared, while 3 spectral pre-processing methods and 5 ANN algorithms were studied for the ANN strategy. The results indicated that PLS was more suitable for the analysis of chrysophanol, aloe-emodin, emodin and physcion, whereas ANN was better for rhein. For the optimal NIR models of chrysophanol, aloe-emodin, rhein, emodin and physcion, the correlation coefficients of the calibration set (Rcal) were 0.9916, 0.9762, 0.9839, 0.9794 and 0.9800, respectively; the correlation coefficients of the prediction set (Rpre) were 0.9888, 0.9359, 0.9410, 0.9805 and 0.9785, respectively; the root mean square error of validation (RMSEP) were 0.0402, 0.0197, 0.0593, 0.0133 and 0.0192, respectively. Subsequently, the optimal NIR models were used to study the effects of geographical regions and processing, and identify the spurious rhubarb. Collectively, NIRS may be a well-acceptable method for quality evaluation of rhubarb and other traditional Chinese medicine (TCM). [Display omitted] •Raw, processed and spurious rhubarb was studied by near-infrared spectroscopy.•A fast and nondestructive method was used for simultaneous analysis 5 components.•Two different multivariate strategies (PLS and ANN) were compared.•The effect of processing and geographical regions was analyzed and compared.•Official and unofficial rhubarb was studied by near-infrared spectroscopy.