Issue 23, 2016

The rapid determination of total polyphenols content and antioxidant activity in Dendrobium officinale using near-infrared spectroscopy

Abstract

Despite their popularity and extensive use, some herbs have not been officially recognized in most countries. The main reason is the lack of comprehensive research data and methods. In this study, a rapid approach based on near-infrared spectroscopy (NIR) was developed for the determination of total polyphenols content (TPC) and antioxidant activity (AA) in Dendrobium officinale (D. officinale), an important Chinese herb. Adopting the Folin–Ciocalteu (FC) assay and 2,2-diphenyl-1-picrylhydrazyl radical (DPPH) free radical scavenging activity as the reference methods, TPC and AA in D. officinale samples (n = 83) collected from different locations in China were analyzed. The spectra generated by NIR were pretreated with different pre-processing methods and analyzed with the partial least-square (PLS) method. To obtain a robust and predictive quantitative model, competitive adaptive reweighted sampling (CARS) was applied to screen the key variables. The correlation coefficient of prediction (Rpre2) and root mean square error of prediction (RMSEP) by competitive adaptive reweighted sampling-partial least-square (CARS-PLS) were 0.8412 and 0.2905 for TPC and 0.9062 and 0.1028 for AA. The results show that the combination of NIR spectroscopy with CARS-PLS provides a rapid and precise alternative to existing chemical analysis for the determination of TPC and AA in D. officinale.

Graphical abstract: The rapid determination of total polyphenols content and antioxidant activity in Dendrobium officinale using near-infrared spectroscopy

Article information

Article type
Paper
Submitted
23 Feb 2016
Accepted
10 May 2016
First published
11 May 2016

Anal. Methods, 2016,8, 4584-4589

Author version available

The rapid determination of total polyphenols content and antioxidant activity in Dendrobium officinale using near-infrared spectroscopy

L. Ma, Z. Zhang, X. Zhao, S. Zhang and H. Lu, Anal. Methods, 2016, 8, 4584 DOI: 10.1039/C6AY00542J

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