Rapid detection of adulteration in powder of ginger (Zingiber officinale Roscoe) by FT-NIR spectroscopy combined with chemometrics

Dai-Xin Yu; Sheng Guo; Xia Zhang; Hui Yan; Zhen-Yu Zhang; Xin Chen; Jiang-Yan Chen; Shan-Jie Jin; Jian Yang; Jin-Ao Duan

doi:10.1016/j.fochx.2022.100450

Rapid detection of adulteration in powder of ginger (Zingiber officinale Roscoe) by FT-NIR spectroscopy combined with chemometrics

Food Chem X. 2022 Sep 17:15:100450. doi: 10.1016/j.fochx.2022.100450. eCollection 2022 Oct 30.

Authors

Dai-Xin Yu¹, Sheng Guo¹, Xia Zhang², Hui Yan¹, Zhen-Yu Zhang¹, Xin Chen¹, Jiang-Yan Chen¹, Shan-Jie Jin², Jian Yang³, Jin-Ao Duan¹

Affiliations

¹ National and Local Collaborative Engineering Center of Chinese Medicinal Resources Industrialization and Formulae Innovative Medicine, Jiangsu Collaborative Innovation Center of Chinese Medicinal Resources Industrialization, Nanjing University of Chinese Medicine, Nanjing 210023, China.
² College of Artificial Intelligence and Information Technology, Nanjing University of Chinese Medicine, Nanjing 210023, China.
³ State Key Laboratory of Dao-di Herbs Breeding Base, National Resource Center for Chinese Materia Medica, China Academy of Chinese Medical Sciences, Beijing 100700, China.

Abstract

Ginger powder (GP) is a popular spice in the world. Duo to its nutritional value, GP is regarded as an attractive target for adulteration, which is not easily detected. In this study, chromaticity analysis and Fourier transform near-infrared (FT-NIR) spectroscopy combined with chemometrics were developed to identify and quantify of GP and its adulterants. The result showed that GPs and adulterated GPs cannot be completely distinguished by chromaticity analysis. While, the optimized NIR spectra could accurately distinguish the authentic GPs from those adulterated samples. Random forest and gradient boosting algorithms exhibited the highest accuracies (100%) in classification. Moreover, a quantitative model was successfully established to predict the adulteration level in GP. The optimal parameters of prediction to deviation were 8.92, 13.68, 14.61, and 4.30, for pure and adulterated GPs. Overall, FT-NIR spectroscopy is a promising tool, which can quickly identify potential adulteration in GP and track the types of adulterants.

Keywords: Adulteration; Chemometrics; Ginger powder; NIR spectroscopy; Quantitative analysis.