化学计量学
近红外光谱
光谱学
数学
色谱法
分析化学(期刊)
食品科学
化学
物理
光学
量子力学
作者
Dai-Xin Yu,Sheng Guo,Xia Zhang,Hui Yan,Zhenyu Zhang,Xin Chen,Jiang-yan Chen,Shan-jie Jin,Jian Yang,Jin‐Ao Duan
标识
DOI:10.1016/j.fochx.2022.100450
摘要
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.
科研通智能强力驱动
Strongly Powered by AbleSci AI