Abstract

A quantitative near infrared diffuse reflectance spectroscopy method was established for the simultaneous determination of three flavonol aglycones (quercetin, kaempferol and isorhamnetin) in Ginkgo biloba leaf extracts. Partial leat squares was applied to build the correlation models with the pre-processing methods of first derivative and multiplicative scatter correction. A moving window partial least squares method was used for variable selection. Satisfactory calibration statistics were obtained for quercetin, kaempferol and isorhamnetin with coefficients of determination 0.94, 0.90, 0.88; and root mean square error of cross-validation / prediction of 0.61 / 0.48, 0.80 / 0.94, 0.28 / 0.30, respectively. This method demonstrates the great potential of NIR spectroscopy as a non-destructive and efficient tool for quality control of Ginkgo biloba leaf extracts manufacture.

© 2008 IM Publications LLP

Optical system for tablet variety discrimination using visible/near-infrared spectroscopy

Yongni Shao, Yong He, and Xingyue Hu
Appl. Opt. 46(34) 8379-8384 (2007)

Partial least squares regression calculation for quantitative analysis of metals submerged in water measured using laser-induced breakdown spectroscopy

Tomoko Takahashi, Blair Thornton, Takumi Sato, Toshihiko Ohki, Koichi Ohki, and Tetsuo Sakka
Appl. Opt. 57(20) 5872-5883 (2018)

Wavelength selection of terahertz time-domain spectroscopy based on a partial least squares model for quantitative analysis

Qingxiao Ma, Chun Li, Biao Wang, Xin Ma, and Ling Jiang
Appl. Opt. 60(19) 5638-5642 (2021)

Acidity measurement of iron ore powders using laser-induced breakdown spectroscopy with partial least squares regression

Z.Q. Hao, C.M. Li, M. Shen, X.Y. Yang, K.H. Li, L.B. Guo, X.Y. Li, Y.F. Lu, and X.Y. Zeng
Opt. Express 23(6) 7795-7801 (2015)

Multiple kinds of pesticide residue detection using fluorescence spectroscopy combined with partial least-squares models

Rendong Ji, Shicai Ma, Hua Yao, Yue Han, Xiao Yang, Ruiqiang Chen, Yinshang Yu, Xiaoyan Wang, Dongyang Zhang, TieZhu Zhu, and Haiyi Bian
Appl. Opt. 59(6) 1524-1528 (2020)