This study was conducted to evaluate the feasibility of using near-infrared spectroscopy (NIRS) for simultaneous determination of total phenolic content (TPC) and antioxidant properties of Siraitia grosvenorii, specifically 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulphonic… Click to show full abstract
This study was conducted to evaluate the feasibility of using near-infrared spectroscopy (NIRS) for simultaneous determination of total phenolic content (TPC) and antioxidant properties of Siraitia grosvenorii, specifically 2,2′-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid) (ABTS), ferric reducing antioxidant power (FRAP), and 2,2-diphenyl-1-picrylhydrazyl (DPPH). Partial least squares (PLS) coupled with wavelength selection was applied to develop NIRS calibration models based on a set of 80 samples. All models established were cross- and test set validated. The root mean square error of cross validation (RMSECV) and the coefficient of determination for cross validation Rcv2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\left( {{\text{R}}_{{{\text{cv}}}}^{2} } \right) $$\end{document} were calculated to evaluate the performance of models. The results showed good precision of models for TPC (Rcv2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{R}}_{{{\text{cv}}}}^{2}$$\end{document} = 0.9829, RMSECV = 0.0426), DPPH (Rcv2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{R}}_{{{\text{cv}}}}^{2}$$\end{document} = 0.9477, RMSECV = 0.0279), ABTS (Rcv2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{R}}_{{{\text{cv}}}}^{2}$$\end{document} = 0.8958, RMSECV = 0.0154), and FRAP (Rcv2\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{R}}_{{{\text{cv}}}}^{2}$$\end{document} = 0.9137, RMSECV = 0.0176). In addition, 20 unknown samples were used to evaluate the predictive ability of the obtained models, and the ratio performance deviation (RPD) for TPC, ABTS, DPPH, and FRAP ranged from 2.70 to 4.57, which indicate that these models had acceptable predictive ability. These results demonstrated that NIRS has the potential to be a time saving and cost-effective method for the determination of both TPC and antioxidant capacities of Siraitia grosvenorii.
               
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