A novel simultaneous quantitative method for differential volatile components in herbs based on combined near-infrared and mid-infrared spectroscopy

被引:12
|
作者
Fan, Yao [2 ]
Bai, Xiuyun [1 ]
Chen, Hengye [1 ]
Yang, Xiaolong [1 ]
Yang, Jian [3 ]
She, Yuanbin [2 ]
Fu, Haiyan [1 ]
机构
[1] South Cent Minzu Univ, Coll Pharm, Modernizat Engn Technol Res Ctr Ethn Minor Med Hub, Wuhan 430074, Peoples R China
[2] Zhejiang Univ Technol, Coll Chem Engn, Hangzhou 310032, Peoples R China
[3] China Acad Chinese Med Sci, Natl Resource Ctr Chinese Mat Med, State Key Lab Breeding Base Dao di Herbs, Beijing 100700, Peoples R China
基金
国家重点研发计划; 欧盟地平线“2020”; 中国国家自然科学基金;
关键词
Herbs; NIR-MIR; Differential volatile components; Simultaneous quantitative analysis; Chemometrics; MEDICINAL HERBS; SPICES; AUTHENTICATION; RAMAN;
D O I
10.1016/j.foodchem.2022.135096
中图分类号
O69 [应用化学];
学科分类号
081704 ;
摘要
A novel method based on GC-MS, near-infrared (NIR) and mid-infrared (MIR) spectroscopy combined with chemometrics was established to simultaneously analyze differential volatile components (DVCs) of herb sam-ples. Herein, Florists Chrysanthemum was adopted as the representative sample. Through the introduction of Automatic data analysis workflow (AntDAS) and one-class partial least squares discriminant analysis (O-PLSDA) model, five kinds of terpenes and five kinds of alcohols were efficiently screened as DVCs. By using the selected NIR-MIR spectra sections combined with O-PLSDA, it could achieve the accurate identification of Florists Chry-santhemum from Chrysanthemum morifolium Ramat. What's more, since the selected spectra sections were closely related to the structural and content of DVCs, they could be further used for simultaneous quantitative analysis of DVCs combined with optimized variable-weighted least-squares support vector machine based on particle swarm optimization (PSO-VWLS-SVM). This method only adopted the same NIR-MIR sections for multiple component accurate quantification, highlighting its convenience.
引用
收藏
页数:7
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