A Metabolomics Coupled With Chemometrics Strategy to Filter Combinatorial Discriminatory Quality Markers of Crude and Salt-Fired Eucommiae Cortex

Abstract

Eucommiae Cortex is commonly used for treating various diseases in a form of the crude and salt-fired products. Generally, it is empirical to distinguish the difference between two types of Eucommiae Cortex. The metabolomics coupled with chemometrics strategy was proposed to filter the combinatorial discriminatory quality markers for precise distinction and further quality control of the crude and salt-fired Eucommiae Cortex. The metabolomics data of multiple batches of Eucommiae Cortex samples was obtained by ultra-high performance liquid chromatography coupled with mass spectrometry (UHPLC-MS). Orthogonal partial least-squares discriminant analysis was utilized to filter candidate markers for characterizing the obvious difference of the crude and salt-fired Eucommiae Cortex. The accuracy of combinatorial markers was validated by random forest and partial least squares regression. Finally, eleven combinatorial discriminatory quality markers from 67 identified compounds were rapidly screened, identified, and determined for distinguishing the difference between crude and salt-fired Eucommiae Cortex. It was demonstrated that UHPLC-MS based metabolomics with chemometrics was a powerful strategy to screen the combinatorial discriminatory quality markers for distinguishing the crude and salt-fired Eucommiae Cortex and to provide the reference for precise quality control of Eucommiae Cortex.

Comparison of the chemical profile differences of Aster tataricus between raw and processed products by metabolomics coupled with chemometrics methods

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Exploration of Habitat-Related Chemical Markers for Stephania tetrandra Applying Multiple Chromatographic and Chemometric Analysis

“…It is well accepted that medicinal herbs exert their efficacies through synergistic actions via “multi-components hitting multi-targets” of complex chemicals in the herbs [ 6 , 7 ], and integrating multiple methods simultaneously characterizing different kinds of components has been employed as a comprehensive strategy to evaluate the holistic quality, thus assure the efficacy of medicinal herbs [ 8 ]. Moreover, chemometrics provides a variety of good algorithms to explore and obtain more valuable chemical information [ 9 , 10 , 11 , 12 , 13 , 14 , 15 ]. Among these, discriminatory analysis is an effective tool for accurate prediction according to various characteristic values.…”