Profiling complex volatile components by HS-GC-MS and entropy minimization software: An example on Ligusticum...

Area of Science:

• Phytochemistry
• Analytical Chemistry
• Chemometrics

Background:

• Volatile oils in medicinal herbs contain diverse bioactive compounds.
• Gas chromatography-mass spectrometry (GC-MS) is crucial for profiling these compounds.
• GC-MS data analysis faces challenges like co-elution and high background noise.

Purpose of the Study:

• To develop a rapid, cost-effective solution for volatile compound identification in medicinal herbs.
• To apply the entropy minimization (EM) algorithm for enhanced GC-MS data analysis.
• To differentiate geo-authentic Chuanxiong Rhizoma (CR) from its adulterants.

Main Methods:

• Headspace GC-MS analysis of ten batches of CR and eight batches of adulterants (Fuxiong, Shanchuanxiong, Cnidii Rhizoma).
• Application of the EM algorithm to reconstruct co-eluting and low-concentration peaks.
• Qualitative identification of compounds by comparing reconstructed mass spectra with the NIST library.

Main Results:

• The EM algorithm accurately reconstructed complex GC-MS peaks, improving data analysis.
• Volatile chemical profiles of adulterants (Fuxiong, Shanchuanxiong, Cnidii Rhizoma) were distinct from authentic CR.
• The method demonstrated high accuracy and confidence in compound identification.

Conclusions:

• The EM algorithm offers a feasible and efficient solution for volatile phytochemical analysis.
• Accurate identification of medicinal herbs and adulterants is crucial for clinical and pharmaceutical applications.
• The EM algorithm has broad applicability for rapid and accurate identification of volatile compounds in various medicinal herbs.