[Quantitative models for Baicalin content using NIR technology for the study of Shang Jie plaster]

Area of Science:

• Analytical Chemistry
• Spectroscopy
• Chemometrics

Context:

• Shang Jie plasters are a traditional Chinese medicine formulation.
• Baicalin is a key active compound in Scutellaria baicalensis (Huang Qin), a primary herb in Shang Jie plasters.
• Accurate quantification of Baicalin is crucial for ensuring the efficacy and quality of the plasters.

Purpose:

• To develop a dynamic prediction model for Baicalin content in Shang Jie plasters extract solutions.
• To utilize near-infrared (NIR) spectroscopy in transmission mode for real-time monitoring.
• To establish a robust chemometric model using partial least squares regression (PLSR) for quantitative analysis.

Summary:

• Near-infrared (NIR) transmission spectra were collected during the extraction process (n=65).
• A partial least squares regression (PLSR) model was developed correlating NIR spectra with Baicalin content determined by High-Performance Liquid Chromatography (HPLC).
• The model demonstrated high accuracy, with a cross-validation RMSECV of 0.0068 mg/g and R=0.9991, and prediction RMSEP of 0.0092 mg/g and R=0.9987.

Impact:

• This study validates NIR spectroscopy combined with PLS as a powerful, non-destructive technique for the rapid determination of Baicalin in herbal extracts.
• The developed dynamic model facilitates real-time quality control during the extraction process, improving efficiency and consistency.
• This approach can be applied to other traditional Chinese medicine formulations for active compound quantification and process optimization.