Improving Reproducibility of HPTLC Analysis for Cranberry Supplements Through Digitization and Chemometric...

Area of Science:

• Analytical Chemistry
• Chemometrics
• Botanical Analysis

Background:

• High-performance thin-layer chromatography (HPTLC) is crucial for botanical supplement quality control.
• Traditional HPTLC interpretation suffers from subjectivity and inter-plate variability, limiting reproducibility.

Purpose of the Study:

• To improve HPTLC reproducibility and analytical utility through digitization and chemometric preprocessing.
• To enhance the quality assessment of cranberry dietary supplements using advanced analytical techniques.

Main Methods:

• Standardized HPTLC protocol applied to diverse cranberry supplements.
• Digitization of chromatograms with multiple derivatization and imaging conditions.
• Chemometric preprocessing including normalization, retention factor (RF) alignment, PCA, and ANOVA-PCA.

Main Results:

• Digitization and preprocessing workflow significantly reduced plate variability (23% to 11%).
• Retention factor (RF) alignment increased sample-type variance (59% to 79%), improving classification.
• Combined data from multiple conditions enhanced chemical fingerprinting and PCA clustering.

Conclusions:

• Digitized HPTLC with chemometric preprocessing modernizes botanical fingerprinting, improving reproducibility and interpretability.
• This approach supports robust quality control for botanical products, promoting data transparency and reusability.
• Chemometric analysis facilitates data-driven quality assessment and enhances sample classification accuracy.