Using HPLC with In-Column Derivatization to Authenticate Coffee Samples

Area of Science:

• Food Science
• Analytical Chemistry
• Agricultural Science

Background:

• Coffee is a globally popular beverage with a significant market value.
• Coffee fraud, involving adulteration with cheaper blends, is a growing concern, exacerbated by climate change impacting crop yields.
• Current authentication methods lack the speed and robustness required for real-time detection in a complex market.

Purpose of the Study:

• To develop a novel, rapid, and robust method for real-time coffee authentication.
• To visualize coffee's antioxidant profiles for use as authentication indicators.
• To establish mathematical similarity metrics for identifying unknown coffee samples.

Main Methods:

• Novel in-column derivatization technique for visualizing antioxidant profiles.
• Cupric Reducing Antioxidant Capacity (CUPRAC) assay.
• Three simple mathematical similarity metrics for sample identification.

Main Results:

• Successfully visualized antioxidant profiles of coffee samples.
• Demonstrated the capability to identify unknown coffee samples using the developed metrics.
• Identified unknown coffee samples within a library of thirty distinct samples.

Conclusions:

• The proposed in-column derivatization and mathematical metrics offer a promising solution for real-time coffee authentication.
• This technique can help combat coffee fraud and ensure product authenticity in the growing global market.
• The method provides a faster, easier, and more robust approach compared to existing authentication techniques.