Prediction of key aroma development in coffees roasted to different degrees by colorimetric sensor array

Area of Science:

• Food Chemistry
• Analytical Chemistry
• Sensory Science

Background:

• Coffee aroma is complex, influenced by roasting degree.
• Volatile compounds significantly contribute to perceived coffee aroma.
• Accurate methods are needed to quantify aroma profiles related to roast levels.

Purpose of the Study:

• To develop and validate a colorimetric sensor array (CSA) for discriminating coffee samples based on roast degree.
• To identify key volatile compounds associated with different roast levels.
• To correlate CSA responses with the concentration of specific aroma compounds.

Main Methods:

• Development of a colorimetric sensor array (CSA) sensitive to key coffee aroma volatiles.
• Analysis of volatile compounds (Strecker aldehydes, α-diketones, sulfur compounds) in coffee samples.
• Application of chemometric methods: Principal Component Analysis (PCA), Hierarchical Cluster Analysis (HCA), and Partial Least Squares Regression (PLSR).

Main Results:

• CSA successfully differentiated coffee samples roasted to various degrees.
• Specific volatile compounds (Strecker aldehydes, α-diketones, sulfur compounds) showed distinct patterns across roast levels.
• CSA responses demonstrated strong correlations (r_p² = 0.686–0.955) with volatile compound concentrations.
• Dimethyl sulfide was uniquely detected in light roasts.

Conclusions:

• The developed CSA is a rapid and effective tool for assessing coffee roast degrees.
• CSA technology can accurately predict coffee aroma development by monitoring volatile compound changes.
• This method offers a promising approach for quality control and sensory analysis in the coffee industry.