QA/QC of coffee using the Agilent Cary 630 ATR-FTIR analyzer

Significance of the topic

Coffee ranks among the most popular beverages globally, driven by its flavor, aroma and caffeine content. Ensuring consistent quality and authentic origin is critical for manufacturers, roasters and retailers. Traditional QA/QC workflows often rely on time-consuming chemical analyses. A rapid, on-site approach enables swift acceptance or rejection of incoming coffee lots, protecting product integrity and reducing costs.

Objectives and study overview

This study evaluates the Agilent Cary 630 ATR-FTIR analyzer as a fast, non-destructive tool for coffee QA/QC. Commercial ground-coffee brands were analyzed to:

• Establish spectral fingerprints for each product.
• Create a reference library of authenticated samples.
• Test the ability to identify unknown samples and differentiate among brands.

Methodology

Ground coffee samples from various commercial brands were obtained and directly applied to the diamond attenuated total reflectance (ATR) crystal of the Cary 630 analyzer. A pressure clamp ensured reproducible contact without overtightening. Spectra were recorded in under 30 seconds (64 scans, 4 cm⁻¹ resolution) across the mid-infrared region. Reference spectra were stored in a MicroLab FTIR database, and incoming samples were automatically classified by pass/fail or percentage similarity against this library.

Instrumentation

The core instrumentation consisted of:

• Agilent Cary 630 ATR-FTIR analyzer with diamond ATR crystal.
• Agilent MicroLab FTIR software for spectral acquisition, library management and automated search functions.

Key results and discussion

All ground-coffee brands exhibited characteristic IR bands between 1800 and 800 cm⁻¹. The 1800–1600 cm⁻¹ region captured C=O stretching from esters, lactones, aldehydes and acids, while the 1470–1430 cm⁻¹ range showed C–H bending of lipids. Strong absorptions between 1200 and 900 cm⁻¹ corresponded to carbohydrate-derived C–O–H and C–O–C vibrations. Duplicate analyses of each brand produced highly reproducible spectra. Validation with unknown samples achieved 100% correct identification via the MicroLab search algorithm, demonstrating robust discrimination based on the full spectral fingerprint.

Benefits and practical applications

The ATR-FTIR method offers:

• No sample preparation or reagents required.
• Rapid analysis (<1 minute per sample).
• Non-destructive testing suitable for on-site use at receiving docks or production lines.
• High specificity through full spectral fingerprint comparisons.
• Reduced operational costs and faster decision-making in QA/QC workflows.

Future trends and opportunities

Building larger spectral libraries may enable origin tracing, roast-degree classification and detection of adulteration. Integration with advanced chemometric techniques (e.g., PCA, PLS-DA) could enhance quantitative predictions of moisture, lipid or caffeine content. Portable ATR-FTIR units may further extend real-time quality monitoring throughout the supply chain and open applications to other food and agricultural products.

Conclusion

The Agilent Cary 630 ATR-FTIR analyzer provides a fast, reliable and user-friendly approach for coffee QA/QC. By leveraging characteristic mid-IR fingerprints and automated library matching, this method eliminates sample prep, accelerates decision-making and ensures consistent product quality.

Reference

1. Craig AP, Franca AS, Oliveira LS. Evaluation of the potential of FTIR and chemometrics for separation between defective and non-defective coffees. Food Chemistry. 2012;132:1368–1374.
2. Gordillo-Delgado F, Marín E, Cortés-Hernández DM, Mejía-Morales C, García-Salcedo AJ. Discrimination of organic coffee via Fourier transform infrared–photoacoustic spectroscopy. Journal of the Science of Food and Agriculture. 2012; DOI:10.1002/jsfa.5628.
3. Lyman DJ, Benck RM, Merle SF. Difference spectroscopy in the analysis of the effects of coffee cherry processing variables on the flavor of brewed coffee. International Journal of Spectroscopy. 2011;2011:815304, 5 pages. DOI:10.1155/2011/815304.
4. Innawong B, Mallikarjunan P, Irudayaraj JQ, Marcy JE. The determination of frying oil quality using Fourier transform infrared attenuated total reflectance. LWT — Food Science and Technology. 2004;37:23–28.