A predictive spatial model for roasted coffee using oxygen isotopes of α-cellulose

Area of Science:

• Stable isotope geochemistry
• Food authenticity and traceability
• Agricultural science

Background:

• Fraudulent region-of-origin labeling is a significant issue for high-value commodities like coffee.
• Oxygen isotope ratios (δ¹⁸O) in cellulose serve as reliable geographic tracers, integrating climate and water source information.
• A predictive spatial model, or isoscape, of coffee bean cellulose δ¹⁸O is needed to assess origin claims.

Purpose of the Study:

• To develop a predictive spatial model (isoscape) for the oxygen isotope ratio (δ¹⁸O) of coffee bean cellulose.
• To evaluate the utility of coffee bean cellulose δ¹⁸O for verifying region-of-origin claims.
• To establish a quantitative tool for roasted coffee authentication.

Main Methods:

• Measured oxygen isotope ratios (δ¹⁸O) of α-cellulose from roasted coffee beans using TC-EA/IRMS.
• Calculated the δ¹⁸O value of coffee bean water and modeled its enrichment relative to local precipitation based on temperature and humidity.
• Integrated this function into a mechanistic model to predict coffee bean cellulose δ¹⁸O values globally.

Main Results:

• Coffee bean cellulose δ¹⁸O values ranged from +22‰ to +42‰ (V-SMOW).
• Coffees from the same region exhibited similar isotope ratios, with bean cellulose δ¹⁸O generally higher than modeled stem cellulose.
• Predicted coffee cellulose δ¹⁸O values closely matched measured values, with an accuracy of ±2.3‰.

Conclusions:

• The oxygen isotope ratio of coffee bean cellulose is a robust indicator of geographic origin.
• Cellulose δ¹⁸O values predictably vary with climatic factors and precipitation isotope ratios.
• The developed isoscape provides a quantitative tool for verifying the region-of-origin of roasted coffee.