- First combination of stable isotopes and nuclear magnetic resonance for cocoa.
- Chemometric analysis of combined data sets allows improved discrimination.
- Multivariate models achieved correct classification for countries and varieties.
- NMR-spectral signals identify ingredients suited for discrimination purposes.
- Putative general approach for authenticity screening of food.
Within the cocoa market (
L.), quality and prices are often determined by geographical origin, making traceability indispensable. Therefore, to investigate possibilities of tracing by analytical methods, 48 carefully selected cocoa samples from 20 countries have been profiled using a combination of stable isotope-ratio mass spectrometry (IRMS) and proton nuclear magnetic resonance (
H NMR). Chemometric analysis of combined data sets from both, stable isotope data (δ
H, %C, %N, %O, %H) and
H NMR fingerprints, achieved good separation with increased classification rates compared to classification with data of the isolated methods. IRMS contributed primarily to discrimination between countries, while 1H NMR significantly contributed to separation of varieties, but also the regions within individual countries. This study thus demonstrates that combination of two analytical methods is an effective tool to enhance both, accuracy and precision, in authenticity testing of cocoa.