NIR and MIR spectroscopy for quick detection of the adulteration of cocoa content in chocolates

The Near (NIR) and Mid (MIR) Infrared Spectroscopy associated with chemometric techniques were used to determine the cocoa solids content in chocolates and detect possible adulterations. Five chocolate formulations (30% to 90%) were produced with different cocoa solids concentrations and 110 commercial samples from 10 different countries with varying concentrations of cocoa solids (30% to 88%) were acquired. All repetions of the produced and commercial chocolates were evaluated using NIR and MIR. Spectroscopic data were submitted to multivariate techniques of Principal Component Analysis (PCA) and Partial Least Squares Regression (PLS). For both spectroscopy techniques, the PCA of the 5 formulations formed 5 distinct groups regarding the cocoa solids and the commercial samples showed a behavior pattern similar to the produced samples. For PLS, the regression equations showed high predictive capacity, with correlation coefficients above 90 and RMSECV values of 0.70 and 1.22, for NIR and MIR, respectively. These models highlighted, approximately, 14% of the commercial samples as possible adulterated products.

Automated summary

The study utilized Near Infrared (NIR) and Mid Infrared (MIR) Spectroscopy with chemometric techniques to accurately determine cocoa solids content in chocolates and detect possible adulterations. The results showed that Principal Component Analysis (PCA) and Partial Least Squares Regression (PLS) could effectively differentiate chocolates with varying cocoa solids concentrations, with high predictive capacity for commercial samples as well. The models identified approximately 14% of commercial samples as potentially adulterated products.