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Determining the Authenticity of Cocoa Solid in Chocolates Using Chemical Markers, Antioxidant Activity, and Multivariate Analysis

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Abstract

The objective was to determine the cocoa solids in chocolates using the content of bioactive compounds and their antioxidant capacity combined with multivariate statistics. For control, 5 formulations were produced with different concentrations of cocoa solids (30%, 45%, 60%, 75%, and 90%) and 105 commercial samples were acquired with varying concentrations of cocoa solids (30–88%). The chocolates were evaluated regarding total phenolic compounds, methylxanthines (theobromine and caffeine), phenolics (( +)-catechin and ( −)-epicatechin), and antioxidant capacity. The obtained data were submitted to the multivariate techniques of principal component analysis (PCA) and multiple linear regression (MRL). The PCA of the 5 formulations produced distinct groups in relation to cocoa concentrations and a similar behavior for commercial chocolates. The regression equation (MLR) was able to predict the cocoa solids of commercial chocolates and highlighted 10% of the samples as possible adulterated products. Thus, multivariate analysis associated with quantified bioactive compounds and antioxidant capacity of the samples proved to be an effective strategy for verifying cocoa solids in chocolates.

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Higher Education Personnel (CAPES).

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Correspondence to Sibelli Passini Barbosa Ferrão.

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Ingrid Alves Santos declares that she has no conflict of interest. Acsa Santos Batista declares that he has no conflict of interest. Daniele Gomes Conceição declares that he has no conflict of interest. Márjorie Castro Pinto Porfírio declares that she has no conflict of interest. Leandro Soares Santos declares that he has no conflict of interest. Sibelli Passini Barbosa Ferrão declares that she has no conflict of interest.

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Santos, I.A., Batista, A.S., Conceição, D.G. et al. Determining the Authenticity of Cocoa Solid in Chocolates Using Chemical Markers, Antioxidant Activity, and Multivariate Analysis. Food Anal. Methods 15, 2558–2565 (2022). https://doi.org/10.1007/s12161-022-02316-0

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  • DOI: https://doi.org/10.1007/s12161-022-02316-0

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