Optimization of chromatographic separation and classification of artisanal and fine chocolate based on its bioactive compound content through multivariate statistical techniques

In this study, multivariate statistical techniques were used to evaluate concentrations of bioactive compounds such as theobromine, catechin, epicatechin, and caffeine in artisanal and fine chocolate using high-performance liquid chromatography (HPLC). The compound separation optimization step was carried out using a central composite design with three variables. The optimized variables were the initial percentage of methanol in the mobile phase, gradient time and flow rate. The optimal conditions were: initial methanol percentage of 0% (starting with 100% 010.1% (v/v) acetic acid solution), changing to 100% of methanol in 9.85 min, with a flow rate of 0.74 mL min(-1). The optimized procedure was validated and applied to the analysis of artisanal and fine chocolates with varying cocoa content. Principal component analysis (PCA) and hierarchical cluster analysis (HCA) were used to discriminate the samples based on the cocoa content present in the chocolates. Samples containing a high percentage of cocoa solids were separated from those containing a low percentage of cocoa solids due to their high concentrations of methylxanthines and flavonoids. Theobromine, catechin, epicatechin and caffeine concentrations in all samples ranged from 1.6 mg g(-1) to 13.9 mg g(-1), 0.047 mg g(-1) to 0.60 mg g(-1), 0.048 mg g(-1 )to 1.68 mg g(-1) and 0.6 mg g(-1) to 1.52 mg g(-1), respectively. A comparison with data found in the scientific literature showed that artisanal and fine chocolate with a high cocoa content can be a good source of stimulant substances such as caffeine and antioxidant compounds such as catechin and epicatechin.