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The development and in-house testing of a method for the detection and quantification of cocoa butter equivalents in cocoa butter and plain chocolate is described. A database consisting of the triacylglycerol profile of 74 genuine cocoa butter and 75 cocoa butter equivalent samples obtained by high-resolution capillary gas liquid chromatography was created, using a certified cocoa butter reference material (IRMM-801) for calibration purposes. Based on these data, a large number of cocoa butter/cocoa butter equivalent mixtures were arithmetically simulated. By subjecting the data set to various statistical tools, reliable models for both detection (univariate regression model) and quantification (multivariate model) were elaborated. Validation data sets consisting of a large number of samples (n = 4050 for detection, n = 1050 for quantification) were used to test the models. Excluding pure illipé fat samples from the data set, the detection limit was determined between 1 and 3% foreign fat in cocoa butter. Recalculated for a chocolate with a fat content of 30%, these figures are equal to 0.3–0.9% cocoa butter equivalent. For quantification, the average error for prediction was estimated to be 1.1% cocoa butter equivalent in cocoa butter, without prior knowledge of the materials used in the blend corresponding to 0.3% in chocolate (fat content 30%). The advantage of the approach is that by using IRMM-801 for calibration, the established mathematical decision rules can be transferred to every testing laboratory.

Detection and Quantification of Cocoa Butter Equivalents in Cocoa Butter and Plain Chocolate by Gas Liquid Chromatography of Triacylglycerols