Rejection thresholds in chocolate milk: Evidence for segmentation

Bitterness is generally considered a negative attribute in food, yet many individuals enjoy some bitterness in products like coffee or chocolate. In chocolate, bitterness arises from naturally occurring alkaloids and phenolics found in cacao. Fermentation and roasting help develop typical chocolate flavor and reduce the intense bitterness of raw cacao by modifying these bitter compounds. As it becomes increasingly common to fortify chocolate with ‘raw’ cacao to increase the amount of healthful phytonutrients, it is important to identify the point at which the concentration of bitter compounds becomes objectionable, even to those who enjoy some bitterness. Classical threshold methods focus on the presence or absence of a sensation rather than acceptability or hedonics. A new alternative, the rejection threshold, was recently described in the literature. Here, we sought to quantify and compare differences in rejection thresholds (RjT) and detection thresholds (DT) in chocolate milk spiked with a food safe bitterant (sucrose octaacetate). In experiment 1, a series of paired preference tests was used to estimate the RjT for bitterness in chocolate milk. In a new group of participants (experiment 2), we determined the RjT and DT using the forced choice ascending method of limits. In both studies, participants were segmented on the basis of self-declared preference for milk or dark solid chocolate. Based on sigmoid fits of the indifference–preference function, the RjT was ∼2.3 times higher for those preferring dark chocolate than the RjT for those preferring milk chocolate in both experiments. In contrast, the DT for both groups was functionally identical, suggesting that differential effects of bitterness on liking of chocolate products are not based on the ability to detect bitterness in these products.

► A new psychophysical method, the rejection threshold, was recently described.
► We refine the models used in this approach by applying sigmoidal curve fitting.
► We demonstrate attributes can reach universal rejection in contrast to earlier work.
► This method successfully characterized different market segments for chocolate milk.
► In spite of clear segmentation, preference was not driven by perceptual differences.