Sensory drivers of liking for plant-based meat alternatives: insights from check-all-that-apply with ideal profile integration.

Plant-based meats have gained popularity owing to environmental and health considerations; however, their acceptance is often limited by less favorable sensory qualities. This study investigated the sensory drivers of liking for plant-based tteok-galbi by applying penalty analysis and partial least squares regression (PLSR) to check-all-that-apply data. To strengthen the findings, the rate-all-that-apply method was implemented with a separate group of consumers. A total of 200 consumers evaluated seven plant-based and one pork-based sample for overall liking and sensory attributes, and additionally selected desirable attributes for an ideal product. Compared with penalty analysis, PLSR enabled a more targeted identification of key drivers by accounting for attribute correlations. Attributes such as "glossy appearance", "sweet taste", "umami taste", "meaty odor/flavor", "smoked flavor," "elasticity mouthfeel", and "oily mouthfeel" enhanced liking, while "cooked soybean odor" and "cooked soybean flavor" reduced acceptance. The combined use of both methods offered a more comprehensive understanding of consumer preferences.