In recent years, there has been a demand for predicting sensory evaluation scores as a complementary index to subjective human sensory evaluation, for application in quality control and new product development.
Our foundation has attempted to objectively and comprehensively evaluate foods by quantifying their taste, appearance, and hardness using equipment related to the secondary functions (preference functions) of food, such as taste sensors and visual analyzers.
In this presentation, we will use chocolate as an example to introduce a case in which a prediction equation for sensory evaluation scores was constructed using PLS regression analysis of sensory evaluation scores and measurement data from instrumental and component analyses related to taste, texture, and color.
