Exploring creaminess perception in ice cream products using a combined static and dynamic sensory approach

Background, Context, or Rationale: Creaminess is a critical determinant of the consumer acceptance of ice cream, yet its multidimensional sensory drivers—particularly across static and temporal dimensions—remain poorly characterised, thus hindering the development of healthier, low-fat alternatives. Aim(s): To identify key textural and temporal attributes governing creaminess perception in ice cream using complementary static (quantitative descriptive analysis, QDA) and dynamic (temporal check-all-that-apply, TCATA) sensory methodologies. Methods: A mixed-method framework was implemented: (1) A word association task with 186 consumers captured spontaneous creaminess descriptors, consolidated into 12 attributes via focus groups; (2) QDA quantified static correlations between creaminess and sensory properties; and (3) TCATA tracked dynamic attribute interactions over 60 s. Major Findings: Static drivers (QDA): Creaminess correlated negatively with melting time, coldness, hardness and iciness (P < 0.05), and positively with thickness and mouth coating (P < 0.05). Temporal dynamics (TCATA): Creaminess perception evolved in two phases: (1) 0–25 s: Driven by viscosity and mouth coating intensity (P < 0.05); (2) 60–120 s: Sustained by thickness and smoothness, delaying perceptual decline. Scientific or Industrial Implications: This dual-axis model advances creaminess characterisation by linking instantaneous texture (thickness and mouth coating) to time-dependent sensory transitions, offering a novel framework for studying complex sensory attributes. Findings enable targeted reformulation of low-fat ice creams by modulating thickness and smoothness in order to mimic fat-derived creaminess.