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Predicting sensory texture properties of cosmetic emulsions by physical measurements

Abstract : The aim of this work was to investigate how instrumental measurements could predict the sensory texture of cosmetic emulsions. Eight oil-in-water emulsions, only varying by their polymeric constituent and one “control” emulsion without any polymer were formulated for this purpose. Six texture attributes were selected and precisely defined, with accurate sensory evaluation procedures and notation scales, using the Spectrum™ Descriptive Analysis method; these were Gloss, Integrity of Shape, Penetration Force, Compression Force, Stringiness and Difficulty of Spreading. Besides, an extensive rheological characterization of the creams was carried out, including flow, creep and oscillation tests. In addition, an instrumental textural characterization of the emulsions was performed using a texture analyzer, with different tests of penetration, compression, extrusion, stretching and spreadability. The gloss was also measured on emulsion films using a gloss meter. Predictive models were developed using linear simple, linear multiple and Partial Least Square (PLS) regressions. Univariate analysis showed that Gloss, Compression Force and Difficulty of Spreading were very well predicted by imitative instrumental measurements (R2 = 0.994, 0.961 and 0.968, respectively). Several good calibration models were built for each of the three other attributes (Radjusted2 > 0.914). Five commercial cosmetic emulsions were then instrumentally and sensory assessed to test the robustness of each calibration model and cross-validation was used to evaluate their predictability. Stringiness was finally very well predicted by the breaking length of filament, resulting from the imitative test of the sensory protocol (Ratio of Performance to Deviation (RPD) = 3.25); whereas Integrity of Shape and Penetration Force were very well predicted by a combination of rheological and textural parameters (RPD = 3.62 and 2.90, respectively).
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https://hal-normandie-univ.archives-ouvertes.fr/hal-02507779
Contributor : Géraldine Savary <>
Submitted on : Friday, March 13, 2020 - 3:07:13 PM
Last modification on : Tuesday, April 28, 2020 - 1:24:02 PM

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Laura Gilbert, Géraldine Savary, Michel Grisel, Celine Picard. Predicting sensory texture properties of cosmetic emulsions by physical measurements. Chemometrics and Intelligent Laboratory Systems, Elsevier, 2013, 124, pp.21-31. ⟨10.1016/j.chemolab.2013.03.002⟩. ⟨hal-02507779⟩

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