Sunscreen sensory attribute prediction via textural, rheological and tribological tests

This study aims to find the quick ways to predict sensorial attributes of sunscreens using instrumental measurements. We specifically focus on the attributes most relevant to consumer 'liking' and the easiest measurements to implement in industrial labs for product development. Of the latter, we consider three types of measurements: emulative 'textural' tests typically performed with a texture analyser as well as rheological and tribological measurements. Textural tests are generally preferred but may be paralleled by rheological measurements provided they are implementable on simple viscometers used in industry (albeit with additional data processing). We found that both textural and simple rheological/viscometrical tests work well for predicting sensorial attributes about flow before (thickness) and during (spreadability) application of the products. Tribology provides useful additional information for the latter but is primarily useful for after-feel or residue attributes (absorption and skin stickiness). These findings show that simple lab tests relying on these techniques can predict human sensory attributes, thus efficiently guide product developers while reducing the need for costly and time-consuming panel studies.

Authors

Institutions

Publication Details

Journal
International Journal of Cosmetic Science
Published
2025-09-04
DOI
https://doi.org/10.1111/ics.70021
Primary Topic
Sensory Analysis and Statistical Methods
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Sunscreen sensory attribute prediction via textural, rheological and tribological tests

Andrei Potanin, Baran Teoman, Gennady Y. Gor, Günel Nabiyeva
International Journal of Cosmetic Science
Sensory Analysis and Statistical Methods
article

Sunscreen sensory attribute prediction via textural, rheological and tribological tests

Andrei Potanin, Baran Teoman, Gennady Y. Gor, Günel Nabiyeva
article en

Abstract

This study aims to find the quick ways to predict sensorial attributes of sunscreens using instrumental measurements. We specifically focus on the attributes most relevant to consumer 'liking' and the easiest measurements to implement in industrial labs for product development. Of the latter, we consider three types of measurements: emulative 'textural' tests typically performed with a texture analyser as well as rheological and tribological measurements. Textural tests are generally preferred but may be paralleled by rheological measurements provided they are implementable on simple viscometers used in industry (albeit with additional data processing). We found that both textural and simple rheological/viscometrical tests work well for predicting sensorial attributes about flow before (thickness) and during (spreadability) application of the products. Tribology provides useful additional information for the latter but is primarily useful for after-feel or residue attributes (absorption and skin stickiness). These findings show that simple lab tests relying on these techniques can predict human sensory attributes, thus efficiently guide product developers while reducing the need for costly and time-consuming panel studies.

International Journal of Cosmetic ScienceVol. 48(1)
New Jersey Institute of Technology (US), Colgate-Palmolive (United States) (US)
National Science Foundation
Openalex Percentile: Top 72%
Sensory Analysis and Statistical Methods
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.