The purpose of this study was to investigate the feasibility of using texture analyzer to predict sensory attributes of cosmetic emulsions.Eleven emulsions prepared in the lab and twelve commercial products have been ...The purpose of this study was to investigate the feasibility of using texture analyzer to predict sensory attributes of cosmetic emulsions.Eleven emulsions prepared in the lab and twelve commercial products have been tested by texture analyzer and evaluated by a trained sensory panel.Based on the collected data,a series of precise predictive equations were presented,and the predictive models were developed using simple linear regression by the best Pearson’s correlation coefficients.The results showed that the texture analyzer can predict sensory attributes of spreadability,firmness,ease of pick-up,peak after pick-up and tackiness by single corresponding parameter.All the values of R2 for these predictive models were above 0.80 except for the attribute of spreadability(R2=0.71).New methods were designed to measure three sensory attributes of ease of pick-up,peak after pick-up and tackiness,while the modified methods were developed to measure spreadability and firmness.These reported methods in the research are very effective and easy to operate and can support alternatives to traditional sensory profiles obtained with trained panels.展开更多
文摘The purpose of this study was to investigate the feasibility of using texture analyzer to predict sensory attributes of cosmetic emulsions.Eleven emulsions prepared in the lab and twelve commercial products have been tested by texture analyzer and evaluated by a trained sensory panel.Based on the collected data,a series of precise predictive equations were presented,and the predictive models were developed using simple linear regression by the best Pearson’s correlation coefficients.The results showed that the texture analyzer can predict sensory attributes of spreadability,firmness,ease of pick-up,peak after pick-up and tackiness by single corresponding parameter.All the values of R2 for these predictive models were above 0.80 except for the attribute of spreadability(R2=0.71).New methods were designed to measure three sensory attributes of ease of pick-up,peak after pick-up and tackiness,while the modified methods were developed to measure spreadability and firmness.These reported methods in the research are very effective and easy to operate and can support alternatives to traditional sensory profiles obtained with trained panels.
