[Objectives] This study was carried out to determine texture parameters for texture profile analysis （TPA）, and optimize the texture determination of ‘Yali’ by texture analyzer.[Methods] The traditional varieties ...[Objectives] This study was carried out to determine texture parameters for texture profile analysis （TPA）, and optimize the texture determination of ‘Yali’ by texture analyzer.[Methods] The traditional varieties of ‘Yali’ were taken as the materials, and texture parameters were determined at different compression rates and deformations at target.[Results] In the process of the TPA, the deformation at target had an extremely significant influence on 8 TPA texture parameters, namely, the hardness, cohesiveness, springiness, adhesiveness, gumminess, resilience, fracturability, and chewiness （ P ≤0.01）, while the compression rate had significant influence on the hardness and gumminess （ P ≤0.05）, had an extremely significant influence on fracturability （ P ≤0.01）, and had no significant influence on other 5 TPA parameters.[Conclusions] Taking the compression rate of 1 mm/s and 20% deformation at target as the experimental conditions for TPA could avoid the impact load of high speed on the tissue and objectively reflect the textural characteristics of ‘Yali’ pulp tissue.展开更多
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
基金Supported by Special Project of Hebei Provincial Department of Finance(F18R1908)Special Fund for Basic Scientific Research Project in Hebei Academy of Agriculture and Forestry Sciences(A2015020103)The Earmarked Fund for China Agriculture Research System(CARS-28)
文摘[Objectives] This study was carried out to determine texture parameters for texture profile analysis （TPA）, and optimize the texture determination of ‘Yali’ by texture analyzer.[Methods] The traditional varieties of ‘Yali’ were taken as the materials, and texture parameters were determined at different compression rates and deformations at target.[Results] In the process of the TPA, the deformation at target had an extremely significant influence on 8 TPA texture parameters, namely, the hardness, cohesiveness, springiness, adhesiveness, gumminess, resilience, fracturability, and chewiness （ P ≤0.01）, while the compression rate had significant influence on the hardness and gumminess （ P ≤0.05）, had an extremely significant influence on fracturability （ P ≤0.01）, and had no significant influence on other 5 TPA parameters.[Conclusions] Taking the compression rate of 1 mm/s and 20% deformation at target as the experimental conditions for TPA could avoid the impact load of high speed on the tissue and objectively reflect the textural characteristics of ‘Yali’ pulp tissue.
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.
