Abstract
In this study, safflower (Carthamus tinctorius L.) was taken as a representative example to examine the application of color characteristics to evaluate quality.
A computer vision system was established for the objective and nondestructive assessment of color using image processing algorithms. Color parameters were investigated based on the RGB, L*a*b and HSV color spaces. The content of hydroxysafflor yellow A (HSYA), a major bioactive constituent of safflower, was determined by high-performance liquid chromatography. The relationship between HSYA content and color values was investigated by Pearson correlation analysis. A multiple linear regression model was established to predict the HSYA content from color values.
The red color and lightness of safflower were found to be significantly related to HSYA content. The prediction equation obtained by multiple regression was reliable with an R2 value of 0.805 (P <.01).
The results suggest that the computer vision technique could be used as a promising and non-destructive technology for color measurement and quality evaluation of CHM.
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