Prediction of Congou Black Tea Fermentation Quality Indices from Color Features Using Non-Linear Regression Methods.

ABSTRACT: Fermentation is the key process to produce the special color of congou black tea. The machine vision technology is applied to detect the color space changes of black tea's color in RGB, Lab and HSV, and to find out its relevance to black tea's fermentation quality. And then the color feature parameter is used as input to establish physicochemical indexes (TFs, TRs, and TBs) and sensory features' linear and non-linear quantitative evaluation model. Results reveal that color features are significantly correlated to quality indices. Compared with the other two color models (RGB and HSV), CIE Lab model can better reflect the dynamic variation features of quality indices and foliage color information of black tea. The predictability of non-linear models (RF and SVM) is superior to PLS linear mo

SUBMITTER: Dong C 

PROVIDER: S-EPMC6043511 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature