A mid-level data fusion approach for evaluating the internal and external changes determined by FT-NIR, electronic nose and colorimeter in Curcumae Rhizoma processing

Abstract

The aim of this study was to establish a robust and rapid method for identification of the changes of Curcumae Rhizoma (CR) in its physical properties and the components after processing. Color and odor used as the indexes for physical property evaluation in this study were quantified by non-targeted bionic detectors colorimeter and e-nose according to Chinese pharmacopoeia, and all chemical changes of the samples were observed by NIR. The technique of mid-level data fusion was adopted to simulate the recognition mode of human, and the prediction accuracy was 100%. A modified NIR band extraction method was used for feature selection after removing the redundant data which otherwise may compromise the accuracy of analysis, with a result showing bisdemethoxycurcumin and curcumol as the key factors most correlated with the changes during processing. The fused matrix was analyzed to evaluate the weight of different sensors and precisely describe the external changes of the samples, followed by a pairwise correlation analysis to investigate the role of colorimeter, e-nose and NIR in identifying the changes caused by processing as well as their correlation with each other. The results of data fusion revealed that aromatic derivatives produced during processing were closely associated with the changes in external characteristics, i.e., color and smell of the samples, while the changes in proteins did not cause significant differences. Correlation analysis demonstrated that bionic sensors could be classified into two groups: a*, WW and WS sensors, which were related to NIR band at about 6500-6700 cm^-1 formed by NH vibration of amide and protein degradation, were sensitive to the processed CR; while L*, b* and WC sensors were found to be correlated to NIR band around 8000 cm^-1 which was caused by first overtone of C-H combination of aromatic derivatives, thus could be employed as the detectors for raw CR.

Keywords: Colorimeter; Correlation map; Curcumae Rhizoma processing; Data fusion; E-nose; FT-NIR.