Adaptive kernel independent component analysis and UV spectrometry applied to characterize the procedure for processing prepared rhubarb roots

Abstract

By determination of the number of absorptive chemical components (ACCs) in mixtures using median absolute deviation (MAD) analysis and extraction of spectral profiles of ACCs using kernel independent component analysis (KICA), an adaptive KICA (AKICA) algorithm was proposed. The proposed AKICA algorithm was used to characterize the procedure for processing prepared rhubarb roots by resolution of the measured mixed raw UV spectra of the rhubarb samples that were collected at different steaming intervals. The results show that the spectral features of ACCs in the mixtures can be directly estimated without chemical and physical pre-separation and other prior information. The estimated three independent components (ICs) represent different chemical components in the mixtures, which are mainly polysaccharides (IC1), tannin (IC2), and anthraquinone glycosides (IC3). The variations of the relative concentrations of the ICs can account for the chemical and physical changes during the processing procedure: IC1 increases significantly before the first 5 h, and is nearly invariant after 6 h; IC2 has no significant changes or is slightly decreased during the processing procedure; IC3 decreases significantly before the first 5 h and decreases slightly after 6 h. The changes of IC1 can explain why the colour became black and darkened during the processing procedure, and the changes of IC3 can explain why the processing procedure can reduce the bitter and dry taste of the rhubarb roots. The endpoint of the processing procedure can be determined as 5-6 h, when the increasing or decreasing trends of the estimated ICs are insignificant. The AKICA-UV method provides an alternative approach for the characterization of the processing procedure of rhubarb roots preparation, and provides a novel way for determination of the endpoint of the traditional Chinese medicine (TCM) processing procedure by inspection of the change trends of the ICs.

Dependent Component Analysis and its Applications for Estimation of Source Ultraviolet Spectral Profiles and Characterization of Processing Batch for Preparation of <i>R</i><i>adix s</i><i>cutellariae</i>

“…It should be noted that the estimated DCs may be the mirrors of the real sources that likes using InfomaxICA, FastICA, and kernel ICA, in which there is no nonnegative constraint to the mixing matrix [4][5][6]. On these cases, the estimated DCs should be mirrored according to the chemical information of the spectra of the components represented or use other ICA algorithms to cross verify the estimated sources.…”

“…Recent years, we used independent component analysis (ICA) to directly estimate source spectral profiles, which ere considered as the independent components (ICs), from the mixed spectra that were measured during Chinese medical plants processing batches [4][5][6]. By inspection of the peak features and variations of the relative concentrations of the extracted ICs, the main active components can be accounted and the endpoint of the processing batch can be determined.…”

Quality Prediction Model of KICA-JITL-LWPLS Based on Wavelet Kernel Function

“…The wavelet kernel function, by virtue of the multi-scale nature of the wavelet transform and by providing an approximate orthogonal basis, combined with the ICA algorithm to analyze the data step-by-step, can improve the ability of the non-linear mapping and hence the data separation performance [21,22]. Although the above methods can handle non-Gaussian and complex non-linear data and improve the data-processing accuracy, they mainly emphasize the ability to interpret the independent variables themselves and ignore the ability to interpret the dependent variables [23,24]. It is often applied to fault detection and the data processing of industrial processes and is unable to perform regression analysis and build quality prediction models for the dependent variable.…”

An experimental study on providing a scientific evidence for seven-time alcohol-steaming of Rhei Rhizoma when clinically used

“…Additionally, processing is important to moderate reactions (such as anaphylaxis and allergies), diminish adverse events and modify detrimental properties (such as disagreeable flavors and odors) [ 6 ]. Experimental studies have been conducted to confirm the benefits of processing medicinal herbs to reduce their toxicity [ 7 , 8 ].…”

“…Wang et al compared the levels of anthraquinones and tannins in several processed RR extracts using different methods and found RR steaming decreased combined anthraquinones, while there was little change in total anthraquinones and tannins. Additionally, water-steamed RR decreased the anthraquinone glycoside content [ 7 , 8 ]. Doui et al reported that alcohol-soaking in 16 % ethanol and then steaming of RR decreased the sennoside content, while the processing increased the anthraquinone content [ 10 , 11 ].…”