This work first describes a simple approach for the untargeted profiling of volatile compounds for distinguishing between white duck down (WDD) and white goose down (WGD) based on resolution-optimized GC-IMS combined ...This work first describes a simple approach for the untargeted profiling of volatile compounds for distinguishing between white duck down (WDD) and white goose down (WGD) based on resolution-optimized GC-IMS combined with optimized chemometric techniques, namely PCA. The detection method for down samples was established by using GC-IMS. Meanwhile, the reason of unpleasant odors caused by WDD was explained on the basis of the characteristic volatile compounds identification. GC-IMS fingerprinting can be considered a revolutionary approach for a truly fully automatable, cost-efficient, and in particular highly sensitive method. A total of 22 compounds were successfully separated and identified through GC-IMS method, and the significant differences in volatile compounds were observed in three parts of WDD and WGD samples. The most characteristic volatile compounds of WGD belong to aldehydes, whereas carboxylic acids from WDD were detected generated by autoxidation reaction. Meanwhile, the main reason of unpleasant odor generation was possibly attributed to the high concentration of volatile carboxylic acids of WDD. Therefore, the constructed model presents a simple and efficient method of analysis and serves as a basis for down processing and quality control.展开更多
Data evaluation strategies for the novel coupled MCC-IMS sensory system are developed. Mayor attention to the plausibility of applied procedures and the feasibility of automation was paid. Three stages of extraction l...Data evaluation strategies for the novel coupled MCC-IMS sensory system are developed. Mayor attention to the plausibility of applied procedures and the feasibility of automation was paid. Three stages of extraction levels with increasing data reduction are presented for several fields of application. According to suitable extraction levels, real data were tested on various structures of artificial neural networks (ANN) with the result, that the computational levels must still be chosen by expertise, but subsequent processing and training can be fully automated. For the training of larger net- works a method of automated generation of secondary training data is presented which exceeds the quality of previous noise models by far. It is concluded that the combination of MCC-IMS as measuring instrument and ANNs as evalua- tion technique have high potential for industrial use in process monitoring.展开更多
Objectives:The chemical constituents of Poria cocos grown with different substrates vary significantly;thus,identifying and comparing their biomarkers are important.Materials and Methods:Herein,the chemical constituen...Objectives:The chemical constituents of Poria cocos grown with different substrates vary significantly;thus,identifying and comparing their biomarkers are important.Materials and Methods:Herein,the chemical constituents of Poria cocos obtained with five different substrates were assessed using gas chromatography–ion mobility spectrometry(GC-IMS),high-performance liquid chromatography and multivariate statistical analysis.Results:The content of moisture,ash,alcohol-soluble matter,and heavy metals,except for those of the miscellaneous wood Poria cocos,conform to the specifications defined in the Chinese Pharmacopoeia(Edition 2020),and the polysaccharide contents are all greater than 57%.Conclusions:Based on GC-IMS and the established fingerprints,87 compounds were detected,70 of which were identified in each group.Multivariate statistical analysis revealed seven compounds(two esters,three alcohols,and two aldehydes),which could be considered as potential marker compounds for discrimination.展开更多
文摘This work first describes a simple approach for the untargeted profiling of volatile compounds for distinguishing between white duck down (WDD) and white goose down (WGD) based on resolution-optimized GC-IMS combined with optimized chemometric techniques, namely PCA. The detection method for down samples was established by using GC-IMS. Meanwhile, the reason of unpleasant odors caused by WDD was explained on the basis of the characteristic volatile compounds identification. GC-IMS fingerprinting can be considered a revolutionary approach for a truly fully automatable, cost-efficient, and in particular highly sensitive method. A total of 22 compounds were successfully separated and identified through GC-IMS method, and the significant differences in volatile compounds were observed in three parts of WDD and WGD samples. The most characteristic volatile compounds of WGD belong to aldehydes, whereas carboxylic acids from WDD were detected generated by autoxidation reaction. Meanwhile, the main reason of unpleasant odor generation was possibly attributed to the high concentration of volatile carboxylic acids of WDD. Therefore, the constructed model presents a simple and efficient method of analysis and serves as a basis for down processing and quality control.
文摘Data evaluation strategies for the novel coupled MCC-IMS sensory system are developed. Mayor attention to the plausibility of applied procedures and the feasibility of automation was paid. Three stages of extraction levels with increasing data reduction are presented for several fields of application. According to suitable extraction levels, real data were tested on various structures of artificial neural networks (ANN) with the result, that the computational levels must still be chosen by expertise, but subsequent processing and training can be fully automated. For the training of larger net- works a method of automated generation of secondary training data is presented which exceeds the quality of previous noise models by far. It is concluded that the combination of MCC-IMS as measuring instrument and ANNs as evalua- tion technique have high potential for industrial use in process monitoring.
基金the National Key Research and Development Program of China(No.2023YFD2200903)the World Bank Loans Qiandao Lake and Xin’an River Basin Water Resources and Ecological Protection Projects in Zhejiang(CLJY3),China.
文摘Objectives:The chemical constituents of Poria cocos grown with different substrates vary significantly;thus,identifying and comparing their biomarkers are important.Materials and Methods:Herein,the chemical constituents of Poria cocos obtained with five different substrates were assessed using gas chromatography–ion mobility spectrometry(GC-IMS),high-performance liquid chromatography and multivariate statistical analysis.Results:The content of moisture,ash,alcohol-soluble matter,and heavy metals,except for those of the miscellaneous wood Poria cocos,conform to the specifications defined in the Chinese Pharmacopoeia(Edition 2020),and the polysaccharide contents are all greater than 57%.Conclusions:Based on GC-IMS and the established fingerprints,87 compounds were detected,70 of which were identified in each group.Multivariate statistical analysis revealed seven compounds(two esters,three alcohols,and two aldehydes),which could be considered as potential marker compounds for discrimination.
