Comparison between voltammetric detection methods for abalone-flavoring liquid

This article attempts to determine the most accurate classification method for different abalone-flavoring liquids. Three common voltammetric detection methods, namely, linear sweep voltammetry (LSV), cyclic voltammetry (CV), and square-wave voltammetry (SWV), were considered. To compare their class...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Lv Yan, Zhang Xu, Zhang Peng, Wang Huihui, Ma Qinyi, Tao Xueheng
Formato:	article
Lenguaje:	EN
Publicado:	De Gruyter 2021
Materias:	abalone-flavoring liquid voltammetric detection methods principal component analysis probabilistic neural network support vector machine Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/cf9cea105b6743018522eb2b8b6ab600
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:cf9cea105b6743018522eb2b8b6ab600
record_format	dspace
spelling	oai:doaj.org-article:cf9cea105b6743018522eb2b8b6ab6002021-12-05T14:10:41ZComparison between voltammetric detection methods for abalone-flavoring liquid2391-541210.1515/biol-2021-0035https://doaj.org/article/cf9cea105b6743018522eb2b8b6ab6002021-04-01T00:00:00Zhttps://doi.org/10.1515/biol-2021-0035https://doaj.org/toc/2391-5412This article attempts to determine the most accurate classification method for different abalone-flavoring liquids. Three common voltammetric detection methods, namely, linear sweep voltammetry (LSV), cyclic voltammetry (CV), and square-wave voltammetry (SWV), were considered. To compare their classification accuracies of abalone-flavoring liquids, three methods were separately adopted to classify five different abalone-flavoring liquids, using a four-electrode (Au, Pt, Pd, and W) sensor array. Then the data acquired by each method were subject to the principal component analysis (PCA): the first three principal components whose eigenvalues were greater than 1 were extracted from each set of data; the cumulative variance contribution rate and the principal component scores of each method were obtained. The PCA results show that the first three principal components obtained by the CV had the highest cumulative variance contribution rate (91.307%), indicating that the CV can more comprehensively characterize the information of abalone-flavoring liquid samples than the other two methods. According to the principal component scores, compared with those of LSV and SWV, the same kind of samples detected by the CV were highly clustered and the different kinds of samples detected by the CV were greatly dispersed. This indicates that the CV can effectively distinguish between the five abalone-flavoring liquids. Finally, the detection data were further verified through probabilistic neural network and a support vector machine algorithm optimized by genetic algorithm. The results further confirm that the CV is more accurate than the other two methods in the classification of abalone-flavoring liquids. Therefore, the CV was recommended for the classification of abalone-flavoring liquids.Lv YanZhang XuZhang PengWang HuihuiMa QinyiTao XuehengDe Gruyterarticleabalone-flavoring liquidvoltammetric detection methodsprincipal component analysisprobabilistic neural networksupport vector machineBiology (General)QH301-705.5ENOpen Life Sciences, Vol 16, Iss 1, Pp 354-361 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	abalone-flavoring liquid voltammetric detection methods principal component analysis probabilistic neural network support vector machine Biology (General) QH301-705.5
spellingShingle	abalone-flavoring liquid voltammetric detection methods principal component analysis probabilistic neural network support vector machine Biology (General) QH301-705.5 Lv Yan Zhang Xu Zhang Peng Wang Huihui Ma Qinyi Tao Xueheng Comparison between voltammetric detection methods for abalone-flavoring liquid
description	This article attempts to determine the most accurate classification method for different abalone-flavoring liquids. Three common voltammetric detection methods, namely, linear sweep voltammetry (LSV), cyclic voltammetry (CV), and square-wave voltammetry (SWV), were considered. To compare their classification accuracies of abalone-flavoring liquids, three methods were separately adopted to classify five different abalone-flavoring liquids, using a four-electrode (Au, Pt, Pd, and W) sensor array. Then the data acquired by each method were subject to the principal component analysis (PCA): the first three principal components whose eigenvalues were greater than 1 were extracted from each set of data; the cumulative variance contribution rate and the principal component scores of each method were obtained. The PCA results show that the first three principal components obtained by the CV had the highest cumulative variance contribution rate (91.307%), indicating that the CV can more comprehensively characterize the information of abalone-flavoring liquid samples than the other two methods. According to the principal component scores, compared with those of LSV and SWV, the same kind of samples detected by the CV were highly clustered and the different kinds of samples detected by the CV were greatly dispersed. This indicates that the CV can effectively distinguish between the five abalone-flavoring liquids. Finally, the detection data were further verified through probabilistic neural network and a support vector machine algorithm optimized by genetic algorithm. The results further confirm that the CV is more accurate than the other two methods in the classification of abalone-flavoring liquids. Therefore, the CV was recommended for the classification of abalone-flavoring liquids.
format	article
author	Lv Yan Zhang Xu Zhang Peng Wang Huihui Ma Qinyi Tao Xueheng
author_facet	Lv Yan Zhang Xu Zhang Peng Wang Huihui Ma Qinyi Tao Xueheng
author_sort	Lv Yan
title	Comparison between voltammetric detection methods for abalone-flavoring liquid
title_short	Comparison between voltammetric detection methods for abalone-flavoring liquid
title_full	Comparison between voltammetric detection methods for abalone-flavoring liquid
title_fullStr	Comparison between voltammetric detection methods for abalone-flavoring liquid
title_full_unstemmed	Comparison between voltammetric detection methods for abalone-flavoring liquid
title_sort	comparison between voltammetric detection methods for abalone-flavoring liquid
publisher	De Gruyter
publishDate	2021
url	https://doaj.org/article/cf9cea105b6743018522eb2b8b6ab600
work_keys_str_mv	AT lvyan comparisonbetweenvoltammetricdetectionmethodsforabaloneflavoringliquid AT zhangxu comparisonbetweenvoltammetricdetectionmethodsforabaloneflavoringliquid AT zhangpeng comparisonbetweenvoltammetricdetectionmethodsforabaloneflavoringliquid AT wanghuihui comparisonbetweenvoltammetricdetectionmethodsforabaloneflavoringliquid AT maqinyi comparisonbetweenvoltammetricdetectionmethodsforabaloneflavoringliquid AT taoxueheng comparisonbetweenvoltammetricdetectionmethodsforabaloneflavoringliquid
_version_	1718371867224440832

Comparison between voltammetric detection methods for abalone-flavoring liquid

Ejemplares similares