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Rapid determination of lambda-cyhalothrin residues on Chinese cabbage based on MIR spectroscopy and a Gustafson–Kessel noise clustering algorithm

Pesticide residues exceeding the standard in Chinese cabbage is harmful to human health. In order to quickly, non-destructively and effectively qualitatively analyze lambda-cyhalothrin residues on Chinese cabbage, a method involving a Gustafson–Kessel noise clustering (GKNC) algorithm was proposed t...

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Detalles Bibliográficos
Autores principales: Zheng, Jun, Gong, Zhe, Yin, Shaojie, Wang, Wei, Wang, Meng, Lin, Peng, Zhou, Haoxiang, Yang, Yangjian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9218965/
https://www.ncbi.nlm.nih.gov/pubmed/35799918
http://dx.doi.org/10.1039/d2ra01557a
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author Zheng, Jun
Gong, Zhe
Yin, Shaojie
Wang, Wei
Wang, Meng
Lin, Peng
Zhou, Haoxiang
Yang, Yangjian
author_facet Zheng, Jun
Gong, Zhe
Yin, Shaojie
Wang, Wei
Wang, Meng
Lin, Peng
Zhou, Haoxiang
Yang, Yangjian
author_sort Zheng, Jun
collection PubMed
description Pesticide residues exceeding the standard in Chinese cabbage is harmful to human health. In order to quickly, non-destructively and effectively qualitatively analyze lambda-cyhalothrin residues on Chinese cabbage, a method involving a Gustafson–Kessel noise clustering (GKNC) algorithm was proposed to cluster the mid-infrared (MIR) spectra. A total of 120 Chinese cabbage samples with three different lambda-cyhalothrin residue levels (no lambda-cyhalothrin, and cases where the ratios of lambda-cyhalothrin and water were 1 : 500 and 1 : 100) were scanned using an Agilent Cary 630 FTIR spectrometer for collecting the MIR spectra. Next, multiple scatter correction (MSC) was employed to eliminate the effects of light scattering. Furthermore, principal component analysis (PCA) and linear discriminant analysis (LDA) were utilized to reduce the dimensionality and extract the feature information from the MIR spectra. Finally, fuzzy c-means (FCM) clustering, Gustafson–Kessel (GK) clustering, noise clustering (NC) and the GKNC algorithm were applied to cluster the MIR spectral data, respectively. The experimental results showed that the GKNC algorithm gave the best classification performance compared against the other three fuzzy clustering algorithms, and its highest clustering accuracy reached 93.3%. Therefore, the GKNC algorithm coupled with MIR spectroscopy is an effective method for detecting lambda-cyhalothrin residues on Chinese cabbage.
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spelling pubmed-92189652022-07-06 Rapid determination of lambda-cyhalothrin residues on Chinese cabbage based on MIR spectroscopy and a Gustafson–Kessel noise clustering algorithm Zheng, Jun Gong, Zhe Yin, Shaojie Wang, Wei Wang, Meng Lin, Peng Zhou, Haoxiang Yang, Yangjian RSC Adv Chemistry Pesticide residues exceeding the standard in Chinese cabbage is harmful to human health. In order to quickly, non-destructively and effectively qualitatively analyze lambda-cyhalothrin residues on Chinese cabbage, a method involving a Gustafson–Kessel noise clustering (GKNC) algorithm was proposed to cluster the mid-infrared (MIR) spectra. A total of 120 Chinese cabbage samples with three different lambda-cyhalothrin residue levels (no lambda-cyhalothrin, and cases where the ratios of lambda-cyhalothrin and water were 1 : 500 and 1 : 100) were scanned using an Agilent Cary 630 FTIR spectrometer for collecting the MIR spectra. Next, multiple scatter correction (MSC) was employed to eliminate the effects of light scattering. Furthermore, principal component analysis (PCA) and linear discriminant analysis (LDA) were utilized to reduce the dimensionality and extract the feature information from the MIR spectra. Finally, fuzzy c-means (FCM) clustering, Gustafson–Kessel (GK) clustering, noise clustering (NC) and the GKNC algorithm were applied to cluster the MIR spectral data, respectively. The experimental results showed that the GKNC algorithm gave the best classification performance compared against the other three fuzzy clustering algorithms, and its highest clustering accuracy reached 93.3%. Therefore, the GKNC algorithm coupled with MIR spectroscopy is an effective method for detecting lambda-cyhalothrin residues on Chinese cabbage. The Royal Society of Chemistry 2022-06-23 /pmc/articles/PMC9218965/ /pubmed/35799918 http://dx.doi.org/10.1039/d2ra01557a Text en This journal is © The Royal Society of Chemistry https://creativecommons.org/licenses/by-nc/3.0/
spellingShingle Chemistry
Zheng, Jun
Gong, Zhe
Yin, Shaojie
Wang, Wei
Wang, Meng
Lin, Peng
Zhou, Haoxiang
Yang, Yangjian
Rapid determination of lambda-cyhalothrin residues on Chinese cabbage based on MIR spectroscopy and a Gustafson–Kessel noise clustering algorithm
title Rapid determination of lambda-cyhalothrin residues on Chinese cabbage based on MIR spectroscopy and a Gustafson–Kessel noise clustering algorithm
title_full Rapid determination of lambda-cyhalothrin residues on Chinese cabbage based on MIR spectroscopy and a Gustafson–Kessel noise clustering algorithm
title_fullStr Rapid determination of lambda-cyhalothrin residues on Chinese cabbage based on MIR spectroscopy and a Gustafson–Kessel noise clustering algorithm
title_full_unstemmed Rapid determination of lambda-cyhalothrin residues on Chinese cabbage based on MIR spectroscopy and a Gustafson–Kessel noise clustering algorithm
title_short Rapid determination of lambda-cyhalothrin residues on Chinese cabbage based on MIR spectroscopy and a Gustafson–Kessel noise clustering algorithm
title_sort rapid determination of lambda-cyhalothrin residues on chinese cabbage based on mir spectroscopy and a gustafson–kessel noise clustering algorithm
topic Chemistry
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9218965/
https://www.ncbi.nlm.nih.gov/pubmed/35799918
http://dx.doi.org/10.1039/d2ra01557a
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