Pigment analysis based on a line-scanning fluorescence hyperspectral imaging microscope combined with multivariate curve resolution.

A rapid and cost-effective system is vital for the detection of harmful algae that causes environmental problems in terms of water quality. The approach for algae detection was to capture images based on hyperspectral fluorescence imaging microscope by detecting specific fluorescence signatures. Wit...

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Autores principales:	Lijin Lian, Xuejuan Hu, Zhenhong Huang, Liang Hu, Lu Xu
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/76e889dd411e4cc0bf49fc16537dd9c8
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spelling	oai:doaj.org-article:76e889dd411e4cc0bf49fc16537dd9c82021-12-02T20:18:32ZPigment analysis based on a line-scanning fluorescence hyperspectral imaging microscope combined with multivariate curve resolution.1932-620310.1371/journal.pone.0254864https://doaj.org/article/76e889dd411e4cc0bf49fc16537dd9c82021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0254864https://doaj.org/toc/1932-6203A rapid and cost-effective system is vital for the detection of harmful algae that causes environmental problems in terms of water quality. The approach for algae detection was to capture images based on hyperspectral fluorescence imaging microscope by detecting specific fluorescence signatures. With the high degree of overlapping spectra of algae, the distribution of pigment in the region of interest was unknown according to a previous report. We propose an optimization method of multivariate curve resolution (MCR) to improve the performance of pigment analysis. The reconstruction image described location and concentration of the microalgae pigments. This result indicated the cyanobacterial pigment distribution and mapped the relative pigment content. In conclusion, with the advantage of acquiring two-dimensional images across a range of spectra, HSI conjoining spectral features with spatial information efficiently estimated specific features of harmful microalgae in MCR models.Lijin LianXuejuan HuZhenhong HuangLiang HuLu XuPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 8, p e0254864 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Lijin Lian Xuejuan Hu Zhenhong Huang Liang Hu Lu Xu Pigment analysis based on a line-scanning fluorescence hyperspectral imaging microscope combined with multivariate curve resolution.
description	A rapid and cost-effective system is vital for the detection of harmful algae that causes environmental problems in terms of water quality. The approach for algae detection was to capture images based on hyperspectral fluorescence imaging microscope by detecting specific fluorescence signatures. With the high degree of overlapping spectra of algae, the distribution of pigment in the region of interest was unknown according to a previous report. We propose an optimization method of multivariate curve resolution (MCR) to improve the performance of pigment analysis. The reconstruction image described location and concentration of the microalgae pigments. This result indicated the cyanobacterial pigment distribution and mapped the relative pigment content. In conclusion, with the advantage of acquiring two-dimensional images across a range of spectra, HSI conjoining spectral features with spatial information efficiently estimated specific features of harmful microalgae in MCR models.
format	article
author	Lijin Lian Xuejuan Hu Zhenhong Huang Liang Hu Lu Xu
author_facet	Lijin Lian Xuejuan Hu Zhenhong Huang Liang Hu Lu Xu
author_sort	Lijin Lian
title	Pigment analysis based on a line-scanning fluorescence hyperspectral imaging microscope combined with multivariate curve resolution.
title_short	Pigment analysis based on a line-scanning fluorescence hyperspectral imaging microscope combined with multivariate curve resolution.
title_full	Pigment analysis based on a line-scanning fluorescence hyperspectral imaging microscope combined with multivariate curve resolution.
title_fullStr	Pigment analysis based on a line-scanning fluorescence hyperspectral imaging microscope combined with multivariate curve resolution.
title_full_unstemmed	Pigment analysis based on a line-scanning fluorescence hyperspectral imaging microscope combined with multivariate curve resolution.
title_sort	pigment analysis based on a line-scanning fluorescence hyperspectral imaging microscope combined with multivariate curve resolution.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/76e889dd411e4cc0bf49fc16537dd9c8
work_keys_str_mv	AT lijinlian pigmentanalysisbasedonalinescanningfluorescencehyperspectralimagingmicroscopecombinedwithmultivariatecurveresolution AT xuejuanhu pigmentanalysisbasedonalinescanningfluorescencehyperspectralimagingmicroscopecombinedwithmultivariatecurveresolution AT zhenhonghuang pigmentanalysisbasedonalinescanningfluorescencehyperspectralimagingmicroscopecombinedwithmultivariatecurveresolution AT lianghu pigmentanalysisbasedonalinescanningfluorescencehyperspectralimagingmicroscopecombinedwithmultivariatecurveresolution AT luxu pigmentanalysisbasedonalinescanningfluorescencehyperspectralimagingmicroscopecombinedwithmultivariatecurveresolution
_version_	1718374291526909952

Pigment analysis based on a line-scanning fluorescence hyperspectral imaging microscope combined with multivariate curve resolution.

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