The application of near-infrared spectra micro-image in the imaging analysis of biology samples

In this research, suitable imaging methods were used for acquiring single compound images of biology samples of chicken pectorales tissue section, tobacco dry leaf, fresh leaf and plant glandular hair, respectively. The adverse effects caused by the high water content and the thermal effect of near...

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Main Authors: Dong Wang, Yun-Sheng Ding, Zhong-Hua Guo, Shun-Geng Min
Format: Article
Language:English
Published: World Scientific Publishing 2014-07-01
Series:Journal of Innovative Optical Health Sciences
Subjects:
Online Access:http://www.worldscientific.com/doi/pdf/10.1142/S1793545813500624
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spelling doaj-cc43fdd0bc3d4c2ab887cbebd93676c12020-11-24T23:28:52ZengWorld Scientific PublishingJournal of Innovative Optical Health Sciences1793-54581793-72052014-07-01741350062-11350062-1010.1142/S179354581350062410.1142/S1793545813500624The application of near-infrared spectra micro-image in the imaging analysis of biology samplesDong Wang0Yun-Sheng Ding1Zhong-Hua Guo2Shun-Geng Min3Department of Applied Chemistry, College of Science, China Agricultural University, Beijing 100193, P. R. ChinaYunnan Tobacco Company Dali Branch, Yunnan 671000, P. R. ChinaDepartment of Applied Chemistry, College of Science, China Agricultural University, Beijing 100193, P. R. ChinaDepartment of Applied Chemistry, College of Science, China Agricultural University, Beijing 100193, P. R. ChinaIn this research, suitable imaging methods were used for acquiring single compound images of biology samples of chicken pectorales tissue section, tobacco dry leaf, fresh leaf and plant glandular hair, respectively. The adverse effects caused by the high water content and the thermal effect of near infrared (NIR) light were effectively solved during the experiment procedures and the data processing. PCA algorithm was applied to the NIR micro-image of chicken pectorales tissue. Comparing the loading vector of PC3 with the NIR spectrum of dry albumen, the information of PC3 was confirmed to be provided mainly by protein, i.e., the 3rd score image represents the distribution trend of protein mainly. PCA algorithm was applied to the NIR micro-image of tobacco dry leaf. The information of PC2 was confirmed to be provided by carbohydrate including starch mainly. Compared to the 2nd score image of tobacco dry leaf, the compared correlation image with the reference spectrum of starch had the same distribution trend as the 2nd score image. The comparative correlation images with the reference spectra of protein, glucose, fructose and the total plant alkaloid were acquired to confirm the distribution trend of these compounds in tobacco dry leaf respectively. Comparative correlation images of fresh leaf with the reference spectra of protein, starch, fructose, glucose and water were acquired to confirm the distribution trend of these compounds in fresh leaf. Chemimap imaging of plant glandular hair was acquired to show the tubular structure clearly.http://www.worldscientific.com/doi/pdf/10.1142/S1793545813500624Near-infrared spectra micro-imageprincipal component analysiscompound distributiontobacco leafplant glandular hair
collection DOAJ
language English
format Article
sources DOAJ
author Dong Wang
Yun-Sheng Ding
Zhong-Hua Guo
Shun-Geng Min
spellingShingle Dong Wang
Yun-Sheng Ding
Zhong-Hua Guo
Shun-Geng Min
The application of near-infrared spectra micro-image in the imaging analysis of biology samples
Journal of Innovative Optical Health Sciences
Near-infrared spectra micro-image
principal component analysis
compound distribution
tobacco leaf
plant glandular hair
author_facet Dong Wang
Yun-Sheng Ding
Zhong-Hua Guo
Shun-Geng Min
author_sort Dong Wang
title The application of near-infrared spectra micro-image in the imaging analysis of biology samples
title_short The application of near-infrared spectra micro-image in the imaging analysis of biology samples
title_full The application of near-infrared spectra micro-image in the imaging analysis of biology samples
title_fullStr The application of near-infrared spectra micro-image in the imaging analysis of biology samples
title_full_unstemmed The application of near-infrared spectra micro-image in the imaging analysis of biology samples
title_sort application of near-infrared spectra micro-image in the imaging analysis of biology samples
publisher World Scientific Publishing
series Journal of Innovative Optical Health Sciences
issn 1793-5458
1793-7205
publishDate 2014-07-01
description In this research, suitable imaging methods were used for acquiring single compound images of biology samples of chicken pectorales tissue section, tobacco dry leaf, fresh leaf and plant glandular hair, respectively. The adverse effects caused by the high water content and the thermal effect of near infrared (NIR) light were effectively solved during the experiment procedures and the data processing. PCA algorithm was applied to the NIR micro-image of chicken pectorales tissue. Comparing the loading vector of PC3 with the NIR spectrum of dry albumen, the information of PC3 was confirmed to be provided mainly by protein, i.e., the 3rd score image represents the distribution trend of protein mainly. PCA algorithm was applied to the NIR micro-image of tobacco dry leaf. The information of PC2 was confirmed to be provided by carbohydrate including starch mainly. Compared to the 2nd score image of tobacco dry leaf, the compared correlation image with the reference spectrum of starch had the same distribution trend as the 2nd score image. The comparative correlation images with the reference spectra of protein, glucose, fructose and the total plant alkaloid were acquired to confirm the distribution trend of these compounds in tobacco dry leaf respectively. Comparative correlation images of fresh leaf with the reference spectra of protein, starch, fructose, glucose and water were acquired to confirm the distribution trend of these compounds in fresh leaf. Chemimap imaging of plant glandular hair was acquired to show the tubular structure clearly.
topic Near-infrared spectra micro-image
principal component analysis
compound distribution
tobacco leaf
plant glandular hair
url http://www.worldscientific.com/doi/pdf/10.1142/S1793545813500624
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