skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Synchrotron Infrared Spectroscopy with Multivariate Spectral Analyses Potentially Facilitates the Classification of Inherent Structures of Feed-Type of Sorghum

Abstract

The objective of this study was to investigate the inherent structural-chemical features of Chinese feed-type sorghum seed using synchrotron-radiation Fourier transform infrared microspectroscopy (SRFTIRM) with two multivariate molecular spectral analysis techniques: Agglomerative Hierarchical cluster (AHCA) and principal component analyses (PCA). The results show that by application of these two multivariate techniques with the infrared spectroscopy of the SRFTIRM, it makes possible to discriminate and classify the inherent molecular structural features among the different layers of sorghum with a great efficiency. With the SRFTIRM, images of the molecular chemistry of sorghum could be generated at an ultra-spatial resolution. The features of nutrient matrix and nutrient make-up and interactions could be revealed.

Authors:
;  [1];  [2]
  1. College of Agriculture and Bioresources, University of Saskatchewan 51 Campus Drive, Saskatoon, S7N 5A8 (Canada)
  2. College of Animal Science and Technology, Northeast Agricultural University (China)
Publication Date:
OSTI Identifier:
21370990
Resource Type:
Journal Article
Journal Name:
AIP Conference Proceedings
Additional Journal Information:
Journal Volume: 1214; Journal Issue: 1; Conference: WIRMS 2009: 5. international workshop on infrared microscopy and spectroscopy with accelerator based sources, Alberta (Canada), 13-17 Sep 2009; Other Information: DOI: 10.1063/1.3326350; (c) 2010 American Institute of Physics; Journal ID: ISSN 0094-243X
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; ABSORPTION SPECTROSCOPY; CRYSTAL STRUCTURE; FOURIER TRANSFORMATION; IMAGES; INFRARED SPECTRA; MICROSTRUCTURE; MULTIVARIATE ANALYSIS; NUTRIENTS; SEEDS; SORGHUM; SPATIAL RESOLUTION; SYNCHROTRON RADIATION; BREMSSTRAHLUNG; CEREALS; ELECTROMAGNETIC RADIATION; GRAMINEAE; INTEGRAL TRANSFORMATIONS; LILIOPSIDA; MAGNOLIOPHYTA; MATHEMATICS; PLANTS; RADIATIONS; RESOLUTION; SPECTRA; SPECTROSCOPY; STATISTICS; TRANSFORMATIONS

Citation Formats

Peiqiang, Yu, Damiran, Daalkhaijav, and Dasen, Liu. Synchrotron Infrared Spectroscopy with Multivariate Spectral Analyses Potentially Facilitates the Classification of Inherent Structures of Feed-Type of Sorghum. United States: N. p., 2010. Web. doi:10.1063/1.3326350.
Peiqiang, Yu, Damiran, Daalkhaijav, & Dasen, Liu. Synchrotron Infrared Spectroscopy with Multivariate Spectral Analyses Potentially Facilitates the Classification of Inherent Structures of Feed-Type of Sorghum. United States. https://doi.org/10.1063/1.3326350
Peiqiang, Yu, Damiran, Daalkhaijav, and Dasen, Liu. 2010. "Synchrotron Infrared Spectroscopy with Multivariate Spectral Analyses Potentially Facilitates the Classification of Inherent Structures of Feed-Type of Sorghum". United States. https://doi.org/10.1063/1.3326350.
@article{osti_21370990,
title = {Synchrotron Infrared Spectroscopy with Multivariate Spectral Analyses Potentially Facilitates the Classification of Inherent Structures of Feed-Type of Sorghum},
author = {Peiqiang, Yu and Damiran, Daalkhaijav and Dasen, Liu},
abstractNote = {The objective of this study was to investigate the inherent structural-chemical features of Chinese feed-type sorghum seed using synchrotron-radiation Fourier transform infrared microspectroscopy (SRFTIRM) with two multivariate molecular spectral analysis techniques: Agglomerative Hierarchical cluster (AHCA) and principal component analyses (PCA). The results show that by application of these two multivariate techniques with the infrared spectroscopy of the SRFTIRM, it makes possible to discriminate and classify the inherent molecular structural features among the different layers of sorghum with a great efficiency. With the SRFTIRM, images of the molecular chemistry of sorghum could be generated at an ultra-spatial resolution. The features of nutrient matrix and nutrient make-up and interactions could be revealed.},
doi = {10.1063/1.3326350},
url = {https://www.osti.gov/biblio/21370990}, journal = {AIP Conference Proceedings},
issn = {0094-243X},
number = 1,
volume = 1214,
place = {United States},
year = {Wed Feb 03 00:00:00 EST 2010},
month = {Wed Feb 03 00:00:00 EST 2010}
}