Literature DB >> 27374557

Chemical morphology of Areca nut characterized directly by Fourier transform near-infrared and mid-infrared microspectroscopic imaging in reflection modes.

Jian-Bo Chen1, Su-Qin Sun1, Qun Zhou2.   

Abstract

Fourier transform near-infrared (NIR) and mid-infrared (MIR) imaging techniques are essential tools to characterize the chemical morphology of plant. The transmission imaging mode is mostly used to obtain easy-to-interpret spectra with high signal-to-noise ratio. However, the native chemical compositions and physical structures of plant samples may be altered when they are microtomed for the transmission tests. For the direct characterization of thick plant samples, the combination of the reflection NIR imaging and the attenuated total reflection (ATR) MIR imaging is proposed in this research. First, the reflection NIR imaging method can explore the whole sample quickly to find out typical regions in small sizes. Next, each small typical region can be measured by the ATR-MIR imaging method to reveal the molecular structures and spatial distributions of compounds of interest. As an example, the chemical morphology of Areca nut section is characterized directly by the above approach.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Areca nut; Attenuated total reflection; FT-IR spectroscopic imaging; MIR spectroscopy; NIR spectroscopy

Mesh:

Substances:

Year:  2016        PMID: 27374557     DOI: 10.1016/j.foodchem.2016.05.168

Source DB:  PubMed          Journal:  Food Chem        ISSN: 0308-8146            Impact factor:   7.514


  2 in total

Review 1.  A Review of Mid-Infrared and Near-Infrared Imaging: Principles, Concepts and Applications in Plant Tissue Analysis.

Authors:  Sevgi Türker-Kaya; Christian W Huck
Journal:  Molecules       Date:  2017-01-20       Impact factor: 4.411

2.  Near-Infrared Spectroscopy Coupled Chemometric Algorithms for Rapid Origin Identification and Lipid Content Detection of Pinus Koraiensis Seeds.

Authors:  Hongbo Li; Dapeng Jiang; Jun Cao; Dongyan Zhang
Journal:  Sensors (Basel)       Date:  2020-08-30       Impact factor: 3.576

  2 in total

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