Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Advertisement

Nature Precedings
  • View all journals
  • Search
  • My Account Login
  • Content Explore content
  • About the journal
  • RSS feed
  1. nature
  2. nature precedings
  3. articles
  4. article
Soybean Composition Database from NIR, NMR and GC-MS Analyses- (v.3)
Download PDF
Download PDF
  • Manuscript
  • Open access
  • Published: 14 November 2011

Soybean Composition Database from NIR, NMR and GC-MS Analyses- (v.3)

  • I. Baianu1,
  • Tiefeng You2,
  • Jun Guo2,
  • Doina Costescu2 &
  • …
  • V. Prisecaru2 

Nature Precedings (2011)Cite this article

  • 597 Accesses

  • 1 Citations

  • Metrics details

Abstract

This novel Soybean Composition Database from the AFC-NMR & NIR Spectroscopy Facility of the College of ACES at the University of Illinois at Urbana includes more than 12,000 NIR measurements on soybeans from the International Soybean Germplasm Collection, such as those received from Peking at the National Soybean Collection.Excel files (.xls) of our novel spectroscopic data are currently available for all 80,000 + NIR and FT-NMR measurements; such data are made available from an ultra-fast and secure supercomputer server utilizing the current version of the Scientific-Linux OS-based software.A detailed account is also presented of our high-resolution nuclear magnetic resonance (HR-NMR) and near infrared (NIR) calibration models, methodologies and validation procedures, together with a large number of composition analyses for soybean seeds. NIR calibrations were developed based on both HR-NMR and analytical chemistry reference data for oil and twelve amino acid residues in mature soybeans and soybean embryos. Moreover, this is our first detailed report of HR-NMR determinations of amino acid profiles of proteins from whole soybean seeds, without protein extraction from the seed. It was found that the best results for both oil and protein calibrations were obtained with a Partial Least Squares Regression (PLS-1) analysis of our extensive NIR spectral data, acquired with either a DA7000 Dual Diode Array (Si and InGaAs detectors) instrument or with several Fourier Transform NIR (FT-NIR) spectrometers equipped with an integrating sphere/InGaAs detector accessory. In order to extend the bulk soybean samples calibration models to the analysis of single soybean seeds, we have analized in detail the component NIR spectra of all major soybean constituents through spectral deconvolutions for bulk, single and powdered soybean seeds. Baseline variations and light scattering effects in the NIR spectra were corrected, respectively, by calculating the first-order derivatives of the spectra and the Multiplicative Scattering Correction (MSC). The single soybean seed NIR spectra are broadly similar to those of bulk whole soybeans, with the exception of minor peaks in single soybean NIR spectra in the region from 950 to 1,000 nm. Based on previous experience with bulk soybean NIR calibrations, the PLS-1 calibration model was selected for protein, oil and moisture calibrations that we developed for single soybean seed analysis. In order to improve the reliability and robustness of our calibrations with the PLS-1 model we employed standard samples with a wide range of soybean constituent compositions: from 34% to 55% for protein, from 11% to 22% for oil and from 2% to 16% for moisture. Such calibrations are characterized by low standard errors and high degrees of correlation for all major soybean constituents. Morever, we obtained highly resolved NIR chemical images for selected regions of mature soybean embryos that allow for the quantitation of oil and protein components. Recent developments in high-resolution FT-NIR microspectroscopy extend the NIR sensitivity range to the picogram level, with submicron spatial resolution in the component distribution throughout intact soybean seeds and embryos. Such developments are potentially important for biotechnology applications that require rapid and ultra- sensitive analyses, such as those concerned with high-content microarrays in Genomics and Proteomics research. Other important applications of FT-NIR microspectroscopy are envisaged in biomedical research aimed at cancer prevention, the early detection of tumors by NIR-fluorescence, and identification of single cancer cells, or single virus particles in vivo by super-resolution microscopy/ microspectroscopy.

Similar content being viewed by others

Spectral enhancement of PlanetScope using Sentinel-2 images to estimate soybean yield and seed composition

Article Open access 01 July 2024

Autofluorescence-spectral imaging as an innovative method for rapid, non-destructive and reliable assessing of soybean seed quality

Article Open access 08 September 2021

A giant NLR gene confers broad-spectrum resistance to Phytophthora sojae in soybean

Article Open access 05 November 2021

Article PDF

Author information

Authors and Affiliations

  1. AFC-NMR and NIR Microspectroscopy Facility, College of ACES, University of Illinois, Urbana, Illinois, 61801, USA

    I. Baianu

  2. University of Illinois at Urbana, AFC- NMR and NIR Microspectroscopy Facility, College of ACES https://www.nature.com/nature

    Tiefeng You, Jun Guo, Doina Costescu & V. Prisecaru

Authors
  1. I. Baianu
    View author publications

    Search author on:PubMed Google Scholar

  2. Tiefeng You
    View author publications

    Search author on:PubMed Google Scholar

  3. Jun Guo
    View author publications

    Search author on:PubMed Google Scholar

  4. Doina Costescu
    View author publications

    Search author on:PubMed Google Scholar

  5. V. Prisecaru
    View author publications

    Search author on:PubMed Google Scholar

Rights and permissions

Creative Commons Attribution 3.0 License.

Reprints and permissions

About this article

Cite this article

Baianu, I., You, T., Guo, J. et al. Soybean Composition Database from NIR, NMR and GC-MS Analyses- (v.3). Nat Prec (2011). https://doi.org/10.1038/npre.2011.6201.3

Download citation

  • Received: 14 November 2011

  • Accepted: 14 November 2011

  • Published: 14 November 2011

  • DOI: https://doi.org/10.1038/npre.2011.6201.3

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

Keywords

  • Soybean Composition Database
  • bioinformatics
  • Plant biology
  • Molecular Biology
  • soybean genetics
  • chemical composition analysis
  • NIR
  • NMR
  • GC-MS
  • FCS
  • FCCS
  • single-molecule and single-cell microspectroscopy detection
  • Nanotechnology
  • micro- and nano- structures
Download PDF

Advertisement

Explore content

  • Research articles
  • News & Comment
  • Sign up for alerts
  • RSS feed

About the journal

  • Journal Information

Search

Advanced search

Quick links

  • Explore articles by subject
  • Find a job
  • Guide to authors
  • Editorial policies

Nature Precedings (Nat Preced)

nature.com sitemap

About Nature Portfolio

  • About us
  • Press releases
  • Press office
  • Contact us

Discover content

  • Journals A-Z
  • Articles by subject
  • protocols.io
  • Nature Index

Publishing policies

  • Nature portfolio policies
  • Open access

Author & Researcher services

  • Reprints & permissions
  • Research data
  • Language editing
  • Scientific editing
  • Nature Masterclasses
  • Research Solutions

Libraries & institutions

  • Librarian service & tools
  • Librarian portal
  • Open research
  • Recommend to library

Advertising & partnerships

  • Advertising
  • Partnerships & Services
  • Media kits
  • Branded content

Professional development

  • Nature Awards
  • Nature Careers
  • Nature Conferences

Regional websites

  • Nature Africa
  • Nature China
  • Nature India
  • Nature Japan
  • Nature Middle East
  • Privacy Policy
  • Use of cookies
  • Legal notice
  • Accessibility statement
  • Terms & Conditions
  • Your US state privacy rights
Springer Nature

© 2025 Springer Nature Limited

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing