Determination of Soybean Oil, Protein and Amino Acid Residues in Soybean Seeds by High Resolution Nuclear Magnetic Resonance (NMRS) and Near Infrared (NIRS)

Abstract

A detailed account is here 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. This is our first 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 firstorder 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 ultrasensitive 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 vir...

Effects of type I Diacylglycerol O-acyltransferase (DGAT1) genes on soybean (Glycine max L.) seed composition

“…Seed composition and morphological traits analyses. Seed composition traits were measured using the high-throughput near-infrared reflectance (NIR) method, which is now a common way of measuring seed composition traits in soybean 47,48 . The results of seed composition analyses showed that the seed oil accumulation in transgenic lines of DGAT1-11A-3, DGAT1-11B-1, and DGAT1-15A-5 were decreased by 10 mg/g (by 4.5%), 18 mg/g (8.3%), and 11 mg/g (5.3%), respectively, in comparison with the wild-type, cultivar Jack.…”

Development of a Nuclear Magnetic Resonance Method and a Near Infrared Calibration Model for the Rapid Determination of Lipid Content in the Field Pea (Pisum sativum)

“…The entire spectrum of absorbance was used to generate the partial least squares (PLS) model ( Figure S3 ) for the near infrared analyses. The PLS was calculated over the selected wavelength range of 1100 nm–2500 nm [ 21 , 34 ]. The near infrared spectra were pre-treated mathematically and derivatized.…”

“…NIR spectroscopy is based on the region of the electromagnetic spectrum between visible light and infrared radiation, occurring from approximately 780 nm to 2600 nm [ 21 ]. It involves changes in vibration energies of the molecular bonds O-H, C-H, C-O, and N-H when subjected to NIR frequencies, wherein bonds undergo vibrational stretching and bending [ 22 ].…”

Food, Nutrition and Agrobiodiversity Under Global Climate Change

“…The NIR technology has been applied to predict oil per se and its quality in rapeseed, safflower, and soybean (Tajuddin et al, 2002;Kim et al, 2007;Patil et al, 2010;Rudolphi et al, 2012;Wittkop et al, 2012); fiber fractions in rapeseed (Wittkop et al, 2012); starch, protein, oil, amino acid composition and weight of individual grains in maize (Spielbauer et al, 2009;Tallada et al, 2009;Rosales et al, 2011); stover quality in maize (Melchinger et al, 1986); amino acid composition in soybean (Kovalenko et al, 2006); protein, starch and seed weight in intact seed in common bean (Hacisalihoglu et al, 2010); and for sensing moisture content of in-shell peanut (Sundaram et al, 2012). Baianu et al (2012) developed a high-resolution nuclear magnetic resonance and NIR models that they validated by estimating amino acid profiles of proteins from a large number of single and bulked soybean seeds, without protein extraction from the seed. Using partial least squares regression technique to analyze the NIR spectral data, they found that single soybean seed NIR spectra are broadly similar to those of bulk whole soybeans, with the exception of minor peaks, 950-1000 nm, in single soybean NIR spectra.…”