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...

Dissecting genomic hotspots underlying seed protein, oil, and sucrose content in an interspecific mapping population of soybean using high‐density linkage mapping

“…The cost‐effective, accurate, and high‐throughput phenotyping for seed composition traits significantly contributed to the acceleration of genetic improvement through molecular breeding approaches. In soybean, major seed composition traits, for example protein, oil, and sucrose, are measured using high‐throughput near‐infrared reflectance (NIR) methods (Baianu et al ., ). The HPLC (high‐performance liquid chromatography) platform is considered more reliable for sucrose content analysis due to its accuracy; however, this platform has limitations to use for high‐throughput assay and also involved higher costs per sample.…”

“…The spectrophotometer was a FOSS NIR System 6500. Two individual samples from each replication of each location were analysed at regular interval to confirm repeatability of measurements (Baianu et al ., ). For the correlation analysis, seed samples of 100 RILs from the experiment grown at the BREC in 2013 and two parents were evaluated on HPLC (Agilent Technologies, Santa Ana, CA) as described by Valliyodan et al .…”

Determination of soybean routine quality parameters using near‐infrared spectroscopy

“…These methods produce highly accurate results, but the analytical processes are time‐consuming and laborious and the chemical reagents that are used contribute to environmental pollution (Liu, ). Alternative rapid and accurate analytical methods are, therefore, urgently needed (Baianu et al., ; Martin, ; Zhu et al., ).…”

“…Near‐infrared spectroscopy (NIRS) is a rapid technique that can be used for the simultaneous detection and analysis of multiple components (Acquah, Via, Billor, Fasina, & Eckhardt, ; Baianu et al., ; Louw & Theron, ; Wehling, Pierce, & Froning, ; Williams, Norris, & Sobering, ). Different chemical components in samples can be rapidly quantified using NIRS by taking advantage of the vibrational absorption modes of the compounds in the NIR region of the spectrum (Martelovidal & Vazquez, ).…”

A novel approach to discriminate transgenic from non-transgenic soybean oil using FT-MIR and chemometrics

“…For some applications, the MSC approach was found to be effective for correcting spectral variations caused by light scattering. As a result of MSC, both the accuracy and reliability of the NIR analysis significantly improved in comparison to calibrations that were based on 'raw' (uncorrected) spectra (Baianu et al, 2004). The central point of OSC is reducing the variation in the X matrix (instrumental response matrix) that is not related to the Y matrix (parameters that are predicted by the model) (Pereira et al, 2008).…”