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

机译:高分辨率核磁共振(NMRS)和近红外光谱(NIRS)测定大豆种子中的大豆油,蛋白质和氨基酸残基

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摘要

A detailed account is 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 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.
机译:详细介绍了我们的高分辨率核磁共振(HR-NMR)和近红外(NIR)校准模型,方法和验证步骤,以及大量的大豆种子成分分析。基于HR-NMR和分析化学参考数据,针对成熟大豆和大豆胚芽中的油和12个氨基酸残基开发了NIR校准。这是我们第一份HR-NMR测定整个大豆种子中蛋白质氨基酸谱的报告,而无需从种子中提取蛋白质。我们发现,通过对我们广泛的NIR光谱数据进行偏最小二乘回归(PLS-1)分析可获得油和蛋白质校准的最佳结果,这些分析是通过DA7000双二极管阵列(Si和InGaAs检测器)仪器或配备了几个带有积分球/ InGaAs检测器附件的傅立叶变换近红外(FT-NIR)光谱仪。为了将散装大豆样品的校准模型扩展到单粒大豆种子的分析,我们通过散装,单粒和粉末状大豆种子的光谱去卷积详细分析了所有主要大豆成分的组分近红外光谱。通过计算光谱的一阶导数和乘积散射校正(MSC),分别校正了近红外光谱中的基线变化和光散射效应。单个大豆种子的NIR光谱与散装全大豆的光谱大致相似,不同之处在于单个大豆NIR光谱在950至1,000 nm范围内有较小的峰值。根据以前对大豆大体积近红外光谱校准的经验,选择了PLS-1校准模型用于蛋白质,油和水分的校准,这是我们为单一大豆种子分析开发的。为了提高我们使用PLS-1模型进行标定的可靠性和鲁棒性,我们使用了具有广泛大豆成分组成的标准样品:蛋白质从34%至55%,油脂从11%至22%,大豆从2% %至16%的水分。此类校准的特点是所有主要大豆成分的标准差低,相关度高。此外,我们获得了成熟大豆胚选定区域的高分辨率NIR化学图像,从而可以定量分析油和蛋白质成分。高分辨率FT-NIR显微技术的最新发展将NIR灵敏度范围扩展到了皮克级,在完整大豆种子和胚中的成分分布中,亚微米级的空间分辨率。对于需要快速和超灵敏分析的生物技术应用(例如,与基因组学和蛋白质组学研究中涉及高含量微阵列的技术相关的应用),此类开发可能具有重要意义。 FT-NIR显微技术的其他重要应用是在旨在预防癌症,通过NIR荧光早期发现肿瘤以及通过超分辨率显微镜/显微技术鉴定体内单个癌细胞或单个病毒颗粒的生物医学研究中设想的。

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