Roberts C A, Ren C, Beuselinck P R, Benedict H R, Bilyeu K
Division of Plant Sciences, University of Missouri, Columbia, Missouri 65211, USA.
Appl Spectrosc. 2006 Nov;60(11):1328-33. doi: 10.1366/000370206778998932.
Genetically improved soybean grain often contains altered fatty acid profiles. Such alterations can have deleterious effects on seed germination and seedling development, making it necessary to monitor fatty acid profiles in follow-up physiological studies. The objective of this research was to quantify the five fatty acids in soybean (Glycine max) cotyledons using near-infrared (NIR) spectroscopy. Soybean cotyledon samples were dried, ground, and scanned with visible and NIR radiation from 400 to 2500 nm, and reflectance was recorded. Samples were also analyzed by gas chromatography (GC) for palmitic, stearic, oleic, linoleic, and linolenic acids and total oil; GC data, expressed as actual concentration and proportion of total oil, were regressed against spectral data to develop calibration equations. Equation statistics indicated that four of the five fatty acids could be predicted accurately by NIR spectroscopy; the fifth fatty acid could be determined by subtraction. Principal component analysis revealed that most of the spectral variation in this population was due to chlorophyll absorbance in the visible region. Therefore, the spectra were trimmed to include the NIR region only (1100-2500 nm), and a second set of equations was developed. Equations based exclusively on NIR spectra had equal or greater precision than equations based on visible and NIR spectra. Principal component analysis and partial least squares analysis revealed that even after trimming, at least 90% of the spectral variation was unrelated to fatty acid, though variation from fatty acid was identified in the second and third principal components. This research provides an NIR method for complete fatty acid profiling of soybean cotyledons. Equations were achieved with NIR spectra only, so spectrophotometers that analyze both the visible and NIR regions are not needed for this analysis. In addition, equations were possible with a 250 mg sample, which is one-tenth the normal sample size for this analysis.
基因改良的大豆籽粒通常含有改变的脂肪酸谱。这种改变可能对种子萌发和幼苗发育产生有害影响，因此在后续的生理学研究中监测脂肪酸谱很有必要。本研究的目的是使用近红外（NIR）光谱法对大豆（Glycine max）子叶中的五种脂肪酸进行定量分析。将大豆子叶样品干燥、研磨，并用400至2500 nm的可见和近红外辐射进行扫描，记录反射率。样品还通过气相色谱（GC）分析棕榈酸、硬脂酸、油酸、亚油酸和亚麻酸以及总油含量；将以实际浓度和总油比例表示的GC数据与光谱数据进行回归分析，以建立校准方程。方程统计表明，五种脂肪酸中的四种可以通过近红外光谱准确预测；第五种脂肪酸可以通过减法确定。主成分分析表明，该群体中大部分光谱变化是由于可见光区域的叶绿素吸收所致。因此，将光谱范围调整为仅包括近红外区域（1100 - 2500 nm），并建立了第二组方程。仅基于近红外光谱的方程比基于可见和近红外光谱的方程具有相同或更高的精度。主成分分析和偏最小二乘分析表明，即使经过调整，至少90%的光谱变化与脂肪酸无关，尽管在第二和第三主成分中发现了脂肪酸引起的变化。本研究提供了一种用于大豆子叶完整脂肪酸谱分析的近红外方法。仅使用近红外光谱就获得了方程，因此该分析不需要同时分析可见光和近红外区域的分光光度计。此外，使用250 mg样品即可获得方程，这是该分析正常样品量的十分之一。
