Fatty Acid Profiling of Soybean Cotyledons by Near-Infrared Spectroscopy

Abstract

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.