적외선 분광스펙트럼 및 기체크로마토그라피 분석 데이터의 다변량 통계분석을 이용한 대두 종자 지방산 함량예측 = Simultaneous estimation of fatty acids contents from soybean seeds using fourier transform infrared spectroscopy and gas chromatography by multivariate analysis

다국어 초록 (Multilingual Abstract)

The aim of this study was to investigate whetherfourier transform infrared (FT-IR) spectroscopy can beapplied to simultaneous determination of fatty acids contentsin different soybean cultivars. Total 153 lines of soybean(Glycine max Merrill) were examined by FT-IR spectroscopy.
Quantification of fatty acids from the soybean lines wasconfirmed by quantitative gas chromatography (GC) analysis.
The quantitative spectral variation among different soybeanlines was observed in the amide bond region (1,700 ~ 1,500cm-1), phosphodiester groups (1,500 ~ 1,300 cm-1) and sugarregion (1,200 ~ 1,000 cm-1) of FT-IR spectra. The quantitativeprediction modeling of 5 individual fatty acids contents (palmitic acid, stearic acid, oleic acid, linoleic acid, linolenicacid) from soybean lines were established using partial leastsquare regression algorithm from FT-IR spectra. In crossvalidation, there were high correlations (R2≥0.97) betweenpredicted content of 5 individual fatty acids by PLS regressionmodeling from FT-IR spectra and measured content by GC.
In external validation, palmitic acid (R2=0.8002), oleic acid(R2=0.8909) and linoleic acid (R2=0.815) were predictedwith good accuracy, while prediction for stearic acid (R2=0.4598), linolenic acid (R2=0.6868) had relatively loweraccuracy. These results clearly show that FT-IR spectracombined with multivariate analysis can be used to accuratelypredict fatty acids contents in soybean lines. Therefore, wesuggest that the PLS prediction system for fatty acid contentsusing FT-IR analysis could be applied as a rapid and highthroughput screening tool for the breeding for modified Fattyacid composition in soybean and contribute to acceleratingthe conventional breeding.

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