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

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Title
Simultaneous estimation of fatty acids contents from soybean seeds using fourier transform infrared spectroscopy and gas chromatography by multivariate analysis = 적외선 분광스펙트럼 및 기체크로마토그라피 분석 데이터의 다변량 통계분석을 이용한 대두 종자 지방산 함량예측
Author(s)
Myung Suk Ahn; Eun Yee Jie; S Y Song; J W Ahn; Won Joong JeongSung Ran MinSuk Weon Kim
Bibliographic Citation
Journal of Plant Biotechnology, vol. 42, no. 1, pp. 60-70
Publication Year
2015
Abstract
The aim of this study was to investigate whether fourier transform infrared (FT-IR) spectroscopy can be applied to simultaneous determination of fatty acids contents in 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 was confirmed by quantitative gas chromatography (GC) analysis. The quantitative spectral variation among different soybean lines was observed in the amide bond region (1,700 ? 1,500 cm-1), phosphodiester groups (1,500 ? 1,300 cm-1) and sugar region (1,200 ? 1,000 cm-1) of FT-IR spectra. The quantitative prediction modeling of 5 individual fatty acids contents (palmitic acid, stearic acid, oleic acid, linoleic acid, linolenic acid) from soybean lines were established using partial least square regression algorithm from FT-IR spectra. In cross validation, there were high correlations (R2≥0.97) between predicted content of 5 individual fatty acids by PLS regression modeling 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 predicted with good accuracy, while prediction for stearic acid (R2= 0.4598), linolenic acid (R2=0.6868) had relatively lower accuracy. These results clearly show that FT-IR spectra combined with multivariate analysis can be used to accurately predict fatty acids contents in soybean lines. Therefore, we suggest that the PLS prediction system for fatty acid contents using FT-IR analysis could be applied as a rapid and high throughput screening tool for the breeding for modified Fatty acid composition in soybean and contribute to accelerating the conventional breeding.
Keyword
FT-IR (Fourier transform infrared spectroscopy)GC (Gas-chromatography)PCA (principal component analysis)PLS-DA (partial least square -discriminant analysis)R2 (correlation coefficient)RMSEP (root mean square error of prediction)
ISSN
1229-2818
Publisher
South Korea
DOI
http://dx.doi.org/10.5010/JPB.2015.42.1.60
Type
Article
Appears in Collections:
Jeonbuk Branch Institute > Biological Resource Center > 1. Journal Articles
Division of Biomaterials Research > Plant Systems Engineering Research > 1. Journal Articles
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