Multivariate statistical analysis using FT-IR spectrum data of Soybean Core Collection in Korea
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등록일 : 2024.02.13
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To determine whether FT-IR spectral analysis based on multivariate analysis for whole cell extracts can be used to discriminate between Soybean plants seed at the metabolic level, leaves of 383 soybean core collection plants were subjected to Fourier transform infrared(FT-IR) spectroscopy. FT-IR spectral data from leaves were analyzed by principal component analysis (PCA), partial least square discriminant analysis (PLS-DA) and hierarchical clustering analysis (HCA). FT-IR spectra confirmed typical spectral differences between the frequency regions of 1,700 - 1,500, 1,500 - 1,300 and 1,100 - 950 cm-1, respectively. These spectral regions reflect the quantitative and qualitative variations of amide I, II from amino acids and proteins (1,700 - 1,500cm-1), phosphodiester groups from nucleic acid and phospholipid (1,500 - 1,300cm-1) and carbohydrate compounds (1,100 - 950cm-1). PCA revealed separate clusters that corresponded to their species relationship. Thus, PCA could be used to distinguish between soybean with different metabolite contents. PLS-DA showed similar metabolite contents of soybean. Further more these metabolic discrimination systems could be used for the rapids election and classification of useful soybean cultivars.
대한민국 공식 전자정부 누리집입니다.
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