Abstract
Chemometrics provides statistical methods for the study of joint relationships of intercorrelated biochemical data. Since several variables can be considered simultaneously, generalised interpretations can be made that could not be possible if univariate statistics were applied. Cluster analysis (CA), principal component analysis (PCA) and discriminant analysis (DA) have been widely used in lipid research (Lee D. et al., 1998; Matsumoto M et al., 1997; Stevens J.J. and Jones R.K., 1992; Tsimidou M. et al., 1987). However, we have seen no previous reports involving the use of a chemometrical approach to study the glycerolipid composition of photosynthetic plant tissues.
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© 2003 Springer Science+Business Media Dordrecht
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Rizov, I., Doulis, A. (2003). Characterization of Transgenic Maize Engineered with Antisense FAD2 cDNA by Chemometrical Analysis of Glycerolipids. In: Murata, N., Yamada, M., Nishida, I., Okuyama, H., Sekiya, J., Hajime, W. (eds) Advanced Research on Plant Lipids. Springer, Dordrecht. https://doi.org/10.1007/978-94-017-0159-4_28
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DOI: https://doi.org/10.1007/978-94-017-0159-4_28
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