1995
DOI: 10.1016/0308-8146(95)93935-k
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Characterisation of flour by means of pattern recognition methods

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Cited by 4 publications
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“…A PCA is used to analyze multivariate data and to generate new sets of variables, these being linear combinations of the original ones. 19 PCA was applied as the pattern recognition unsupervised classification method to identify the properties that underline group differences in terms of bioactive components (oligosaccharides, inositol phosphates, trypsin inhibitors and lectins) for each lentil-based extrudate. PCA transforms the original, measured variables into new uncorrelated variables called principal components (PC).…”
Section: Discussionmentioning
confidence: 99%
“…A PCA is used to analyze multivariate data and to generate new sets of variables, these being linear combinations of the original ones. 19 PCA was applied as the pattern recognition unsupervised classification method to identify the properties that underline group differences in terms of bioactive components (oligosaccharides, inositol phosphates, trypsin inhibitors and lectins) for each lentil-based extrudate. PCA transforms the original, measured variables into new uncorrelated variables called principal components (PC).…”
Section: Discussionmentioning
confidence: 99%