作者: Reyhan Selin Uysal , Ismail Hakki Boyaci , Hüseyin Efe Genis , Ugur Tamer
DOI: 10.1016/J.FOODCHEM.2013.06.061
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摘要: Abstract In this study, adulteration of butter with margarine was analysed using Raman spectroscopy combined chemometric methods (principal component analysis (PCA), principal regression (PCR), partial least squares (PLS)) and artificial neural networks (ANNs). Different samples were mixed at various concentrations ranging from 0% to 100% w/w. PCA applied for the classification butters, margarines mixtures. PCR, PLS ANN used detection ratios butter. Models created a calibration data set developed models evaluated validation set. The coefficient determination (R2) values between actual predicted obtained 0.968, 0.987 0.978, respectively. conclusion, combination chemometrics can be testing adulteration.