کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
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1186512 | 963440 | 2011 | 7 صفحه PDF | دانلود رایگان |

Following the introduction of legal identifiers of geographic origin within Europe, methods for confirming any such claims are required. Spectroscopic techniques provide a method for rapid and non-destructive data collection and a variety of chemometric approaches have been deployed for their interrogation. In this present study, class-modelling techniques (SIMCA, UNEQ and POTFUN) have been deployed after data compression by principal component analysis for the development of class-models for a set of olive oils and honeys. The number of principal components, the confidence level and spectral pre-treatments (1st and 2nd derivative, standard normal variate) were varied, and a strategy for variable selection was tried. Models were evaluated on a separate validation sample set. The outcomes are reported and criteria for selection of the most appropriate models for any given application are discussed.
Journal: Food Chemistry - Volume 125, Issue 4, 15 April 2011, Pages 1450–1456