Use of Fourier transform infrared spectroscopy and partial least squares regression for the detection of adulteration of strawberry purées

James K. Holland, E. Katherine Kemsley, Reginald H. Wilson

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68 Citations (Scopus)

Abstract

Fourier transform infrared (FT-IR) spectroscopy and chemometrics have been combined to detect adulteration in strawberry purées. The mid-IR spectra of 983 fruit purées were used as the data for a partial least squares regression on to a binary dummy variable, that represents two sample types, strawberry or non-strawberry. Three hundred and seventy of the spectra were used as an independent test set, of which 94·3% were correctly assigned by the model. Strawberry purées mixed with certain adulterants were included in the database to demonstrate that the detection of these adulterants was possible using this technique. The potential long-term stability of the model, developed with 1993 and 1994 fruit, was illustrated by analysing the spectra of fruit harvested in 1995, of which 96·6% were correctly assigned. A ‘blind test’ of the model was carried out with a set of 23 fruit purée samples prepared by an industrial collaborator. Twenty two of these samples were classified in accordance with the description of the samples provided by the company. © 1998 SCI.
Original languageEnglish
Pages (from-to)263-269
Number of pages7
JournalJournal of the Science of Food and Agriculture
Volume76
Issue number2
DOIs
Publication statusPublished - Feb 1998

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