Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 496751
Title Targeted and Untargeted Detection of Skim Milk Powder Adulteration by Near-Infrared Spectroscopy
Author(s) Capuano, Edoardo; Boerrigter-Eenling, Rita; Koot, Alex; Ruth, S.M. van
Source Food Analytical Methods 8 (2015)8. - ISSN 1936-9751 - p. 2125 - 2134.
DOI https://doi.org/10.1007/s12161-015-0100-3
Department(s) Food Quality and Design
VLAG
RIKILT - BU Authenticity & Nutrients
Publication type Refereed Article in a scientific journal
Publication year 2015
Keyword(s) Acid whey - Adulteration - Class modelling - Near-infrared spectroscopy - Skim milk powder - Starch
Abstract

In the present study, near-infrared spectroscopy (NIRS) was explored as a fast and reliable screening method for the detection of adulteration of skim milk powder (SMP). Sixty genuine SMP were adulterated with acid whey (1–25 % w/w), starch (2 and 5 %) and maltodextrin (2 and 5 %) for a total of 348 adulterated samples. Two chemometric approaches were employed. In the first approach, an untargeted one class model for genuine skim milk powder was developed by Soft Independent Modelling of Class Analogy. In the second approach, adulterant-specific regression models were developed to assess the amount of each adulterant by partial least square regression and principal component regression. The class modelling approach had the advantage that several adulterants could be detected with the same chemometric model, including situations where multiple adulterants are present in the test sample or where yet unknown adulterants are present. Regression models showed a better sensitivity with genuine SMP samples completely discriminated from samples adulterated with 5 % acid whey and 2 % of starch or maltodextrin. NIRS proved to be a useful tool for the rapid and cost-efficient untargeted and/or targeted detection of adulterations in SMP.

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