Classification the geographical origin of corn distillers dried grains with solubles by near infrared reflectance spectroscopy combined with chemometrics: A feasibility study

Xingfan Zhou, Zengling Yang, Simon A. Haughey, Pamela Galvin-King, Lujia Han, Christopher T. Elliott

Research output: Contribution to journalArticlepeer-review

13 Citations (Scopus)

Abstract

In this study, 137 corn distillers dried grains with solubles (DDGS) samples from a range of different geographical origins (Jilin Province of China, Heilongjiang Province of China, USA and Europe) were collected and analysed. Different near infrared spectrometers combined with different chemometric packages were used in two independent laboratories to investigate the feasibility of classifying geographical origin of DDGS. Base on the same dataset, one laboratory developed a partial least square discriminant analysis model and another laboratory developed an orthogonal partial least square discriminant analysis model. Results showed that both models could perfectly classify DDGS samples from different geographical origins. These promising results encourage the development of larger scale efforts to produce datasets which can be used to differentiate the geographical origin of DDGS and such efforts are required to provide higher level food security measures on a global scale.
Original languageEnglish
Pages (from-to)13-18
Number of pages6
JournalFood Chemistry
Volume189
Issue numberSI
Early online date28 Sep 2014
DOIs
Publication statusPublished - 15 Dec 2015

Bibliographical note

ASSET 2014 – Food Integrity and Traceability Conference

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