| Article ID | Journal | Published Year | Pages | File Type | 
|---|---|---|---|---|
| 7590316 | Food Chemistry | 2015 | 6 Pages | 
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.
											Keywords
												
											Related Topics
												
													Physical Sciences and Engineering
													Chemistry
													Analytical Chemistry
												
											Authors
												Xingfan Zhou, Zengling Yang, Simon A. Haughey, Pamela Galvin-King, Lujia Han, Christopher T. Elliott, 
											