The combined use of 1H and 2D NMR‐based metabolomics and chemometrics for non‐targeted screening of biomarkers and identification of reconstituted milk. (12th August 2019)

• Record Type: Journal Article
• Authors: Cui, Jing; Zhu, Dan; Su, Meicheng; Tan, Dongfei; Zhang, Xia; Jia, Man; Chen, Gang
• Is Part Of: Journal of the science of food and agriculture. Volume 99:Number 14(2019)
• Page Start: 6455
• Page End: 6461
• Publication Date: 2019-08-12
• Subjects: proton nuclear magnetic resonance (NMR) -- ultra‐heat treatment (UHT) milk -- reconstituted milk -- identification -- biomarkers -- non‐targeted analysis; Food -- Periodicals; Agriculture -- Periodicals; 664
• DOI: 10.1002/jsfa.9924
• Languages: English
• ISSNs: 0022-5142

Abstract

Abstract: BACKGROUND: The illegal undeclared addition of reconstituted milk powder to ultra‐heat treated (UHT) milk to lower production costs is an example of economically motivated adulteration. This activity not only defrauds consumers but also places honest traders at a disadvantage, which could damage the reputation of milk producers and reduce the integrity of the markets. In this research, a non‐targeted analytical strategy that combines proton ( 1 H) nuclear magnetic resonance (NMR) spectroscopy with a chemometrics data mining tool was developed for the authentication of bovine UHT milk. RESULTS: Unsupervised principal component analysis was used to distinguish UHT and tap‐water‐reconstituted powdered milk. Partial least squares‐discriminant analysis (PLS‐DA) with R 2 (Y) and Q 2 equal to 0.859 and 0.748, respectively, was used to differentiate UHT and reconstituted milk samples. Three compounds were selected as biomarkers to distinguish UHT and reconstituted milk and identified according to the standard NMR‐spectra database. Finally, a PLS‐DA model was established, according to the characteristic spectral bands, to identify UHT milk and reconstituted milk. CONCLUSION: This procedure demonstrated the feasibility of using non‐targeted NMR profiling combined with chemometric analysis to combat mislabeling and fraudulent practices in milk production. © 2019 Society of Chemical Industry