The combined use of ¹H and 2D NMR‐based metabolomics and chemometrics for non‐targeted screening of biomarkers and identification of reconstituted milk

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 (1H) 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 R2(Y) and Q2 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

Comparative metabolite profiling of raw milk from subclinical and clinical mastitis cows using 1H‐NMR combined with chemometric analysis

“…R 2 and Q 2 values not less than 0.5 suggest a robust model with predictive reliability (Brereton, 2007). Finally, variable important in projection (VIP) scores with a value greater than 1.0 were used to screen out the discriminant metabolites (Cui et al ., 2019). An overall PLS‐DA score plot was constructed with a prediction accuracy of 59.25%, R 2 = 0.813 and Q 2 = 0.602 (Fig.…”

“…The quality of PLS‐DA model was assessed by leave‐one‐out cross validation (LOOCV) method and expressed by the prediction accuracy (%), the sum of squares captured by the model ( R 2 ) and the cross‐validated R 2 ( Q 2 ) values. Finally, metabolites with variable importance in projection (VIP) score > 1.0 and P < 0.05 were considered to be accountable for the discrimination (Cui et al ., 2019).…”

Changes in Bovine Colostrum Metabolites during Early Postpartum Period Revealed by 1H-NMR Metabolomics Approach

“…Heat-map visualization combined with Pearson's correlation-based hierarchical clustering (HCA) and partial least-squares−discriminant analysis (PLS-DA) was performed using MetaboAnalyst 4.0 software (www.metaboanalyst.ca). The quality of the model was expressed by R 2 (accuracy) and Q 2 values (predictability) (Cui et al, 2019). Variable important in projection (VIP) scores with a value greater than 1.0 were used to screen out potential biomarker metabolites accountable for the discrimination (Cui et al, 2019).…”

“…The quality of the model was expressed by R 2 (accuracy) and Q 2 values (predictability) (Cui et al, 2019). Variable important in projection (VIP) scores with a value greater than 1.0 were used to screen out potential biomarker metabolites accountable for the discrimination (Cui et al, 2019).…”

Fraud in Animal Origin Food Products: Advances in Emerging Spectroscopic Detection Methods over the Past Five Years

“…Yogurt and cheese Species identification Front-face fluorescence PLS-DA and PLSR [17] Raw milk Detection of adulterants Time Domain NMR PCA, PLS, and SIMCA [257] Milk powder Detection of adulterants 1 H NMR PCA and Conformity Index [78] Ultra-heat-treated bovine milk Detection of adulterants 1 H and 2D NMR PLS-DA [258] Goat milk Detection of adulterants FT-NIR (10000-4000 cm −1 ) PCA, Q-control, k-NN, SIMCA, and PLS-DA [255] Milk powder Detection of adulterants NIR (850-2499.5 nm) PLSR [259] Dairy Raman spectroscopy is another vibrational spectroscopic technique that has been widely investigated for adulteration purposes. For example, a portable Raman spectrometer was employed to detect melamine, dicyandiamide, urea, ammonium sulfate, and sucrose adulteration of milk.…”