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Flaxseed oil is an important source of vegetable oil with a polyunsaturated fatty acid. It is significant to establish a method to quickly identify adulterated flaxseed oil. In the present study, the qualitative and quantitative analysis of phytosterol of flaxseed oil from different varieties and different production areas in the Qinghai area was first performed by gas chromatography-mass spectrometry (GC-MS) and the phytosterol standard profile of flaxseed oil was established. Then, a combination of similarity evaluation and cluster analysis was used to distinguish pure flaxseed oil from flaxseed oil adulterated with concentrations of 10-50% rapeseed oil, peanut oil, sunflower oil, and sesame oil, and discriminant analysis was used to identify the types of adulterated flaxseed oil. The results showed that similarity evaluation combined with cluster analysis can distinguish pure and adulterated flaxseed oil when the concentration of the adulterant was greater than 10%. Discriminant analysis models accurately identified the types of adulterating oil in flaxseed oil when the concentration of rapeseed, peanut, or sunflower oil was greater than 20%, and that of sesame oil was greater than 30%. This study shows that the determination of the phytosterol composition and chemometrics is a valuable tool to evaluate the purity of flaxseed oil.

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Edible bird's nest (EBN) is a high-value health food with various nutrients and bioactive components. With increasing demand for EBN, they are often adulterated with cheaper ingredients or falsely labeled by the origin information, thus harming consumer interests. In this study, high- and low-field nuclear magnetic resonance (HF/LF-NMR) technology combined with multivariate statistical analysis was used to identify the geographical marker of EBN from different origins and authenticate the adulterated EBN with various adulterants at different adulteration rates. Authentic EBN samples from Malaysia were used to simulate adulteration using gelatin (GL), agar (AG) and starch (ST) at 10 %, 20 %, 40 %, 60 %, 80 %, and 100 % w/w, respectively. The results showed significant differences in composition among EBN from different origins, with isocaproate and citric acid serving as geographical markers for Malaysia and Vietnam, respectively. Leucine, glutamic acid, and N-acetylglycoprotein serving as geographical markers for Indonesia. In addition, PLS model further verified the accuracy of origin identification of EBN. The LF-NMR results of adulteration EBN showed a linear correlation between the transverse relaxation (T2, S2) and the adulterated ratio. The OPLS-DA based on T2 spectra could accurately identify authentic EBN from adulterated with GL, AG and ST at 40 %, 20 %, and 20 %, respectively. Fisher discrimination model was able to differentiate at 20 %, 20 %, and 40 %, respectively. These results show that the 1H NMR combined with multivariate statistical analysis method could be a potential tool for the detection of origin and adulteration of EBN.

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Due to the similar chemical structures and physicochemical properties, it is challenging to distinguish dextran, maltodextrin, and soluble starch from the polysaccharide products of plant origin, such as Lycium barbarum polysaccharides (LBPs). Using the first-order derivatives of Fourier-transformed infrared spectroscopy (FTIR, wave range 1800-400 cm-1), this study proposed a two-step pipeline to identify dextran, maltodextrin, and soluble starch from adulterated LBPs samples qualitatively and quantitatively. We applied principal component analysis (PCA) to reduce the dimensionality of FTIR features. For the qualitative step, a set of machine learning models, including logistic regression, support vector machine (SVM), Naïve Bayes, and partial least squares (PLS), were used to classify the adulterants. For the quantitative step, linear regression, LASSO, random forest, and PLS were used to predict the concentration of LBPs adulterants. The results showed that logistic regression and SVM are suitable for classifying adulterants, and random forests is superior for predicting adulterant concentrations. This would be the first attempt to discriminate the adulterants from the polysaccharide's product of plant origin. The proposed two-step methods can be easily extended to other applications for the quantitative and qualitative detection of samples from adulterants with similar chemical structures.

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The quality of Panax Linn products available in the market is threatened by adulteration with different Panax species, such as Panax quinquefolium (PQ), Panax ginseng (PG), and Panax notoginseng (PN). In this paper, we established a 2D band-selective heteronuclear single quantum coherence (bs-HSQC) NMR method to discriminate species and detect adulteration of Panax Linn. The method involves selective excitation of the anomeric carbon resonance region of saponins and non-uniform sampling (NUS) to obtain high-resolution spectra in less than 10 min. The combined strategy overcomes the signal overlap limitation in 1H NMR and the long acquisition time in traditional HSQC. The present results showed that twelve well-separated resonance peaks can be assigned in the bs-HSQC spectra, which are of high resolution, good repeatability, and precision. Notably, the identification accuracy of species was found to be 100% for all tests conducted in the present study. Furthermore, in combination with multivariate statistical methods, the proposed method can effectively determine the composition proportion of adulterants (from 10% to 90%). Based on the PLS-DA models, the identification accuracy was greater than 80% when composition proportion of adulterants was 10%. Thus, the proposed method may provide a fast, practical, and effective analysis technique for food quality control or authenticity identification.

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High-performance liquid chromatography-quadrupole-time-of-flight mass spectrometry (HPLC/Q-TOF MS) was used to analyze 23 phenolic compounds in Chinese poplar propolis, Brazil green propolis, and poplar gum. Propolis and poplar gum samples were dissolved in methanol-water (1:1, v/v) and filtered by 0.45 µm organic phase filtration membrane. The separation was carried out in an Agilent Eclipse Plus C18 column with gradient elution using acetoni-trile and 0.1% (volume percentage) formic acid solution as the mobile phases. The compounds were detected using positive ion electrospray ionization in full scan mode (m/z 100-1000). The quantification analysis was performed by the external standard method. The results showed that all the compounds were linear, with correlation coefficients>0.99, in the range of 10-20 µg/L. The limits of detection and limits of quantification for tangeretin and formononetin were 0.2 and 1 µg/L, respectively, and those for the other compounds were 2 and 10 µg/L, respectively. At the spiked levels of 10, 25, and 50 mg/kg, the recoveries of all the compounds ranged from 70.2% to 122.6%, with relative standard deviations of less than 10%. Salicin, cinnamic acid, caffeic acid, and coumaric acid could be used as markers for detecting adulteration in Chinese poplar propolis, while caffeic acid, ferulic acid, chrysin, caffeic acid phenethyl ester, pinocembrin, galangin, coumaric acid, isorhamnetin, kaempferide, and arte-pillin C could be used as markers for identifying Chinese poplar propolis and Brazil green propolis. The results presented in this paper may be helpful in quality control of propolis products.

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