Rapid authentication of Chinese oolong teas using atmospheric solids analysis probe-mass spectrometry (ASAP-MS) combined with supervised pattern recognition models

A colorimetric sensor array based on peroxidase activity nanozyme for the highly efficient differential sensing of tea polyphenols and Tieguanyin adulteration

Tieguanyin (TGY) is one of top ten famous teas in China, but in the process of brand building there is the phenomenon of falsehood, thus harming the interests of consumers. To solve theadulterate problem of TGY, a colorimetric sensor array (CSA) based onperoxidase activity of nanozyme was constructed. Nanozymes can catalyze 3,3',5,5'-tetramethylbenzidine (TMB) to 3,3',5,5'-tetramethyl -[1,1'-bis(cyclohexyl)]-2,2',5,5'-tetraene-4,4'-diimine (oxTMB), while the tea polyphenols (TPs) can inhibit this process, and the degree of inhibition varies significantly with the reaction time. We selected two nanozymesand three reaction time points to construct CSA. It can successfully distinguish TPsin TGY. The discriminative analysiscan achieve: (1)distinction between TGY and adulterated tea, (2)discrimination of TGY in various seasons and seasonal adulteration in different degrees. The method constructed in this work is promising for both the class and quality differentiation of TGY and other teas with TPs as the main activity.

Food allergen analysis: A review of current gaps and the potential to fill them by matrix-assisted laser desorption/ionization

Food allergy remains a public health, business, and regulatory challenge. Risk analysis (RA) and risk management (RM) of food allergens are of great importance and analysis for food allergens is necessary for both. The current workhorse techniques for allergen analysis (enzyme linked immunosorbent assay [ELISA] and real-time polymerase chain reaction) exhibit recognized challenges including variable and antibody specific responses and detection of species DNA rather than allergen protein, respectively. Liquid chromatography-tandem mass spectrometry (LC-MS/MS) enables protein identification, with potential for multiplex analysis and traceability to the System of International units (SI), aiding global measurement standardization. In this review, recent literature has been systematically reviewed to assess progress in LC-MS/MS and define the potential and benefits of matrix-assisted laser desorption/ionization-time-of-flight MS (MALDI-ToF-MS) technology for allergen analysis. MALDI-ToF-MS of initially intact protein is already applied to verify in silico-derived peptide sequences for LC-MS/MS analysis. We describe the origins of MALDI and its future perspectives, including affinity bead-assisted assays coupled to MALDI. Based on the proliferation of reliable and reproducible MALDI-based clinical applications, the technique should emulate the detection capability (sensitivity) of established allergen detection techniques, whilst reducing technical support and having equivalent multiplexing potential to competing techniques, for example, LC-MS/MS and ELISA. Although unlikely to offer inherent SI traceability, MALDI-based allergen analysis will complement existing MS approaches for allergens. Affinity bead-MALDI appears capable of higher throughput at lower cost per sample than almost any existing technique, enabling repeated sub-sampling as a way to reduce representative sampling issues.

Atmospheric solids analysis probe-mass spectrometry (ASAP-MS) as a rapid fingerprinting technique to differentiate the harvest seasons of Tieguanyin oolong teas

Atmospheric solids analysis probe-mass spectrometry (ASAP-MS), an ambient mass spectrometry technique, was used to differentiate spring and autumn Tieguanyin teas. Two configurations were used to obtain their chemical fingerprints - ASAP attached to a high-resolution quadrupole time-of-flight mass spectrometer (i.e., ASAP-QTOF) and to a single-quadrupole mass spectrometer (i.e., Radian™ ASAP™ mass spectrometer). Then, orthogonal projections to latent structures-discriminant analysis was conducted to identify features that held promise in differentiating harvest seasons. Four machine learning models - decision tree, linear discriminant analysis, support vector machine, and k-nearest neighbour - were built using these features, and high classification accuracy of up to 100% was achieved. The markers were putatively identified using their accurate masses and MS/MS fragmentation patterns from ASAP-QTOF. This approach was successfully transferred to the Radian ASAP MS, which is more deployable in the field. Overall, this study demonstrated the potential of ASAP-MS as a rapid fingerprinting tool for differentiating spring and autumn Tieguanyin.

Authenticating teas using multielement signatures, strontium isotope ratios, and volatile compound profiling

High value food products are subject to adulterations and frauds. This study aimed to combine, in our knowledge for the first time, inorganic chemical tracers (multi-elements and Sr isotopy) with volatile organic compound (VOCs) to discriminate the geographic origin, the varieties and transformation processes to authenticate 26 tea samples. By measuring Sr isotope ratio using the multi-collector inductively coupled plasma mass spectrometry (MC-ICP-MS), 6 out of 11 regions were successfully discriminated. The combination with the ICP-MS inorganic pattern allowed to discriminate 4 more regions with a significance level of 0.05. VOCs fingerprints, obtained with selected ion flow tube mass spectrometer (SIFT-MS), were not correlated with origin but with the cultivar and transformation processes. Green, oolong, and dark teas were clearly differentiated, with hexanal and hexanol contributing to the discrimination of oxidation levels. With this multi-instrumental approach, it is possible to certify the geographical origin and the tea conformity.

Food metabolomics: Latest hardware-developments for nontargeted food authenticity and food safety testing

The analytical requirements for food testing have increased significantly in recent years. On the one hand, because food fraud is becoming an ever-greater challenge worldwide, and on the other hand because food safety is often difficult to monitor due to the far-reaching trade chains. In addition, the expectations of consumers on the quality of food have increased, and they are demanding extensive information. Cutting-edge analytical methods are required to meet these demands. In this context, non-targeted metabolomics strategies using mass and nuclear magnetic resonance spectrometers (mass spectrometry [MS]) have proven to be very suitable. MS-based approaches are of particular importance as they provide a comparatively high analytical coverage of the metabolome. Accordingly, the efficiency to address even challenging issues is high. A variety of hardware developments, which are explained in this review, have contributed to these advances. In addition, the potential of future developments is highlighted, some of which are currently not yet commercially available or only used to a comparatively small extent but are expected to gain in importance in the coming years.

Distinguishing Different Varieties of Oolong Tea by Fluorescence Hyperspectral Technology Combined with Chemometrics

Oolong tea is a semi-fermented tea that is popular among people. This study aims to establish a classification method for oolong tea based on fluorescence hyperspectral technology(FHSI) combined with chemometrics. First, the spectral data of Tieguanyin, Benshan, Maoxie and Huangjingui were obtained. Then, standard normal variation (SNV) and multiple scatter correction (MSC) were used for preprocessing. Principal component analysis (PCA) was used for data visualization, and with tolerance ellipses that were drawn according to Hotelling, outliers in the spectra were removed. Variable importance for the projection (VIP) > 1 in partial least squares discriminant analysis (PLS−DA) was used for feature selection. Finally, the processed spectral data was entered into the support vector machine (SVM) and PLS−DA. MSC_VIP_PLS−DA was the best model for the classification of oolong tea. The results showed that the use of FHSI could accurately distinguish these four types of oolong tea and was able to identify the key wavelengths affecting the tea classification, which were 650.11, 660.29, 665.39, 675.6, 701.17, 706.31, 742.34 and 747.5 nm. In these wavelengths, different kinds of tea have significant differences (p < 0.05). This study could provide a non-destructive and rapid method for future tea identification.

Fast and eco-friendly method using atmospheric solids analysis probe mass spectrometry to characterize orange varieties

Orange fruit is one of the most popular types of fruit in the world, and its juice is the main product of its processing. This study aimed to evaluate a simple, fast, and eco-friendly methodology, atmospheric solids analysis probe mass spectrometry (ASAP-MS), to assess the chemical profile of four oranges varieties (Valencia, Folha Murcha, Pera, and Iapar). The oranges' varieties were evaluated for the physicochemical composition (extraction yield, pH, total titratable acidity, total soluble solids [TSS], °Brix), ratio (TSS/TA), and bioactive compounds (ASAP-MS analysis). The characterization of oranges resulted in great values of oranges yield according to the varieties (44.00-48.10% [w/w], adequate and characteristic acidity [0.73-1.35%], soluble solids content (10.24-13.80°Brix), pH (3.30-3.96), and ratio (7.59-19.90) level for this fruit. This powerful method showed that all analysis procedures were simple, fast, and easy because there is no need to prepare the sample and the analysis time lasted 2 min. Besides, results obtained exhibited a vast array of chemical groups. Principal component analysis (PCA) defined and distinguished the varieties of the orange. Therefore, ASAP-MS and PCA showed that they are very attractive candidates for routine analysis to monitor the varieties of the orange with its pronounced advantages, besides being contributing to the environment because it does not use any quantities of organic solvents. This methodology was applied for the first time to this type of sample.

A validated method for the rapid quantification of melatonin in over-the-counter hypnotics by the atmospheric pressure solid analysis probe (ASAP)

Melatonin is a hormone that regulates the biological day and night cycle. It is mainly produced by the pineal gland during the night. People suffering from insomnia use it as a soporific drug. The aim of this study was to develop a method for the rapid quantification of melatonin in hypnotics. For that purpose, atmospheric pressure solid analysis probe-assisted mass spectrometry was applied, where no chromatographic separation is needed. Thereby, one single analysis takes less than 1 min. Reference measurements were performed with ultra-high-performance liquid chromatography coupled with a quadrupole-time-of-flight mass spectrometer. Both methods were validated and real sample extracts were tested. The coefficients of determination were above 0.97 for both methods. The limits of detection and quantification were below 1 mg kg^-1. Both methods gave comparable results. Moreover, the content of melatonin differed from the specified value in many samples. The highest and lowest observed deviations were 78% and 1%, respectively.