Promoting LC-QToF based non-targeted fingerprinting and biomarker selection with machine learning for the discrimination of black tea geographical origin.

Traceability and mislabelling of black tea for their geographical origin is known as a major fraud concern of the sector. Discrimination among various geographical indications (GIs) can be challenging due to the complexity of chemical fingerprints in multi-class metabolomics analysis. In this study, 302 black tea samples from 9 main cultivation GI regions were collected.

Fingerprinting black tea: When spectroscopy meets machine learning a novel workflow for geographical origin identification.

Food fraud, along with many challenges to the integrity and sustainability, threatens the prosperity of businesses and society as a whole. Tea is the second most commonly consumed non-alcoholic beverage globally. Challenges to tea authenticity require the development of highly efficient and rapid solutions to improve supply chain transparency.

MALDI-ToF MS and chemometric analysis as a tool for identifying wild and farmed salmon.

In this study, the difference between wild and farmed salmon production was successfully profiled and differentiated by matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-ToF MS) combined with chemometric analysis. The established method based on multivariate analysis mainly involved principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least squares-discriminant analysis (OPLS-DA) as the screening and verifying tools to provide insights into the distinctive features found in wild and farmed salmon products, respectively. The discrimination between farmed and wild salmon was accomplished with 100% classification accuracy using chemometric models, 100% identification accuracy was also achieved in distinguishing wild Salmo salar and Oncorhynchus nerka samples.

Data fusion and multivariate analysis for food authenticity analysis.

A mid-level data fusion coupled with multivariate analysis approach is applied to dual-platform mass spectrometry data sets using Rapid Evaporative Ionization Mass Spectrometry and Inductively Coupled Plasma Mass Spectrometry to determine the correct classification of salmon origin and production methods. Salmon (n = 522) from five different regions and two production methods are used in the study. The method achieves a cross-validation classification accuracy of 100% and all test samples (n = 17) have their origins correctly determined, which is not possible with single-platform methods.

Multivariate versus machine learning-based classification of rapid evaporative Ionisation mass spectrometry spectra towards industry based large-scale fish speciation.

Detection and prevention of fish food fraud are of ever-increasing importance, prompting the need for rapid, high-throughput fish speciation techniques. Rapid Evaporative Ionisation Mass Spectrometry (REIMS) has quickly established itself as a powerful technique for the instant in situ analysis of foodstuffs. In the current study, a total of 1736 samples (2015-2021) - comprising 17 different commercially valuable fish species - were analysed using iKnife-REIMS, followed by classification with various multivariate and machine learning strategies.

Elementomics combined with dd-SIMCA and K-NN to identify the geographical origin of rice samples from China, India, and Vietnam.

The COVID-19 pandemic has impacted the food industry and consumers, with production gaps, shipping delays, and changes in supply and demand leading to an increased risk of food fraud. Rice has a high probability for adulteration by food fraudsters, being a staple commodity for more than half the global population, making the assessment of geographical origins of rice for authenticity important in terms of protecting businesses and consumers. In this study, we describe ICP-MS elemental profiling coupled with elementomic modelling to identify the geographical indications of Indian, Chinese, and Vietnamese rice.

Authentication of organically grown vegetables by the application of ambient mass spectrometry and inductively coupled plasma (ICP) mass spectrometry; The leek case study.

Health conscious and environmentally aware consumers are purchasing more organically produced foods. They prefer organic fruits and leafy vegetables as these are much less likely to have been exposed to contaminants such as pesticides. The detection of fraudulent activity in this area is difficult to undertake, because many chemical plant protection treatments degrade very quickly or can be washed off to remove evidence of their existence.

Simultaneous Detection of Eight Prohibited Flavor Compounds in Foodstuffs Using Gas Chromatography-Tandem Mass Spectrometry.

A multiflavor detection method, using gas chromatography-triple quadrupole tandem mass spectrometry (GC-MS/MS), has been developed for the simultaneous identification and quantification of eight prohibited flavor compounds in daily foods. Under the optimized extraction conditions, samples were purified directly through membrane filtration. Variables affecting the GC-MS/MS were optimized to obtain better separation.

[Screening of 17 cephalosporin residues in infant formula milk powder by ultra-high performance liquid chromatography-high resolution mass spectrometry].

A method for the simultaneous determination of 17 cephalosporinsin milk powder by ultra-high performance liquid chromatography-quadrupole/electrostatic field orbitrap high resolution mass spectrometry (UHPLC-Q-Orbitrap HRMS) has been developed. After dissolution in water, the homogenized milk powder samples were extracted with acetonitrile to remove impurities such as proteins and the extract was further purified by high-speed centrifugation at low temperature. A C8 chromatographic column was employed to separate the analytes.

A high-throughput screening method of bisphenols, bisphenols digycidyl ethers and their derivatives in dairy products by ultra-high performance liquid chromatography-tandem mass spectrometry.

A simple and universal analytical method based on ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) for high throughput screening of 21 bisphenols, bisphenols digycidyl ethers and their derivatives in dairy products was developed. Response Surface Methodology (RSM) was used to optimize sample preparation conditions based on a quick, easy, cheap, effective, rugged and safe (QuEChERS) method. The analytes were extracted by using 15 mL acetonitrile with 1% acetic acid, and the extracts were further purified by using 190 mg of C18 and 390 mg of PSA.

Simultaneous determination of 22 cephalosporins drug residues in pork muscle using liquid chromatography-tandem mass spectrometry.

A simple, sensitive and reliable analytical method was developed for the simultaneous determination of 22 common cephalosporins from the first generation to the fourth generation in pork muscle by liquid chromatographic-tandem mass spectrometric (LC-MS/MS) method. Under the optimized extraction conditions, samples were directly purified through membrane filtration to separate all 22 cephalosporins and the critical pairs of each parent drug were completely separated. Variables affecting the LC-MS/MS were optimized to get a better separation.