non-targeted analysis (6)

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Here, a biomarker-free detection assay was developed using an optical nanosensor array to aid in the food safety of citrus juices.

Researchers have coupled machine learning capability of their computational process named algorithmically guided optical nanosensor selector (AGONS) with the fluorescence data collected using their nanosensor array, in a biomarker-free detection assay, to construct a predictive model for citrus juice authenticity. 

Over 707 measurements of pure and adulterated citrus juices were collected for prediction. Overall, the approach achieved above 90% accuracy on three data sets in discriminating three pure citrus fruit juices, artificially sweetened tangerine juice with various concentrations of corn syrup, and juice-to-juice dilution of orange juice using apple juice. 

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This review examines the potential of non-targeted metabolomic analysis to assess food authenticity. It looks at range of products, which includes wine, rice, olive oil, spices, and honey because they are regarded as the most vulnerable to fraud. The identification of biomarkers  for geographical origin is central theme of the review.

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9242579475?profile=RESIZE_400xHerbs and spices are vulnerable to adulteration, and the problem has only been compounded by the Covid pandemic. However, NGS is giving food manufacturers, retailers, and regulators, the tools they need to help combat on food fraud. Rather than returning a simple positive/ negative result, NGS reliably detects and reports multi-species DNA in even the most complex of samples, including herbs and spices, which allows food analyst laboratories to screen for thousands of species in one test, and get same-day results.

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Using NMR to Authenticate Spanish Wine

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This article reports a recent webinar to discuss the role of NMR in the non-targeted authenticity analysis of wine, and in particular Spanish wine. The NMR analysis is able to identify and quantify several hundred compounds present in the wine. Reference databases have been built up of these compound profiles using authentic wine, and these are used on wine samples to verify whether they are authentic or not. The method has been adopted by the  Estación Enológica de Haro (EEH) part of the Institute of Vine and Wines Sciences in La Rioja, which serves the wine industry across Spain, and analyses 25,000 samples annually and conducts around 263,000 analyses every year from private clients.  

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This method has been developed so that it can differentiate between a slaughtering method that conforms with Islamic rights, and therefore can be certified as Halal, and one which does not.. Kosher slaughter and Islamic rights, Zabiha (ZA) slaughtering procedure involves the severing of the poultry's throat with a single stroke of a sharp knife thus cutting a carotid artery, jugular vein, windpipe, and esophagus without injuring the spinal cord. Non-Zabiha (NZ) slaughter may involve completely cutting off the neck of the animal during slaughter, and hence detaching the spinal cord. Liquid chromatography-electrospray ionization-tandem mass spectrometry (LC-ESI-MS/MS) based non-targeted metabolomics of chicken meat samples were evaluated to differentiate meat samples based on slaughtering methods. Forty samples were grouped into equal numbers of Zabiha (cutting neck without detaching spinal cord) and Non-Zabiha (completely detaching neck). A volcano plot revealed at least 150 features found significantly different between the two groups having ≥ 2-fold changes in intensities with p-values ≤ 0.05. Among them 5 identified metabolites and 25 unidentified metabolites have clear differences in peak intensities. After chemometric analysis, the 5 metabolites were considered as potentially significant markers to differentiate between the two methods of slaughter.

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3877560624?profile=RESIZE_710x Olive oil, especially extra virgin olive oil (EVOO), has been the subject of many recent scandals of adulteration and fraud. Spanish researchers have proposed a new analytical platform by coupling electrospray ionisation (ESI) with differential mobility analysis (DMA), and mass spectrometry (MS) for the analysis of olive oils based on the information obtained from the chemical fingerprint (non-targeted analyses). Two approaches for preparing the olive oil samples were proposed: (i) sample dilution and (ii) liquid–liquid extraction (LLE). In order to test the feasibility of the method, 30 olive oil samples in 3 different categories (extra vigin -EVOO, virgin -VOO, lampante - LOO) were analysed, using 21 of them to elaborate the classification model and the remaining 9 to test it (blind samples). After applying chemometrics, the overall success rate of the classification to differentiate between the EVOO, VOO), and LOO was 89% for the LLE samples and 67% for the diluted samples. However, combining both methods, the ability to differentiate EVOO from lower-quality oils (VOO and LOO), and the edible oils (EVOO and VOO) from nonedible oil (LOO) was 100%. The results show that ESI-DMA-MS has potential to become an effective tool for the olive oil sector.

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