lc-hrms (4)

 

10929285292?profile=RESIZE_584xThis paper describes a new non-targeted method (NTM) for distinguishing spelt from wheat, which aids in food fraud detection and authenticity testing. A spectral fingerprint was obtained for several cultivars of spelt and wheat using liquid chromatography coupled high-resolution mass spectrometry (LC-HRMS). Neural network (CNN) models are built using a nested cross validation (NCV) approach neural network (CNN) models are built using a nested cross validation (NCV) approach by appropriately training them using a calibration set comprising duplicate measurements of eleven cultivars of wheat and spelt, each. The CNNs automatically learn patterns and representations to best discriminate tested samples into spelt or wheat. The method was validated using artificially mixed spectra from samples of processed spelt bread and flour, comprising of eleven untypical spelt, and six old wheat cultivars, which were not part of model building. The results showed that based on the same chemometric approach, the non-targeted method is reliable enough to be used on a wider range of cultivars and their mixes.

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10479696676?profile=RESIZE_400xIn this paper, a quantitative method based on LC-HRMS (liquid chromatography-high resolution mass spectrometry) for the simultaneous detection and differentiation of milk type from eight different animal species (namely: cow, water buffalo, wild yak, goat, sheep, donkey, horse, and camel) was developed by detecting species specific peptides originating from casein. The use of stable isotope labelled peptides was adopted in the developed method in order to increase its accuracy and precision. The developed method was validated in-house in terms of sensitivity, accuracy, and precision. It was also used in a market survey of 46 commercial minor species’ milk products, in which 15 samples were deemed to be mislabelled.

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9654883498?profile=RESIZE_584x

There has been neither analytical methods nor specific parameters to  define milk freshness, which is an important consumer and quality issue. This study identified 8 marker molecules as indicators of milk aging, using liquid chromatography–high-resolution mass spectrometry (LC-HRMS) followed by chemometric analysis. Thirty high-quality pasteurised liquid milk samples were collected directly from a production site over a 6 week period and analysed immediately, and after storage at 2 to 8°C for 7 days to determine the markers and establish the model. The markers were then validated by challenging the model with a set of 10 milk samples, not previously analysed, and were able to clearly distinguish between the fresh pasteurised milk samples (0 days) and the stored samples (7 days). 

You can read the full paper before the 16 November 2021, and the abstract after this date.

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3925480647?profile=RESIZE_710xThe assessment of durum wheat geographical origin is an important and emerging challenge, due to the added value that a claim of origin could provide to the raw material itself, and subsequently to the final products (i.e. pasta). As an alternative to the use of stable isotopes and trace elements to determine geographic origin, Italian researchers used non-targeted high resolution mass spectrometry (LC-HRMS) to select chemical markers related to the geographical origin of durum wheat. Durum wheat samples from the 2016 wheat harvest were used to set up the model and to select the markers, while samples from the 2018 harvest were used for model and metabolomic markers validation. Different geographies across different continents were used in the sample set, so that it is now possible to discriminate between Italian, European and Non-European durum wheat samples.

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