ArticleScientific reports2022
Ambient mass spectrometry for rapid authentication of milk from Alpine or lowland forage.
Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- A Comprehensive Review of Milk Components: Recent Developments on Extraction and Analysis Methods.Molecules (Basel, Switzerland) · 2025Review
- Effect of Diet on CPFAs Used as Markers in Milk for the Detection of Silage in the Ration of Dairy Cows.Foods (Basel, Switzerland) · 2025Article
- Rapid Assessment of Metabolomic Fingerprinting of Recycled Sunflower By-Products via DART-HRMS.Molecules (Basel, Switzerland) · 2024Article
- A Snapshot, Using a Multi-Omic Approach, of the Metabolic Cross-Talk and the Dynamics of the Resident Microbiota in Ripening Cheese Inoculated withFoods (Basel, Switzerland) · 2024Article
- Applications of ambient ionization mass spectrometry in 2022: An annual review.Analytical science advances · 2023Review
- Seasonal Variation in Raw Milk VOC Profile within Intensive Feeding Systems.Foods (Basel, Switzerland) · 2023Article
- Metabolic signature ofFrontiers in veterinary science · 2023Article
- Authentication of Edible Insects' Powders by the Combination of DART-HRMS Signatures: The First Application of Ambient Mass Spectrometry to Screening of Novel Food.Foods (Basel, Switzerland) · 2022Article
- Rapid, novel screening of toxicants in poison baits, and autopsy specimens by ambient mass spectrometry.Frontiers in chemistry · 2022Article
- Direct Ambient Mass Spectrometry for Food, Beverage, and Agricultural Sample Analysis and Research.Mass spectrometry reviewsReview
- Rapid, Sensitive, and Versatile: A 5-Year Perspective on Applications of Ambient Ionization Mass Spectrometry in Bioanalytical Science.Mass spectrometry reviewsReview
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Metabolomics approaches, such as direct analysis in real time-high resolution mass spectrometry (DART-HRMS), allow characterising many polar and non-polar compounds useful as authentication biomarkers of dairy chains. By using both a partial least squares discriminant analysis (PLS-DA) and a linear discriminant analysis (LDA), this study aimed to assess the capability of DART-HRMS, coupled with a low-level data fusion, discriminate among milk samples from lowland (silages vs. hay) and Alpine (grazing; APS) systems and identify the most informative biomarkers associated with the main dietary forage. As confirmed also by the LDA performed against the test set, DART-HRMS analysis provided an accurate discrimination of Alpine samples; meanwhile, there was a limited capacity to correctly recognise silage- vs. hay-milks. Supervised multivariate statistics followed by metabolomics hierarchical cluster analysis allowed extrapolating the most significant metabolites. Lowland milk was characterised by a pool of energetic compounds, ketoacid derivates, amines and organic acids. Seven informative DART-HRMS molecular features, mainly monoacylglycerols, could strongly explain the metabolomic variation of Alpine grazing milk and contributed to its classification. The misclassification between the two lowland groups confirmed that the intensive dairy systems would be characterised by a small variation in milk composition.
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