This industrial doctoral thesis aimed to develop a multi-target method, based on ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), capable to detect allergenic traces of different species of nuts and peanuts in a single analysis in complex matrices such as bakery products. Allergy to nuts and peanuts represents a global relevant problem, especially due to the risk of their ingestion as hidden allergens, as a result of cross‐contamination between production lines at industrial level occurring during food manufacturing. Mass spectrometry methods have a very high potential for the identification and quantification of allergenic ingredients at part-per-million (ppm) levels through the detection of peptide markers arising from the artificial digestion of their proteins.

Development of innovative methods for the multiple analysis of allergens in processed foods

Anna Luparelli;Linda Monaci
2022

Abstract

This industrial doctoral thesis aimed to develop a multi-target method, based on ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), capable to detect allergenic traces of different species of nuts and peanuts in a single analysis in complex matrices such as bakery products. Allergy to nuts and peanuts represents a global relevant problem, especially due to the risk of their ingestion as hidden allergens, as a result of cross‐contamination between production lines at industrial level occurring during food manufacturing. Mass spectrometry methods have a very high potential for the identification and quantification of allergenic ingredients at part-per-million (ppm) levels through the detection of peptide markers arising from the artificial digestion of their proteins.
2022
Istituto di Scienze delle Produzioni Alimentari - ISPA
9788875902278
Tree nut allergy;peanut allergy; hidden allergens; LC–MS/MS analysis; nut specific peptide markers
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/549292
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