Speciation and milk adulteration analysis by rapid ambient liquid MALDI mass spectrometry profiling using machine learning

Abstract Growing interest in food quality and traceability by regulators as well as consumers demands advances in more rapid, versatile and cost-effective analytical methods. Milk, as most food matrices, is a heterogeneous mixture composed of metabolites, lipids and proteins. One of the major challe...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Cristian Piras, Oliver J. Hale, Christopher K. Reynolds, A. K. Jones, Nick Taylor, Michael Morris, Rainer Cramer
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/e10aab61123d4cd2a4be27a0b138fb74
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:e10aab61123d4cd2a4be27a0b138fb74
record_format	dspace
spelling	oai:doaj.org-article:e10aab61123d4cd2a4be27a0b138fb742021-12-02T14:27:02ZSpeciation and milk adulteration analysis by rapid ambient liquid MALDI mass spectrometry profiling using machine learning10.1038/s41598-021-82846-52045-2322https://doaj.org/article/e10aab61123d4cd2a4be27a0b138fb742021-02-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-82846-5https://doaj.org/toc/2045-2322Abstract Growing interest in food quality and traceability by regulators as well as consumers demands advances in more rapid, versatile and cost-effective analytical methods. Milk, as most food matrices, is a heterogeneous mixture composed of metabolites, lipids and proteins. One of the major challenges is to have simultaneous, quantitative detection (profiling) of this panel of biomolecules to gather valuable information for assessing food quality, traceability and safety. Here, for milk analysis, atmospheric pressure matrix-assisted laser desorption/ionization employing homogenous liquid sample droplets was used on a Q-TOF mass analyzer. This method has the capability to produce multiply charged proteinaceous ions as well as highly informative profiles of singly charged lipids/metabolites. In two examples, this method is coupled with user-friendly machine-learning software. First, rapid speciation of milk (cow, goat, sheep and camel) is demonstrated with 100% classification accuracy. Second, the detection of cow milk as adulterant in goat milk is shown at concentrations as low as 5% with 92.5% sensitivity and 94.5% specificity.Cristian PirasOliver J. HaleChristopher K. ReynoldsA. K. JonesNick TaylorMichael MorrisRainer CramerNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Cristian Piras Oliver J. Hale Christopher K. Reynolds A. K. Jones Nick Taylor Michael Morris Rainer Cramer Speciation and milk adulteration analysis by rapid ambient liquid MALDI mass spectrometry profiling using machine learning
description	Abstract Growing interest in food quality and traceability by regulators as well as consumers demands advances in more rapid, versatile and cost-effective analytical methods. Milk, as most food matrices, is a heterogeneous mixture composed of metabolites, lipids and proteins. One of the major challenges is to have simultaneous, quantitative detection (profiling) of this panel of biomolecules to gather valuable information for assessing food quality, traceability and safety. Here, for milk analysis, atmospheric pressure matrix-assisted laser desorption/ionization employing homogenous liquid sample droplets was used on a Q-TOF mass analyzer. This method has the capability to produce multiply charged proteinaceous ions as well as highly informative profiles of singly charged lipids/metabolites. In two examples, this method is coupled with user-friendly machine-learning software. First, rapid speciation of milk (cow, goat, sheep and camel) is demonstrated with 100% classification accuracy. Second, the detection of cow milk as adulterant in goat milk is shown at concentrations as low as 5% with 92.5% sensitivity and 94.5% specificity.
format	article
author	Cristian Piras Oliver J. Hale Christopher K. Reynolds A. K. Jones Nick Taylor Michael Morris Rainer Cramer
author_facet	Cristian Piras Oliver J. Hale Christopher K. Reynolds A. K. Jones Nick Taylor Michael Morris Rainer Cramer
author_sort	Cristian Piras
title	Speciation and milk adulteration analysis by rapid ambient liquid MALDI mass spectrometry profiling using machine learning
title_short	Speciation and milk adulteration analysis by rapid ambient liquid MALDI mass spectrometry profiling using machine learning
title_full	Speciation and milk adulteration analysis by rapid ambient liquid MALDI mass spectrometry profiling using machine learning
title_fullStr	Speciation and milk adulteration analysis by rapid ambient liquid MALDI mass spectrometry profiling using machine learning
title_full_unstemmed	Speciation and milk adulteration analysis by rapid ambient liquid MALDI mass spectrometry profiling using machine learning
title_sort	speciation and milk adulteration analysis by rapid ambient liquid maldi mass spectrometry profiling using machine learning
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/e10aab61123d4cd2a4be27a0b138fb74
work_keys_str_mv	AT cristianpiras speciationandmilkadulterationanalysisbyrapidambientliquidmaldimassspectrometryprofilingusingmachinelearning AT oliverjhale speciationandmilkadulterationanalysisbyrapidambientliquidmaldimassspectrometryprofilingusingmachinelearning AT christopherkreynolds speciationandmilkadulterationanalysisbyrapidambientliquidmaldimassspectrometryprofilingusingmachinelearning AT akjones speciationandmilkadulterationanalysisbyrapidambientliquidmaldimassspectrometryprofilingusingmachinelearning AT nicktaylor speciationandmilkadulterationanalysisbyrapidambientliquidmaldimassspectrometryprofilingusingmachinelearning AT michaelmorris speciationandmilkadulterationanalysisbyrapidambientliquidmaldimassspectrometryprofilingusingmachinelearning AT rainercramer speciationandmilkadulterationanalysisbyrapidambientliquidmaldimassspectrometryprofilingusingmachinelearning
_version_	1718391341641105408

Speciation and milk adulteration analysis by rapid ambient liquid MALDI mass spectrometry profiling using machine learning

Ejemplares similares