Spectroscopic non-targeted methods are gaining ever-growing importance in quality control and authenticity assessment of food products because of their strong potential for identification of specific features of the products by data-driven classifiers. One of the factors hampering the diffusion of spectroscopic non-targeted methods and data-driven classifiers is the lack of harmonized guidelines for their development and validation. In particular, to date, neither conditions to directly compare spectra recorded by different spectrometers nor studies demonstrating the statistical equivalence of the spectra are available. Among the spectroscopic analytical techniques suitable for the development of non-targeted methods, nuclear magnetic resonance (NMR) offers the unique opportunity to generate statistically equivalent signals. In this paper, the feasibility of NMR spectroscopy to generate statistically equivalent NMR signals from a number of different spectrometers was demonstrated for complex mixtures (aqueous extracts of wheat and flour) by organizing an inter-laboratory comparison involving 36 NMR spectrometers. Univariate statistics along with multivariate analysis were exploited to establish unbiased criteria for assessing the statistical equivalence of the NMR signals. The aspects affecting the signal equivalence were investigated, and possible solutions to reduce the extent of the human error were proposed and applied with satisfactory results. This study furnishes the scientific community with an appropriate and easy procedure to validate non-targeted NMR methods and provides error values to be used as a reference for future studies.
A Contribution to the Harmonization of Non-targeted NMR Methods for Data-Driven Food Authenticity Assessment
Arnesano F.;Longobardi F.;
2020-01-01
Abstract
Spectroscopic non-targeted methods are gaining ever-growing importance in quality control and authenticity assessment of food products because of their strong potential for identification of specific features of the products by data-driven classifiers. One of the factors hampering the diffusion of spectroscopic non-targeted methods and data-driven classifiers is the lack of harmonized guidelines for their development and validation. In particular, to date, neither conditions to directly compare spectra recorded by different spectrometers nor studies demonstrating the statistical equivalence of the spectra are available. Among the spectroscopic analytical techniques suitable for the development of non-targeted methods, nuclear magnetic resonance (NMR) offers the unique opportunity to generate statistically equivalent signals. In this paper, the feasibility of NMR spectroscopy to generate statistically equivalent NMR signals from a number of different spectrometers was demonstrated for complex mixtures (aqueous extracts of wheat and flour) by organizing an inter-laboratory comparison involving 36 NMR spectrometers. Univariate statistics along with multivariate analysis were exploited to establish unbiased criteria for assessing the statistical equivalence of the NMR signals. The aspects affecting the signal equivalence were investigated, and possible solutions to reduce the extent of the human error were proposed and applied with satisfactory results. This study furnishes the scientific community with an appropriate and easy procedure to validate non-targeted NMR methods and provides error values to be used as a reference for future studies.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
