Development of Non-Targeted Mass Spectrometry Method for Distinguishing Spelt and Wheat.

ABSTRACT: Food fraud, even when not in the news, is ubiquitous and demands the development of innovative strategies to combat it. A new non-targeted method (NTM) for distinguishing spelt and wheat is described, which aids in food fraud detection and authenticity testing. A highly resolved fingerprint in the form of spectra is obtained for several cultivars of spelt and wheat using liquid chromatography coupled high-resolution mass spectrometry (LC-HRMS). Convolutional 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 results reveal that the CNNs automatically learn patterns and representations to best discriminate tested samples

SUBMITTER: Nichani K 

PROVIDER: S-EPMC9818861 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature