Scientific Study
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Products: Almonds
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The classification of almonds (Prunus dulcis) by country and variety using UHPLC-HRMS-based untargeted metabolomics.
Authors: Gil Solsona, R., Boix, C., Ibáñez, M., & Sancho, J. V.
- Journals: Food Addit Contam Part A Chem Anal Control Expo Risk Assess
- Pages:
- Year: 2018
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The aim of this study was to use an untargeted UHPLC-HRMS-based metabolomics approach allowing discrimination between almonds based on their origin and variety. Samples were homogenized, extracted with ACN:H2O (80:20) containing 0.1% HCOOH and injected in a UHPLC-QTOF instrument in both positive and negative ionization modes. Principal component analysis (PCA) was performed to ensure the absence of outliers. Partial least squares - discriminant analysis (PLS-DA) was employed to create and validate the models for country (with 5 different compounds) and variety (with 20 features), showing more than 95% accuracy. Additional samples were injected and the model was evaluated with blind samples, with more than 95% of samples being correctly classified using both models. MS/MS experiments were carried out to tentatively elucidate the highlighted marker compounds (pyranosides, peptides or amino acids amongst others). This study has shown the potential of HRMS to perform and validate classification models, also providing information concerning the identification of the unexpected biomarkers which showed the highest discriminant power.