Meeting the challenge of varietal and geographical authentication of hazelnuts through lipid metabolite fingerprinting
View/Open
Publication date
2024-09-10ISSN
0308-8146
Abstract
Hazelnuts are high-quality products with significant economic importance in many European countries. Their
market price depends on their qualitative characteristics, which are driven by cultivar and geographical origin,
making hazelnuts susceptible to fraud. This study systematically compared two lipidomic fingerprinting strategies for the simultaneous authentication of hazelnut cultivar and provenance, based on the analysis of the
unsaponifiable fraction (UF) and triacylglycerol (TAG) profiles by gas chromatography–mass spectrometry
coupled with chemometrics. PLS-DA classification models were developed using a large sample set with high
natural variability (n = 309) to discriminate hazelnuts by cultivar and origin. External validation results
demonstrated the suitability of the UF fingerprint as a hazelnut authentication tool, both tested models showing a
high efficiency (>94 %). The correct classification rate of the TAG fingerprinting method was lower (>80 %), but
due to its faster analysis time, it is recommended as a complementary screening tool to UF fingerprinting.
Document Type
Article
Document version
Published version
Language
English
Subject (CDU)
633 - Field crops and their production
Pages
8
Publisher
Elsevier
Is part of
Food Chemistry
Citation
Torres-Cobos, B., S.B. Nicotra, M. Rovira, A. Romero, F. Guardiola, A. Tres, and S. Vichi. 2024. “Meeting the Challenge of Varietal and Geographical Authentication of Hazelnuts Through Lipid Metabolite Fingerprinting.” Food Chemistry, 463 (3): 141203. doi: 10.1016/j.foodchem.2024.141203
Grant agreement number
MICINN/Programa Estatal de generación del conocimiento y fortalecimiento científico y tecnológico del sistema I+D+I/CEX2021-001234-M/ES/ /
FEDER/ / /EU/ /
MICIU/Programa Estatal de generación del conocimiento y fortalecimiento científico y tecnológico del sistema I+D+I y Programa Estatal de I+D+I orientada a los retos de la sociedad/PID2020-117701RB-I00/ES/Desarrollo de herramientas de detección de fraudes en frutos secos españoles con alto riesgo de falsificación/TRACENUTS
Program
Fructicultura
This item appears in the following Collection(s)
- ARTICLES CIENTÍFICS [2850]
Except where otherwise noted, this item's license is described as http://creativecommons.org/licenses/by-nc-nd/4.0/