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A comprehensive methodology based on NTME/GC-MS data and chemometric tools for lemons discrimination according to geographical origin
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Advisor(s)
Abstract(s)
In this work we report an innovative and high throughput methodology involving Needle Trap Microextraction
(NTME) combined with GC-MS analyis and chemometric processing, to obtain comprehensive volatile finger prints for authenticity purposes. This approach ewill allow to characterize the volatile composition of lemon
peels (exocarp) (Eureka variety) from different geographical regions of Portugal (mainland and Madeira Island),
Argentine and South Africa as useful tool to identify geographic molecular markers with potential for dis crimination according to their geographical origin. The most important parameters affecting NTME, namely
extraction and headspace volumes, sample temperature and equilibration time, were optimized using an ex perimental design (DoE). Overall, 75 volatile organic compounds (VOCs), belonging to different chemical
groups, namely monoterpenes, sesquiterpenes, alcohols and carbonyl compounds, were identified. D-limonene,
α-pinene, β-pinene, sabinene, β-myrcene and γ-terpinene were the dominant volatiles identified, accounting for
more than 50% of the volatile composition of selected lemons varieties. The VOCs data matrix obtained was
submitted to both supervised (Orthogonal Projections to Latent Structures Discriminant Analysis, OPLS-DA) and
unsupervised (Hierarchical Clustering Analysis, HCA) statistics, allowing to discriminate lemons based on the
volatomic fingerprint of its peel. The VOCs with the larger contribution to the geographical origin classification
included butanal, α-pinene, α-thujene, 1-butanol, 2-heptanone, D-limonene, 2-methyl-2-heptenal, nonanal,
decanal, 1-octanol, limonene oxide, β-caryophyllene and 2,6-dimethyl-2,6-octadiene, suggesting their potential
as geographical markers. This study shows the potential of NTMS/GC-MS combined with multivariate statistical
analysis as a powerful and rapid strategy to obtain volatile fingerprints of different food matrices and support the
certification of their origin and authenticity.
Description
Keywords
Lemon Eureka variety Peel NTME-GC-MS VOCs Geographical origin Multivariate statistical analysis . Faculdade de Ciências Exatas e da Engenharia Centro de Química da Madeira
Citation
Figueira, J. A., Porto-Figueira, P., Pereira, J. A., & Câmara, J. S. (2020). A comprehensive methodology based on NTME/GC-MS data and chemometric tools for lemons discrimination according to geographical origin. Microchemical Journal, 157, 104933. https://doi.org/10.1016/j.microc.2020.104933
Publisher
Elsevier