A comprehensive methodology based on NTME/GC-MS data and chemometric tools for lemons discrimination according to geographical origin

• Autor(a) principal: Figueira, José
• Data de Publicação: 2020
• Outros Autores: Porto-Figueira, Priscilla, Pereira, Jorge A. M., Câmara, José S.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10400.13/3867
• topic: 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

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.