4.7 Article

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

期刊

MICROCHEMICAL JOURNAL
卷 157, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.microc.2020.104933

关键词

Lemon; Eureka variety; Peel; NTME-GC-MS; VOCs; Geographical origin; Multivariate statistical analysis

资金

  1. FCT-Fundacao para a Ciencia e a Tecnologia through the CQM Base Fund [UIDB/00674/2020]
  2. FCT-Fundacao para a Ciencia e a Tecnologia through Programmatic Fund [UIDP/00674/2020]
  3. FCT-Fundacao para a Ciencia e a Tecnologia [SFRH/BD/129630/2017]
  4. FCT-Fundacao para a Ciencia e a Tecnologia through Madeira 14-20 Program, project PROEQUIPRAM - Reforco do Investimento em Equipamentos e Infraestruturas Cientificas na RAM [M1420-01-0145-FEDER-000008]
  5. ARDITI - Agencia Regional para o Desenvolvimento da Investigacao Tecnologia e Inovacao [M1420-01-0145-FEDER-000005, M1420 -09-5369-FSE-000001]
  6. Fundação para a Ciência e a Tecnologia [UIDP/00674/2020, SFRH/BD/129630/2017] Funding Source: FCT

向作者/读者索取更多资源

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 fingerprints 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 discrimination 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 experimental design (DoE). Overall, 75 volatile organic compounds (VOCs), belonging to different chemical groups, namely monoterpenes, sesquiterpenes, alcohols and carbonyl compounds, were identified. D-limonene, alpha-pinene, beta-pinene, sabinene, beta-myrcene and gamma-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, alpha-pinene, alpha-thujene, 1-butanol, 2-heptanone, D-limonene, 2-methyl-2-heptenal, nonanal, decanal, 1-octanol, limonene oxide, beta-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.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据