NMR-based metabolic profiling and discrimination of wild tropical tunas by species, size category, geographic origin, and on-board storage condition
Lamboy, Nathalie Bodin | Amiel, Aurélien | Fouché, Edwin | Sardenne, Fany | Chassot, Emmanuel | Debrauwer, Laurent | Guillou, Hervé | Tremblay-Franco, Marie | Canlet, Cécile
Tunas are among the most traded and valued fish species, and good traceability of tuna products in the world market is needed to protect both consumers and tuna stocks. To that purpose, high-resolution proton nuclear magnetic resonance (¹H NMR) spectroscopy combined with multivariate data analysis was used to investigate the molecular components of the aqueous extract of white and red muscles in three species of wild tropical tuna species, namely yellowfin tuna (Thunnus albacares), skipjack tuna (Katsuwonus pelamis) and bigeye tuna (T. obesus). Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) applied to the processed ¹H NMR spectra showed significant separation according to the species and size category (i.e., small tunas < 80 cm fork length vs large tunas > 80 cm fork length), the storage conditions on-board the purse-seine vessels (i.e., brine- vs deep-freezing), and the geographical origin (i.e., where the tuna was caught: Mozambique Channel vs western-central Indian Ocean). The major groups of metabolites responsible for differentiation in PLS-DA score plots were the dipeptides (anserine, carnosine) and organic acids (lactate, creatine/phosphocreatine) in the white muscle, and the free amino acids, essential nutrients (choline and its derivatives, phosphatidylethanolamine), dipeptides and organic acids in the red muscle. Our results showed that NMR-based metabolomics is a powerful tool to efficiently discriminate specific profiles among wild tuna species, raw muscle tissues, fish storage conditions and tuna geographical origin.
Показать больше [+] Меньше [-]Ключевые слова АГРОВОК
Библиографическая информация
Эту запись предоставил National Agricultural Library