AgResearch
Browse

File(s) not publicly available

Non-invasive differentiation between fresh and frozen/thawed tuna fillets using near infrared spectroscopy (Vis-NIRS)

journal contribution
posted on 2023-05-03, 13:17 authored by Marlon M.Reis, Ekaitz Martinez, Eduardo Saitua, Raquel Rodriguez, Izaskun Perez, Idoia Olabarrieta
Fresh tuna is an expensive product sold on local and international markets. The use of ultra-low temperatures for frozen fish fillets is a practice found in the market in order to preserve fish quality for longer time. Fillets frozen bellow -60°C do not show visual characteristics changes when thawed, being difficult to differentiate between fresh and frozen/thawed fillets. As fresh tuna is more expensive than thawed one, it is important to prevent that frozen/thawed products are sold as fresh in order to not to deceive the consumer.This study investigates the ability of Visible-Near InfraRed Spectroscopy (Vis-NIRS) to detect whether a sample of tuna is fresh or if it has been frozen/thawed. Fresh fillets were locally obtained, prepared in samples, scanned by Vis-NIRS and subsequently frozen. After five or twenty one or thirty five days the samples were thawed at 4°C for 24 hours and re-scanned. Partial Least Square Discriminant Analysis (PLS-DA) was applied using repeated double cross-validation showing that there is 92% of probability that a fresh sample is predicted correctly as fresh and 82% that frozen/thawed is really a frozen/thawed. This suggest that Vis-NIRS is able to detect the difference between fresh and frozen/thawed tuna samples.

History

Rights statement

© 2016 Elsevier Ltd. All rights reserved.

Language

  • English

Does this contain Māori information or data?

  • No

Publisher

Elsevier

Journal title

LWT - Food Science and Technology

ISSN

0023-6438

Citation

M.Reis, M., Martinez, E., Saitua, E., Rodriguez, R., Perez, I., & Olabarrieta, I. (2017). Non-invasive differentiation between fresh and frozen/thawed tuna fillets using near infrared spectroscopy (Vis-NIRS). LWT - Food Science and Technology, 78, 129–137. doi:10.1016/j.lwt.2016.12.014

Funder

Royal Society of New Zealand

Contract number

A20182

Job code

67277

Usage metrics

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC