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dc.contributor.authorLintvedt, Tiril Aurora
dc.contributor.authorAndersen, Petter Vejle
dc.contributor.authorAfseth, Nils Kristian
dc.contributor.authorHeia, Karsten
dc.contributor.authorLindberg, Stein-Kato
dc.contributor.authorWold, Jens Petter
dc.date.accessioned2022-12-08T13:40:22Z
dc.date.available2022-12-08T13:40:22Z
dc.date.created2022-12-05T13:39:22Z
dc.date.issued2022
dc.identifier.citationTalanta: The International Journal of Pure and Applied Analytical Chemistry. 2023, 254.en_US
dc.identifier.issn0039-9140
dc.identifier.urihttps://hdl.handle.net/11250/3036820
dc.description.abstractRaman spectroscopy was compared with near infrared (NIR) hyperspectral imaging for determination of fat composition (%EPA + DHA) in salmon fillets at short exposure times. Fillets were measured in movement for both methods. Salmon were acquired from several different farming locations in Norway with different feeding regimes, representing a realistic variation of salmon in the market. For Raman, we investigated three manual scanning strategies; i) line scan of loin, ii) line scan of belly and iii) sinusoidal scan of belly at exposure times of 2s and 4s. NIR images were acquired while the fillets moved on a conveyor belt at 40 cm/s, which corresponds to an acquisition time of 1s for a 40 cm long fillet. For NIR images, three different regions of interest (ROI) were investigated including the i) whole fillet, ii) belly segment, and iii) loin segment. For both Raman and NIR measurements, we investigated an untrimmed and trimmed version of the fillets, both relevant for industrial in-line evaluation. For the trimmed fillets, a fat rich deposition layer in the belly was removed. The %EPA + DHA models were validated by cross validation (N = 51) and using an independent test set (N = 20) which was acquired in a different season. Both Raman and NIR showed promising results and high performances in the cross validation, with R2CV = 0.96 for Raman at 2s exposure and R2CV = 0.97 for NIR. High performances were obtained also for the test set, but while Raman had low and stable biases for the test set, the biases were high and varied for the NIR measurements. Analysis of variance on the squared test set residuals showed that performance for Raman measurements were significantly higher than NIR at 1% significance level (p = 0.000013) when slope-and-bias errors were not corrected, but not significant when residuals were slope-and-bias corrected (p = 0.28). This indicated that NIR was more sensitive to matrix effects. For Raman, signal-to-noise ratio was the main limitation and there were indications that Raman was close to a critical sample exposure time at the 2s signal accumulation.
dc.language.isoengen_US
dc.subjectRepresentative sampling
dc.subjectRepresentative sampling
dc.subjectIn line food evaluation
dc.subjectIn-line food evaluation
dc.subjectNIR hyperspectral Imaging
dc.subjectNIR hyperspectral Imaging
dc.subjectSalmon quality
dc.subjectSalmon quality
dc.subjectRamanspektroskopi
dc.subjectRaman spectroscopy
dc.titleRaman spectroscopy and NIR hyperspectral imaging for in-line estimation of fatty acid features in salmon filletsen_US
dc.title.alternativeRaman spectroscopy and NIR hyperspectral imaging for in-line estimation of fatty acid features in salmon filletsen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionpublishedVersion
dc.source.volume254en_US
dc.source.journalTalanta: The International Journal of Pure and Applied Analytical Chemistryen_US
dc.identifier.doi10.1016/j.talanta.2022.124113
dc.identifier.cristin2088787
dc.relation.projectNorges forskningsråd: 309259
dc.relation.projectNorges forskningsråd: 296083
dc.relation.projectNorges forskningsråd: 314111
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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