Fingerprint Approaches Coupled with Chemometrics to Discriminate Geographic Origin of Imported Salmon in China’s Consumer Market

Abstract

Of the salmon sold in China’s consumer market, 92% was labelled as Norwegian salmon, but was in fact was mainly imported from Chile. The aim of this study was to establish an effective method for discriminating the geographic origin of imported salmon using two fingerprint approaches, Near-infrared (NIR) spectroscopy and mineral element fingerprint (MEF). In total, 80 salmon (40 from Norway and 40 from Chile) were tested, and data generated by NIR and MEF were analysed via various chemometrics. Four spectral preprocessing methods, including vector normalization (VN), Savitzky Golay (SG) smoothing, first derivative (FD) and second derivative (SD), were employed on the raw NIR data, and a partial least squares (PLS) model based on the FD + SG9 pretreatment could successfully differentiate Norwegian salmons from Chilean salmons, with a R2 value of 98.5%. Analysis of variance (ANOVA) and multiple comparative analysis were employed on the contents of 16 mineral elements including Pb, Fe, Cu, Zn, Al, Sr, Ni, As, Cr, V, Se, Mn, K, Ca, Na and Mg. The results showed that Fe, Zn, Al, Ni, As, Cr, V, Se, Ca and Na could be used as characteristic elements to discriminate the geographical origin of the imported salmon, and the discrimination rate of the linear discriminant analysis (LDA) model, trained on the above 10 elements, could reach up to 98.8%. The results demonstrate that both NIR and MEF could be effective tools for the rapid discrimination of geographic origin of imported salmon in China’s consumer market.

Intelligent Evaluation of Stone Cell Content of Korla Fragrant Pears by Vis/NIR Reflection Spectroscopy

“…The standardized normal variate (SNV) was used for the centering and calibration of the spectral data in each wavelength [ 38 ]. Several Savitzky–Golay (S-G) filters [ 39 ], with frame sizes of 3–9 and fitting orders of 1–7, were used to improve the smoothing effect. The optimal combination of frame size and fitting order was chosen according to R and RMSE values.…”

Discriminate geographical origin of cabe jamu (Piper retrofractum vahl) using nir spectral fingerprints– a short review

“…The combination of NIR spectroscopy and chemometrics successfully discriminates products related to geographical origin and detect fraud products. NIR spectroscopy coupled with chemometrics can discriminate imported salmon based on geographical origin, with an accuracy reaching 98.8% [33]. Furthermore, this combination can classify the type of meat fraud with acceptable precision and accuracy that reach between 78.95 and 100% [34] (iii) the presence of water in the sample could lessen signal to ratio of NIR measurement and affect to classification model accuracy [25,35] To overcome it and increase model accuracy.…”

“…Especially the organic functional group is easier to interpret using MIR spectroscopy because they have characteristics and a well-defined absorption band in the MIR region. Moreover, the used MIR spectroscopy coupled with NIR tends to be more contributive than NIR in the definition of the latent variable for a sample in an aqueous solution [35] (a) (b) Third, the Data-fusion method from a combination between NIR measurement and different analytical techniques showed high accuracy for the discrimination of botanical and geographical origin [9,33]. Fu et al [33] reported that using a combination of NIR spectroscopy and MEF (mineral element fingerprint) to distinguish imported salmon obtainea classification accuracy of 98%.…”

“…Moreover, the used MIR spectroscopy coupled with NIR tends to be more contributive than NIR in the definition of the latent variable for a sample in an aqueous solution [35] (a) (b) Third, the Data-fusion method from a combination between NIR measurement and different analytical techniques showed high accuracy for the discrimination of botanical and geographical origin [9,33]. Fu et al [33] reported that using a combination of NIR spectroscopy and MEF (mineral element fingerprint) to distinguish imported salmon obtainea classification accuracy of 98%. Bodor et al [9] discriminated honey related to botanical and geographical origin using three techniques, melissopalynology, physicochemical analysis, and NIR.…”

An overview of the consumer‐centric disruptive technology research: Insights from topic modelling and literature review

“…At the same time, consumer acceptance is contingent upon academia and industry collaboration to transition from early to mainstream markets (Park et al, 2021). Once the technology reaches the fourth stage, like fingerprint recognition, it becomes mature enough for widespread use by the industry and consumers (Fu et al, 2021). Technology progression leads to a saturated phase, where consumers have successfully adopted the technology (Kalthaus, 2020).…”