FT-IR-based quantitative analysis strategy for target adulterant in fish oil multiply adulterated with terrestrial animal lipid

Gao, Bing; Xu, Shuai; Han, Lujia; Liu, Xian

doi:10.1016/j.foodchem.2020.128420

Cited by 14 publications

(1 citation statement)

References 28 publications

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“…Raman spectroscopy has been used to authenticate FO depending on their omega-3 content (EPA, DHA, and total PUFA) [ 2 , 17 ]. Gao et al used FT-IR based quantitative analysis (partial least square discriminate analysis (PLS-DA)) to detect terrestrial animal lipid adulterant in FO samples [ 18 ]. However, the use of data-fused spectroscopic data and the creation of global models, i.e., a single model that can detect a range of different adulterants in multiple oil types, is relatively unexplored.…”

Section: Introductionmentioning

confidence: 99%

Rapid Quantitation of Adulterants in Premium Marine Oils by Raman and IR Spectroscopy: A Data Fusion Approach

et al. 2022

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This study uses Raman and IR spectroscopic methods for the detection of adulterants in marine oils. These techniques are used individually and as low-level fused spectroscopic data sets. We used cod liver oil (CLO) and salmon oil (SO) as the valuable marine oils mixed with common adulterants, such as palm oil (PO), omega-3 concentrates in ethyl ester form (O3C), and generic fish oil (FO). We showed that support vector machines (SVM) can classify the adulterant present in both CLO and SO samples. Furthermore, partial least squares regression (PLSR) may be used to quantify the adulterants present. For example, PO and O3C adulterated samples could be detected with a RMSEP value less than 4%. However, the FO adulterant was more difficult to quantify because of its compositional similarity to CLO and SO. In general, data fusion improved the RMSEP for PO and O3C detection. This shows that Raman and IR spectroscopy can be used in concert to provide a useful analytical test for common adulterants in CLO and SO.

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Section: Introductionmentioning

confidence: 99%