Abstract
Raman and infrared spectroscopy, used as individual and low-level fused datasets, were evaluated to identify and quantify the presence of adulterants (palm oil, PO; ω-3 concentrates in ethyl ester, O3C and fish oil, FO) in krill oil. These datasets were qualitatively analysed with principal component analysis (PCA) and classified as adulterated or unadulterated using support vector machines (SVM). Using partial least squares regression (PLSR), it was possible to identify and quantify the adulterant present in the KO mixture. Raman spectroscopy performed better (r2 = 0.98; RMSEP = 2.3%) than IR spectroscopy (r2 = 0.91; RMSEP = 4.2%) for quantification of O3C in KO. A data fusion approach further improved the analysis with model performance for quantification of PO (r2 = 0.98; RMSEP = 2.7%) and FO (r2 = 0.76; RMSEP = 9.1%). This study demonstrates the potential use of Raman and IR spectroscopy to quantify adulterants present in KO.
Original language | English |
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Article number | 3695 |
Number of pages | 16 |
Journal | Molecules |
Volume | 28 |
Issue number | 9 |
DOIs | |
Publication status | Published - 1 May 2023 |
Keywords
- adulteration
- chemometrics
- infrared spectroscopy
- low level data fusion
- marine lipid
- omega-3 fatty acids
- PCA
- PLSR
- Raman spectroscopy
- SVM
- vibrational spectroscopy
- Animals
- Euphausiacea
- Food Contamination
- Least-Squares Analysis
- Spectrophotometry, Infrared
- Spectrum Analysis, Raman
- animal
- food contamination
- infrared spectrophotometry
- krill
- least square analysis
- Raman spectrometry