Irnawati, Irnawati and Windarsih, Anjar and Fadzillah, Nurrulhidayah and Riswanto, Florentinus Dika Octa and Rohman, Abdul
(2023)
Analysis of omega-3 (ω-3) fatty acid in Indonesia fish oils
using infrared spectroscopy and multivariate data analysis.
Analysis of Omega-3 (ω-3) Fatty Acid in Indonesia Fish Oils Using Infrared Spectroscopy and Multivariate Data Analysis.
(In Press)
Abstract
: Omega-3 fatty acids (ω-3 FAs) are important fatty acids having the beneficial roles in human health including reducing blood pressure, lowering the risk of cardiovascular disease and exerting anti-inflammation activities. Omega-3 FAs were mainly found in fish oils, therefore, determination of these FAs is very important. This study highlighted the employment of FTIR spectroscopy combined with multivariate data analysis for determination of ω-3 FAs in fish oils. Fish oils
were obtained from the extraction of corresponding fishes and subjected to purification. The oils
were further subjected to FTIR spectroscopic measurement at mid infrared region (4000-450 cm-1).
Fatty acid compositions of ω-3 FAs namely eicosapentaenoic acid (EPA) and docosahexaenoic acid
(DHA) were determined using gas chromatography with flame ionization (GC-FID), and the results
from GC-FID were used as actual values. Two multivariate regressions along with wavenumbers
regions or their combinations were optimized and compared to provide the best condition for prediction of EPA and DHA in fish oils. The results showed that partial least square regression (PLSR)
was suitable for prediction of DHA applying the variable of absorbance values of the second derivative spectra, with the values of coefficient of determination (R2) of 0.9916 and 0.9316 in calibration
and validation models, respectively. The values of root mean square error of calibration (RMSEC)
and root mean square error of prediction (RMSEP) obtained were 0.789 and 2.53. While, prediction
of EPA was performed using principal component regression with R2 value of > 0.72 and low values
of RMSEC and RMSEC. It can be concluded that the combination of FTIR spectra and multivariate
regression provides the effective tools and alternative GC-FID method for the prediction of EPA
and DHA in fish oils.
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