Method Development and Validation for Omega-3 Fatty Acids (DHA and EPA) in Fish Using Gas Chromatography with Flame Ionization Detection (GC-FID)

Alinafiah, Suryati Muhammad; Azlan, Azrina; Ismail, Amin; Rashid, Nor-Khaizura Mahmud Ab

doi:10.3390/molecules26216592

Cited by 18 publications

(9 citation statements)

References 30 publications

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“…Usually, the lipid fractions are extracted using different organic solvents and mixture of it (e.g., methanol, ether) [24][25][26], Soxhlet [27,28], and supercritical fluid extraction [28,29]. Regarding analytical approaches, infrared spec-troscopy, capillary electrophoresis, liquid (LC), and gas chromatography (GC) have been reported in the determination of FAs profile [30]. From these, GC using a flame ionization detector (FID) is the most used since it is a sensitive, reproducible, accurate, and versatile approach for the analysis of complex samples that led to specific and fast analysis of FAs in a diversity of foods [25,26,31,32].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of Fatty Acids Profile as a Useful Tool towards Valorization of By-Products of Agri-Food Industry

Ferreira

Lourenço

Lopes

et al. 2021

Foods

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Worldwide, the food industry generates a large number of by-products from a wide variety of sources. These by-products represent an interesting and economical source of added value components with potential functionalities and/or bioactivities, which might be explored for industrial purposes, encouraging and promoting the circular economy concept. In this context, the current work aimed to evaluate the fatty acids (FAs) profile using gas chromatography–flame ionization detector (GC–FID) and Fourier Transform Infrared (FTIR), as well as the determination of related health lipid indices (e.g., atherogenic (AI) and thrombogenic (TI)) as a powerful strategy to investigate the potential applications of different agri-food by-products for human nutrition and animal feeding. This work results showed that polyunsaturated fatty acids (PUFAs) are the predominant group in grape pomace (72.7%), grape bunches (54.3%), and brewer’s spent grain (BSG, 59.0%), whereas carrot peels are dominated by monounsaturated fatty acids (MUFAs, 47.3%), and grape stems (46.2%), lees (from 50.8 to 74.1%), and potato peels (77.2%) by saturated fatty acids (SFAs). These findings represent a scientific basis for exploring the nutritional properties of agri-food by-products. Special attention should be given to grape pomace, grape bunches, and BSG since they have a high content of PUFAs (from 54.3 to 72.7%) and lower AI (from 0.11 to 0.38) and TI (from 0.30 to 0.56) indexes, suggesting their potential to provide a variety of health benefits against cardiovascular diseases including well-established hypotriglyceridemia and anti-inflammatory effects, products to which they are added.

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Section: Introductionmentioning

confidence: 99%

Evaluation of Fatty Acids Profile as a Useful Tool towards Valorization of By-Products of Agri-Food Industry

Ferreira

Lourenço

Lopes

et al. 2021

Foods

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“…GC-FID has been developed and validated for quantitative analysis of ω-3 FAs of DHA and EPA in raw and cooked fish [ 48 ]. Fatty acids were derivatized as fatty acid methyl esters (FAMEs), and the derivatized fatty acids were subjected to GC-FID analysis.…”

Section: Chromatographic-based Methods For Analysis Of ω-3 Fas and ω-...mentioning

confidence: 99%

Application of Chromatographic and Spectroscopic-Based Methods for Analysis of Omega-3 (ω-3 FAs) and Omega-6 (ω-6 FAs) Fatty Acids in Marine Natural Products

et al. 2023

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Omega-3 fatty acids v(ω-3 FAs) such as EPA (eicosapentaenoic acid) and DHA (docosahexaenoic acid) and omega-6 fatty acids (ω-6 FAs) such as linoleic acid and arachidonic acid are important fatty acids responsible for positive effects on human health. The main sources of ω-3 FAs and ω-6 FAs are marine-based products, especially fish oils. Some food, supplements, and pharmaceutical products would include fish oils as a source of ω-3 FAs and ω-6 FAs; therefore, the quality assurance of these products is highly required. Some analytical methods mainly based on spectroscopic and chromatographic techniques have been reported. Molecular spectroscopy such as Infrared and Raman parallel to chemometrics has been successfully applied for quantitative analysis of individual and total ω-3 FAs and ω-6 FAs. This spectroscopic technique is typically applied as the alternative method to official methods applying chromatographic methods. Due to the capability to provide the separation of ω-3 FAs and ω-6 FAs from other components in the products, gas and liquid chromatography along with sophisticated detectors such as mass spectrometers are ideal analytical methods offering sensitive and specific results that are suitable for routine quality control.

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“…Therefore, the quality controls of ω-3 FAs by determining the components of ω-3 FAs using some analytical methods is very urgent. Chromatographic-based methods including gas chromatography using flame ionization detector [5], mass spectrometer detector [6], HPLC with UV detection liquid [7] and chromatography/tandem mass spectrometry (LC-MS/MS) [8]. However, these methods involved sophisticated instruments and need skilful analyst, therefore, more user-friendly methods are need to be developed mainly based on spectroscopic methods including FTIR spectroscopy.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Omega-3 (ω-3) Fatty Acid in Indonesia Fish Oils Using Infrared Spectroscopy and Multivariate Data Analysis

Irnawati¹,

Windarsih²,

Fadzilah³

et al. 2023

Preprint

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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 &gt; 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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Method Development and Validation for Omega-3 Fatty Acids (DHA and EPA) in Fish Using Gas Chromatography with Flame Ionization Detection (GC-FID)

Cited by 18 publications

References 30 publications

Evaluation of Fatty Acids Profile as a Useful Tool towards Valorization of By-Products of Agri-Food Industry

Evaluation of Fatty Acids Profile as a Useful Tool towards Valorization of By-Products of Agri-Food Industry

Application of Chromatographic and Spectroscopic-Based Methods for Analysis of Omega-3 (ω-3 FAs) and Omega-6 (ω-6 FAs) Fatty Acids in Marine Natural Products

Analysis of Omega-3 (ω-3) Fatty Acid in Indonesia Fish Oils Using Infrared Spectroscopy and Multivariate Data Analysis

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