Introduction
Fish oils are known for their benefits to human health because they contain Omega-3 fatty acids (n-3 FA), which are families of long-chain polyunsaturated fatty acids (PUFAs). Many such fatty acids have essential roles in the prevention and treatment of coronary heart disease, diabetes, autoimmune disorders, arthritis, hypertension, and inflammatory diseases. The two predominant fatty acids with these benefits are Eicosapentaenoic Acid (EPA, 20:5 n-3) and Docosahexaenoic Acid (DHA, 22:6 n-3) and these are found almost exclusively in seafood products. Dietary guidelines recommend 0.5 g to 1.0 g of these fatty acids per day and more for various treatments. Fish oil contains about twenty percent of their total fatty acids as PUFA, making them highly susceptible to both oxidation and hydrolytic degradation of lipids. These reactions can cause rancid odors and can even give rise to the formation of products like aldehydes, hydroperoxides, and epoxides that can detract from the nutritional content. Some fish oils are converted to biodiesel by alkali or lipase-catalyzed transesterification reactions and Free Fatty Acids (FFA) content is a critical parameter in these reactions. Moisture, FFA, Peroxide Value (PV), Anisidine Value (AV), EPA, and DHA are monitored using physical and chemical techniques, but these methods are slow and expensive to implement, especially in an industrial process setting. There is a pressing need to determine these parameters that cannot only test large amounts of samples but do so in a cheap and timely fashion. One such method that has been examined is NIR spectroscopy.
Analytes
- Free Fatty Acids (FFA)
- Moisture
- Peroxide Value (PV)
- Anisidine Value (AV)
- Eicosapentaenoic Acid (EPA)
- Docosahexaenoic Acid (DHA)
- Total Omega-3 Fatty Acids (n-3 FA)
Summary of Published Papers, Articles, and Reference Materials
Measurement of chemical parameters for quality control purposes has been studied using NIR spectroscopy for fish oils. The results of most studies have been promising. One such study examined monitoring the oxidative and hydrolytic degradation of lipids in fish oil. Good correlation was shown between NIR spectral data and models for FFA and moisture. The correlation was worse for PV and AV, but this may have occurred due to an error in the reference method. Measuring these parameters with accuracy using NIR spectroscopy has been proven in studies using other types of edible oils. Another study compared using NIR, IR, and Raman spectroscopy to measure EPA, DHA, and Total n-3 FA. Another study used a variety of fish oil supplements and IR spectroscopy to measure EPA and DHA with excellent results. FTIR was examined as an alternative for replacing a conventional titration method to measure FFA in fish oils intended for biodiesel production and the results proved the feasibility of this measurement. However, implementing NIR spectroscopy as a large-scale testing method for fish oil will require extensive calibration work to include different varieties and incorporation of natural sources of variability because they are natural products.
Scientific References and Statistics
Multivariate Determination of Free Fatty Acids and Moisture in Fish Oils by Partial Least-Squares Regression and Near-Infrared Spectroscopy – Cozzolino, Murray, Chree, Scaife – Science Direct LWT 38 (2005) 821-828
One hundred and sixty fish oil samples from a fishmeal factory were scanned in transflectance mode using a NIR monochromator instrument. Wavelength range was from 1100 nm to 2500 nm. The fish oil samples had different chemical compositions due to differences in species and seasonality as well as storage in different tanks. Reference values for Free Fatty Acids, Moisture, Peroxide Value, and Anisidine Value were obtained during the production of material and not at the time of scanning. There was a minimum of five days between sampling and scanning time.
| Free Fatty Acids (FFA) | R2= 0.96 |
| Moisture | R2= 0.94 |
| Peroxide Value (PV) | R2= 0.60 |
| Anisidine Value (AV) | R2= 0.93 |
Good correlation was obtained for FFA and moisture calibration models and validation predictions proved the feasibility of the models for measuring these parameters. However, the PV and AV models did not work as well for the validation set. In the case of PV, the delay in time between collecting reference data and scanning the samples contributed to the low correlation coefficients as some oxidation almost certainly occurred in the samples, creating high reference error. In the case of AV, the correlation coefficient was high, but many of the samples had a reference value of zero as secondary oxidation had not yet occurred. Some validation predictions showed a value less than zero which invalidates the model in a real-time setting. PV and AV have been accurately predicted in other types of edible oil and should be able to in fish oil as well with a more carefully constructed calibration set. The results do prove the feasibility of monitoring hydrolytic degradation of lipids in fish oil using NIR spectroscopy.
https://www.sciencedirect.com/science/article/pii/S0023643804002865
Determination of Omega-3 Fatty Acids in Fish Oil Supplements Using Vibrational Spectroscopy and Chemometric Methods – Bekhit, Grung, Mjos, Applied Spectroscopy, Volume 68, Number 10, 2014
A Fourier Transform Infrared (FT-IR), Near-Infrared (NIR), and Raman spectrometer were all used to scan sixty-one fish oil supplements to predict concentrations of Eicosapentaenoic Acid (EPA), Docosahexaenoic Acid (DHA), and Total Omega-3 Fatty Acids (n-3 FAs). GC was used as a reference method to determine concentrations of these three parameters. EPA and DHA concentrations were expressed as percentages relative to the total mass of fatty acids. Total n-3 FAs were the sum of concentrations of eight single n-3 FAs.
| Scanning Parameters | |
|---|---|
| FT-IR | 4000 cm-1– 650 cm-1, 32 scans per average, 4 cm-1 resolution, ATR Crystal background |
| NIR | 1100 nm -2500 nm, 2 nm intervals, 32 scans per average, 4 cm-1 resolution, adjustable transflectance probe, 1 mm pathlength |
| Raman | 3450 cm-1 – 0 cm-1, 5 second exposure time, <500mW excitation laser at 785 nm |
| Results | ||
|---|---|---|
| FT-IR | EPA- | R2= 0.994, Range = 1820 cm-1 – 650 cm-1 |
| DHA- | R2= 0.983, Range = 1820 cm-1– 650 cm-1 | |
| Total n-3 FAs- | R2= 0.985, Range = 3090 cm-1 -2800 cm-1 & 1790 cm-1 –650 cm-1 | |
| NIR | EPA- | R2= 0.979, Range = 1530 nm -1900 nm |
| DHA- | R2= 0.972, Range = 1530 nm -1940 nm | |
| Total n-3 FAs- | R2= 0.997, Range = 1630 nm -1870 nm | |
| Raman | EPA- | R2= 0.977, Range = 1800 cm-1-769 cm-1 |
| DHA- | R2= 0.966, Range = 1800 cm-1-769 cm-1 | |
| Total n-3 FAs- | R2= 0.993, Range = 3450 cm-1 – 0 cm-1 | |
Models were created for all three instruments using different pre-processing techniques and selective wavelength ranges. The best results are shown above. Excellent correlation was shown for all parameters, demonstrating the potential to measure EPA, DHA, and Total n-3 FAs in fish oil supplement. These three vibrational spectroscopy methods have distinct advantages and disadvantages depending on the situation. While FT-IR is easy to implement in a laboratory, the small pathlength when reflecting off an ATR crystal makes it ill-suited for some measurements. Likewise, Raman is unable to detect Raman shifts in certain molecules. NIR is best suited to a process environment because no sample preparation is needed.
Application of Infrared Spectroscopy for Characterization of Dietary Omega-3 Oil Supplements – Plans, Wenstrup, Rodriguez-Saona, J Am Oil Chem Soc (2015) 92:957-966
Commercial Omega-3 dietary supplements of fish oil, cod liver oil, and flaxseed oil from different manufacturers were procured for this study. Duplicate samples for some of the supplements were also purchased at a later date, ensuring separate lots from the original supplements. All samples were scanned from 4000 cm-1 to 700 cm-1using 4 cm-1resolution and an ATR crystal as a background. GC was performed to create a Fatty Acid profile for each sample. Calibration models were created for seven fatty acids using selective wavenumber ranges.
| C14:0 | R2= 0.99 |
| C16:0 | R2= 0.99 |
| C16:1 | R2= 0.95 |
| C18:1 | R2= 0.95 |
| EPA (Eicosapentaenoic Acid) | R2= 0.99 |
| DHA (Docosahexaenoic Acid) | R2= 0.99 |
| FFA (Free Fatty Acids) | R2= 0.96 |
Results showed a consistent classification of four groups of samples. Based on EPA/DHA content, oil source, and factors associated with processing (FA alkyl ester or triglyceride). The samples in the grouping showed clear spectral distinction in the absorption bands for triglycerides and FA alkyl esters. Models showed excellent performance, especially for EPA and DHA which are the two primary Omega-3 fatty acids of interest in such supplements. Prediction results confirm the capability to estimate the main FAs of fish oil supplements.
https://rd.springer.com
FTIR Determination of Free Fatty Acids in Fish Oils Intended for Biodiesel Production – Aryee, Van de Voort, Simpson, Process Biochemistry 44 (2009) 401-405
Biodiesel is commonly derived from vegetable oils and animal fats by alkali or lipase-catalyzed transesterification reactions. Free Fatty Acids (FFA) is a critical parameter in the conversion of fish oil to methyl esters and the feasibility of using FTIR for determining FFA was examined. The performance of FTIR was assessed as an alternative to the conventional AOCS titration method. Spectra were collected using a transmission flow cell at a resolution of 8 cm-1. Sixteen scans were averaged per spectrum and ratioed against an open-beam background spectrum.
The FTIR method involves simultaneously extracting FFAs, conversion to salts using a weak base, and measuring the carboxylate band (COO-) at 1573 cm-1. The method was found to respond linearly to oleic acid addition, producing a calibration equation for FFA. Validation samples proved the FTIR method was more accurate and reproducible than the titrimetric method.
https://www.sciencedirect.com/science