Palm oils have a wide range of application uses, making them the world's most extensively produced and consumed vegetable oil. Both crude palm oil and kernel palm oil have uses that stretch beyond the food industry, as palm oils are found in around 70% of personal care and cosmetic products globally.
How crude palm oil (CPO) is marketed for application use is determined by several quality indicators, including iodine value (IV) and fatty acid composition.
This article describes how near-infrared (NIR) spectroscopy is the perfect substitute for alternatives to conventional analysis techniques such as gas chromatography.
NIRS delivers rapid results in less than one minute without needing chemical reagents and sample preparation, which boosts productivity while reducing costs.
Configuration
DS2500 Liquid Analyzer
The DS2500 Liquid Analyzer is well-suited for quality control applications as it delivers exceptional near-infrared spectroscopy in laboratory and production-based environments. The analyzer is a tried and tested, versatile solution for the routine analysis of liquids across the entire production line.
With a robust design, the DS2500 Liquid Analyzer can withstand even harsh production environments as it is resistant to dust, moisture, and vibrations.
The DS2500 Liquid Analyzer is compatible with various disposable vials and quartz cuvettes. Covering the spectral range from 400 to 2500 nm the analyzer can also run analysis of heat samples up to 80 °C.
These properties make the DS2500 Liquid Analyzer flexible to individual sample requirements, allowing users to attain accurate and reproducible results in under one minute.
The built-in sample holder detection and the intuitive Vision Air Software make operation safe and user-friendly. When performing a larger sample run is necessary, applying a flow-through cell paired with a Metrohm sample robot should significantly boost productivity.
Table 1. Hardware and software equipment overview. Source: Metrohm Middle East FZC
Equipment |
Article number |
DS2500 Liquid Analyzer |
2.929.0010 |
DS2500 Holder 8 mm vials |
6.7492.020 |
Vision Air 2.0 Complete |
6.6072.208 |
Experimental Equipment
Twenty crude palm oil (CPO) samples, each with different iodine values (IV), were heated in a water bath at 60 °C for a minimum of 30 minutes to ensure they melted. These liquefied samples were subsequently analyzed at 60 °C using a Metrohm NIRS DS2500 Liquid Analyzer in transmission mode, covering a wavelength range from 400 to 2500 nm, and utilizing 8 mm disposable vials for the measurements. The process of data gathering and the prediction model development were facilitated using the Vision Air comprehensive software suite provided by Metrohm.
For comparison, the gas chromatography (GC) method was employed following the methylation of fatty acids. The quantification of fatty acids was based on the analysis of their peak areas. The iodine values were determined by calculating the combined oleic and palmitic acid concentrations.
Figure 1. Metrohm NIRS DS2500 Liquid Analyzer used for the determination of iodine value and fatty acid composition in crude palm oil samples. Image Credit: Metrohm Middle East FZC
Result
The measured Vis-NIR spectra were used to generate a prediction model to determine the iodine value (IV), linoleic acid (18:2), oleic acid (18:1), and palmitic acid (16:0) in CPO as shown in Figure 2.
Correlation diagrams were used to assess the quality of the prediction model, which, when evaluated, displayed a high correlation between the Vis-NIR prediction and the GC results. The respective figures of merit (FOM) exhibit the expected precision and verify the feasibility during routine analysis, as illustrated in Figures 3–6.
Figure 2. Selection of Vis-NIR spectra of crude palm oil samples analyzed on a Metrohm NIRS DS2500 Liquid Analyzer with 8 mm vials. Image Credit: Metrohm Middle East FZC
Result Iodine Value
Figure 3. Correlation diagram and the respective figures of merit for the prediction of iodine value in CPO using a DS2500 Liquid Analyzer. The lab value was measured using GC. Image Credit: Metrohm Middle East FZC
Source: Metrohm Middle East FZC
Figures of Merit |
Value |
R2 |
0.994 |
Standard Error of Calibration |
0.10% |
Standard Error of Cross-Validation |
0.11% |
Result C16:0 Fatty Acid Content
Figure 4. Correlation diagram and the respective figures of merit for the prediction of relative palmitic acid content in CPO using a DS2500 Liquid Analyzer. The lab value was measured using GC. Image Credit: Metrohm Middle East FZC
Source: Metrohm Middle East FZC
Figures of Merit |
Value |
R2 |
0.9836 |
Standard Error of Calibration |
0.15% |
Standard Error of Cross-Validation |
0.15% |
Result C18:1 Fatty Acid Content
Figure 5. Correlation diagram and the respective figures of merit for the prediction of relative oleic acid content in CPO using a DS2500 Liquid Analyzer. The lab value was measured using GC. Image Credit: Metrohm Middle East FZC
Source: Metrohm Middle East FZC
Figures of Merit |
Value |
R2 |
0.9851 |
Standard Error of Calibration |
0.11% |
Standard Error of Cross-Validation |
0.12% |
Result C18:2 Fatty Acid Content
Figure 6. Correlation diagram and the respective figures of merit for the prediction of relative linoleic acid content in CPO using a DS2500 Liquid Analyzer. The lab value was measured using GC. Image Credit: Metrohm Middle East FZC
Source: Metrohm Middle East FZC
Figures of Merit |
Value |
R2 |
0.9916 |
Standard Error of Calibration |
0.03% |
Standard Error of Cross-Validation |
0.04% |
Conclusion
Here, in this article, the benefits of using the Metrohm NIRS DS2500 Liquid Analyzer are clear when it comes to routine quality control analysis of crude palm oil.
Table 2. Time to result overview for the determination of iodine value and fatty acid composition in palm oil by standard methods. Source: Metrohm Middle East FZC
Parameter |
Method |
Time to result |
lodine value, Fatty acid composition |
Gas Chromatography |
∼40 min sample preparation (methyl esterification + sample preparation) + ∼20 min GC |
Compared to traditional analytical techniques, there is no need to perform sample preparation when using Vis-NIR spectroscopy to determine certain values. Resultingly, this reduces both workload and operating costs as shown in Table 2.
This information has been sourced, reviewed and adapted from materials provided by Metrohm Middle East FZC.
For more information on this source, please visit Metrohm Middle East FZC.