İstenen sayfanın yerel versiyonuna yönlendirildiniz
Determination of olive oil quality parameters and adulteration with NIR spectroscopy

AN-NIR-125

2025-07

Determination of olive oil quality parameters and adulteration with NIR spectroscopy

Near-infrared spectroscopy reduces costs and chemical waste


Summary

Olive oil quality depends on many factors, such as time spent processing olives after harvest, the production process itself, and olive variety. Due to its high price, virgin olive oil in particular is one of the most vulnerable vegetable oils for food fraud. Many parameters are used to determine the oil quality including the iodine value, free fatty acids (FFA), refractive index, fatty acid composition, and aging indicators such as peroxide value (PV), K232, and induction time. Traditional analysis techniques for olive oil testing like titration or gas chromatography (GC) often require hazardous solvents which can pose health risks and increase laboratory costs. In contrast to these standard methods, the analysis with near-infrared spectroscopy (NIRS) helps to increase productivity and reduce costs, providing quick results for olive oil quality control.


Experimental equipment

The OMNIS NIR Analyzer and a sample filled in a disposable vial.
Figure 1. The OMNIS NIR Analyzer and a sample filled in a disposable vial.

A selection of olive oils with varying quality (137 samples) were measured on the OMNIS NIR Analyzer Liquid (Figure 1) in transmission mode (1000–2250 nm) using 8 mm disposable vials. The vial temperature was set and monitored at 40 °C with the built-in vial sensor to ensure consistent measurement performance. The OMNIS software was used for all data acquisition and prediction model development.


Results

The obtained NIR spectra (Figure 2) were used to create a prediction model for quantification of all parameters: iodine value, FFA, refractive index, K232, PV, induction time, palmitic acid (C16:0), stearic acid (C18:0), oleic acid (C18:1), linoleic acid (C18:2), and alpha-linolenic acid (C18:3). The quality of the prediction models was evaluated using correlation diagrams (Figures 3–8) which display a high correlation between the NIR prediction and the standard reference methods for all parameters. Of the 137 samples measured, 25% were selected as validation set and 75% as calibration set. The respective figures of merit (FOM), shown for the following figures and in Table 1, display the expected precision and confirm the feasibility during routine analysis.

NIR spectra of olive oil samples
Figure 2. NIR spectra of olive oil samples analyzed on an OMNIS NIR Analyzer Liquid with 8 mm vials.

Result iodine value

Correlation diagram and the respective FOMs for the prediction of iodine value
Figure 3. Correlation diagram and the respective FOMs for the prediction of iodine value in olive oil. Lab values were evaluated using GC.
ParameterSEC (mg/100 g)SECV (mg/100 g)SEP (mg/100 g)R2CV
IV0.380.400.38
0.974

Result K232

Correlation diagram and the respective FOMs for the prediction of K232
Figure 4. Correlation diagram and the respective FOMs for the prediction of K232 in olive oil. UV analysis was used to obtain the lab values.
ParameterSEC SECV SEP R2CV
K2320.0670.0860.090 
0.864

Result C16:0 fatty acid content

Correlation diagram and the respective FOMs for the prediction of C16:0 content
Figure 5. Correlation diagram and the respective FOMs for the prediction of C16:0 content in olive oil. Lab values were evaluated using GC.
ParameterSEC (%)SECV (%)SEP (%)R2CV
C16:00.320.380.48
0.962

Result C18:1 fatty acid content

Correlation diagram and the respective FOMs for the prediction of C18:1 content in olive oil
Figure 6. Correlation diagram and the respective FOMs for the prediction of C18:1 content in olive oil. Lab values were evaluated using GC.
ParameterSEC (%)SECV (%)SEP (%)R2CV
C18:10.630.690.75
0.980

Result C18:2 fatty acid content

Correlation diagram and the respective FOMs for the prediction of C18:2 content in olive oil
Figure 7. Correlation diagram and the respective FOMs for the prediction of C18:2 content in olive oil. Lab values were evaluated using GC.
ParameterSEC (%)SECV (%)SEP (%)R2CV
C18:20.320.380.43
0.985

Result induction time

Correlation diagram and the respective FOMs for the prediction of olive oil induction time
Figure 8. Correlation diagram and the respective FOMs for the prediction of olive oil induction time. Lab values were evaluated with a Rancimat.
ParameterSEC (h)SECV (h)SEP (h)R2CV
Induction time0.300.350.34
0.908
Table 1. Figures of merit for the parameters of stearic acid, α-linolenic acid, FFA, peroxide value, and refractive index in various olive oils.
Parameter SECSECVSEPR²CV
Stearic acid (C18:0)0.12%0.22%0.22%0.778
α-linolenic acid (C18:3)0.05%0.05%0.05%0.633
FFA0.03%0.04%0.04%0.746
Peroxide value0.72 meq/kg0.83 meq/kg1.01 meq/kg0.719
Refractive index0.000110.000120.000120.998

Conclusion

This Application Note displays the positive attributes of olive oil analysis with near-infrared spectroscopy. Compared to time-consuming conventional analytical methods, measurements performed with NIRS do not need any sample preparation. This ultimately leads to a workload reduction (Table 2) and reduced costs.

Aside from the parameters shown in this Application Note, additional olive oil quality parameters like sterol content or moisture content can also be determined with NIRS.

Table 2. Time to result overview for the measurement of iodine value, FFA content, refractive index, K232, induction time, and fatty acid composition in olive oils by standard analytical methods.
Parameter MethodTime to result
Iodine valueGas chromatography~30 minutes per sample
FFA content, Peroxide valueTitration~15 minutes per sample
Refractive indexRefractometer~5 minutes per sample
K232UV absorption~5 minutes per sample
Fatty acid compositionGas chromatography~30 minutes per sample
Induction timeRancimat~1–15 hours per sample
İletişim

Metrohm Turkey

Ayazağa Mah. Azerbaycan Cad. No. 3I
34396 İstanbul

İletişim