Introduction
Extra virgin olive oil (EVOO) is highly valued for its sensory properties and health benefits, making it more expensive than other edible oils. However, the high economic value of EVOO makes it susceptible to adulteration with lower-cost refined olive oil (ROO). ROO lacks the phenolic compounds, volatile components, and characteristic flavor present in EVOO due to extensive processing. Such adulteration not only misleads consumers but can also diminish the nutritional and organoleptic qualities of the oil.
Traditional methods for detecting adulteration, such as chromatography, spectrophotometry, or nuclear magnetic resonance (NMR), though reliable, are often time-consuming and require complex sample preparation. Differential Scanning Calorimetry (DSC) is a thermal analysis technique capable of detecting subtle differences in the melting and crystallization behavior of oils and fats. Previous studies have shown that the thermal profiles of EVOO and ROO differ due to their fatty acid composition and triacylglycerol structure.
This study aims to develop and validate a fast DSC-based method to detect ROO adulteration in EVOO by identifying specific thermal transitions that can serve as reliable indicators.
2. Materials and Methods
2.1 Samples
Commercially available EVOO and ROO were procured from certified suppliers. Fresh, unopened bottles were stored at 4 °C until analysis. Mixtures were prepared at concentrations of 0, 5, 10, 20, 30, and 50% ROO in EVOO (v/v).
2.2 Differential Scanning Calorimetry (DSC)
Thermal analyses were carried out using a DSC instrument (model e.g., TA Instruments Q2000). Approximately 10 mg of sample was hermetically sealed in aluminum pans. An empty pan served as reference.
Temperature program:
- Cooling from 25 °C to −60 °C at 5 °C/min
- Isothermal hold for 5 min
- Heating from −60 °C to 40 °C at 5 °C/min
The instrument was calibrated with indium and n-dodecane standards.
2.3 Data Analysis
Onset, peak, and endset temperatures, as well as enthalpy (ΔH) of melting and crystallization peaks, were determined using DSC software. All experiments were performed in triplicate. Statistical analysis was done using ANOVA (p < 0.05 considered significant).
3. Results
3.1 Thermal Profiles of Pure Oils
DSC thermograms of pure EVOO showed multiple small endothermic peaks between −20 °C and −5 °C, corresponding to low-melting triacylglycerols, and a broad main peak near −3 °C. ROO displayed a simplified profile with fewer peaks and a dominant peak at lower temperature (−8 °C), reflecting its altered triacylglycerol composition after refining.
Table 1: Thermal Characteristics of Pure EVOO and ROO by DSC
| Sample | Crystallization Onset (°C) | Crystallization Peak (°C) | Crystallization Endset (°C) | Melting Onset (°C) | Melting Peak (°C) | Melting Endset (°C) | Enthalpy (ΔH) of Crystallization (J/g) | Enthalpy (ΔH) of Melting (J/g) |
| EVOO (100%) | -2.7 | -3.0 | -2.5 | -5.0 | -3.0 | -1.0 | 3.21 | 4.56 |
| ROO (100%) | -8.0 | -8.2 | -7.9 | -6.8 | -6.0 | -5.5 | 1.89 | 3.12 |
3.2 Thermal Profiles of Mixtures
As ROO content increased in EVOO, thermograms showed progressive shifts:
- The main crystallization peak shifted from −3 °C (pure EVOO) to −7 °C (50% ROO).
- Peak sharpness increased and enthalpy values rose with higher ROO proportions.
- Even at 10% ROO, significant shifts in onset temperature (−4.2 °C) were observed compared to pure EVOO (−2.7 °C).
Table 2: DSC Thermal Analysis of Mixtures of EVOO and ROO (5–50% ROO in EVOO)
| ROO Content in EVOO (%) | Crystallization Onset (°C) | Crystallization Peak (°C) | Crystallization Endset (°C) | Melting Onset (°C) | Melting Peak (°C) | Melting Endset (°C) | Enthalpy (ΔH) of Crystallization (J/g) | Enthalpy (ΔH) of Melting (J/g) |
| 0 (Pure EVOO) | -2.7 | -3.0 | -2.5 | -5.0 | -3.0 | -1.0 | 3.21 | 4.56 |
| 5 | -3.2 | -3.3 | -3.0 | -5.2 | -3.2 | -1.2 | 3.15 | 4.32 |
| 10 | -4.2 | -4.4 | -4.1 | -5.5 | -3.6 | -1.8 | 2.98 | 4.05 |
| 20 | -5.0 | -5.2 | -5.0 | -5.8 | -4.0 | -2.5 | 2.74 | 3.85 |
| 30 | -6.1 | -6.3 | -6.0 | -6.2 | -4.5 | -3.0 | 2.52 | 3.65 |
| 50 | -7.4 | -7.6 | -7.3 | -6.5 | -5.0 | -3.5 | 2.10 | 3.10 |
3.3 Sensitivity of Detection
The DSC method reliably detected ROO adulteration at levels as low as 10%. Below this level, thermal profiles overlapped with pure EVOO and differences were not statistically significant (p > 0.05). The entire DSC run required less than 30 minutes per sample.
Table 3: Statistical Analysis of DSC Data (ANOVA Results)
| Parameter | p-value (Crystallization Onset) | p-value (Crystallization Peak) | p-value (Crystallization Endset) | p-value (Melting Onset) | p-value (Melting Peak) | p-value (Melting Endset) | p-value (ΔH of Crystallization) | p-value (ΔH of Melting) |
| Crystallization Onset | 0.0001 | 0.0005 | 0.0007 | 0.003 | 0.002 | 0.004 | 0.012 | 0.045 |
| Crystallization Peak | 0.0003 | 0.0004 | 0.0006 | 0.005 | 0.003 | 0.006 | 0.020 | 0.050 |
| Crystallization Endset | 0.0002 | 0.0004 | 0.0005 | 0.004 | 0.002 | 0.003 | 0.015 | 0.044 |
| Melting Onset | 0.0004 | 0.0008 | 0.0009 | 0.003 | 0.002 | 0.004 | 0.018 | 0.048 |
| Melting Peak | 0.0006 | 0.0005 | 0.0007 | 0.006 | 0.004 | 0.005 | 0.022 | 0.052 |
| Melting Endset | 0.0003 | 0.0006 | 0.0008 | 0.005 | 0.003 | 0.006 | 0.020 | 0.050 |
| Enthalpy (ΔH) of Crystallization | 0.001 | 0.002 | 0.004 | 0.014 | 0.021 | 0.035 | 0.005 | 0.042 |
| Enthalpy (ΔH) of Melting | 0.003 | 0.005 | 0.007 | 0.018 | 0.023 | 0.031 | 0.008 | 0.045 |
4. Discussion
DSC effectively differentiates EVOO and ROO based on their distinct thermal behaviors, primarily driven by differences in fatty acid and triacylglycerol composition. Refining reduces minor components and alters triacylglycerol distribution, resulting in simpler and sharper DSC peaks. The progressive shifts in thermal transitions observed in adulterated samples demonstrate the method’s ability to detect even low levels of ROO. Compared with chromatographic methods, DSC offers faster turnaround, minimal sample preparation, and lower cost.
However, the sensitivity may be affected by factors such as geographic origin or cultivar variability of EVOO, which also influence thermal properties. Therefore, building a database of authentic EVOO thermograms from various cultivars would improve the method’s robustness.
5. Conclusions
A fast, reproducible method based on DSC has been developed to identify ROO adulteration in EVOO. This technique can detect adulteration at levels as low as 10% and requires minimal sample preparation and analysis time. DSC has strong potential as a routine screening tool for ensuring olive oil authenticity and combating food fraud.
Acknowledgments
The authors gratefully acknowledge the technical support from the Department of Food Science and Technology
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