Lemon (Citrus limon) is one of the most popular citrus fruits after oranges and citrus, with a global production capacity of 4.2 million tons, mainly in the United States, Argentina, Spain, Italy and Mexico. Lemon is rich in a variety of secondary metabolites, widely used in the pharmaceutical, nutrition and health products, food and cosmetics industries. In addition to vitamin C, lemons contain phytochemicals, including polyphenols (flavonoids and non-flavonoids), citric acid and terpenoids, which play important roles as nutritional and health products. Some of these metabolites have been shown to have anticancer, antibacterial, antioxidant, and antidiabetic properties. Furthermore, the essential oils of lemon and other citrus fruits are considered as excellent alternatives to chemical additives in the food industry, meeting both safety needs and consumer demand for natural food ingredients.



The volatile composition of food matrix is one of the important factors affecting flavor and consumer acceptance.

In lemons, metabolic pathways and the corresponding volatile components have been widely reported to be influenced by several factors related to genotype (where many hybrids exist), maturity, and geography.

 

Question

How to determine the volatile components of the food matrix and food-related samples?

Currently, different methods are used to determine the volatile components of the food matrix and food-related samples. Gas chromatography-mass spectrometry (GC-MS) is the gold standard instrument technique for VOCs analysis, suitable for a variety of different samples. However, prior sample preparation is often overlooked, which is critical for concentrating VOCs and eliminating interference, especially from complex substrates. Traditional extraction techniques, including solvent extraction, distillation, and headspace techniques, are mainly based on the solubility or volatility of VOCs. These methods can define the fingerprint of the volatile components and the integrated information on the flavor / aroma of the target sample.

 

INNOTEG NeedleTrap (NT) dynamic needle capture technology provides a brand new sample preparation method for trace analysis in gaseous matrix. By increasing the amount of adsorbent and composite different kinds of adsorbent in increasing the adsorption capacity, especially the adsorption of small molecules. The new technology of small sample volume and thermal analysis of internal expansion airflow for rapid analysis without condensation device is conducive to trace grade gas analysis, with high sensitivity and low detection limit.

 

 

Question

How to use NeedleTrap to distinguish the origin of lemon?

 

Sample Source

Samples of lemon from the same variety (Eureka) were randomly selected from the local market, but grown in different regions (mainland Portugal and Madeira, Argentina and South Africa). After selection, the peel (exocarp) of each lemon was collected separately and immediately stored at 80°C of nitrogen with 250mg aliquots until analysis.

 

INNOTEG NeedleTrap (NT) Selection

（60 mm × 0:41 mm id,0.72 mm od， Divinylbenzene/Carboxen 1000/Carbopack X -DVB/Car1000/CarX）

 

Sample Collection Process

1. Put 250 mg of sample into a 20 ml extraction tube and add 100 μ L of 2-heptanol (30 ppm) as the internal standard;

 

2. Seal the extraction tube and equalize at 50 ± 1 °C for 10 min;

 

3. Then, the NTD pre-connected to a disposable 1 mL syringe is inserted into the headspace of the extraction tube, and 30 mL of gas is loaded manually through the adsorbent (30 extraction cycles, average speed of 10 ± 2 mL min 1);

 

4. After extraction, discard the syringe and seal the two ends of the NTD with a PTFE cap;

 

5. Finally, the NTD was injected into the GC-MS system at 250 °C for 60 seconds to achieve the thermal desorption of VOC extraction;

 

* Place the NTD in a regulator for 30 min at 250 °C constant flow helium constant pressure 1 bar prior to the next extraction to reactivate the adsorbent. Unless indicated, all steps were repeated with at least three different samples (N = 3) and analyzed in three copies (N = 3).


Analyse

● Analysis was performed on the Agilent 6890N gas chromatograph system (Agilent Technologies, Palo Alto, CA, USA) coupled with the Agilent 5975 quadrupole Inert mass selection detector;

 

● The extracted compounds were separated on a BP-20 molten silica gel capillary column (60 m 0.25 mm 0.25 μ m);

 

● Non-free injection with helium at a constant flow rate of 1.0 mL min 1;

 

● Oven temperature condition: 45℃ (2 min), then a gradient temperature gradient from 45 oC for 1 min, then 2℃ / min for 90℃, then 3℃ / m to 160℃ (6 min) and finally from 160℃ to 220℃ for 15 min;

 

● The inlet temperature and ion source temperature are 250℃ and 230℃, respectively;

 

Mass spectra of ● compounds were obtained in the electron impact (EI) mode at 70 eV. The electronic multiplier is set to the automatic tuning program. Data was acquired in scan mode (mass range m / z = 35300 amu; 6 scans per second).

 

● Chromatograms and spectra were recorded and processed using the Enhanced ChemStation software (Agilent Technologies, Palo Alto, CA, USA) of GC-MS.

 

Volatile organic compounds profiles of lemon peel in different geographic regions


Image: Typical characteristics of NTME / GC-MS lemon (Eureka variety) peel from the regions investigated: Portugal (mainland and Madeira), Argentina and South Africa

 

Although the VOCs distribution of the four lemon samples is clearly similar from the profiles, some features related to the relative abundance of each VOC and functional group are special.

 

South African lemons seemed to be more fragrant than the other groups because the relative peak area sum was significantly higher (1.5 times, 2 times and 3 times the lemons of Madeira, mainland Portugal and Argentina, respectively). Monoterpenes were the most abundant functional class of all samples, representing more than 95% of the volatile fraction. This performance was mainly due to D-limonene, followed by α -and β -ene, β -ene and γ -terpenes, which had the highest amount of VOCs in all lemon samples. In contrast, the high alcohol content in mainland Portuguese lemon was much higher than that analyzed in the other groups. A similar trend was observed for aldehydes, with higher levels in Portuguese (mainland and Madeira) than in Argentine and South African samples.

 

Statistical analysis of the volatile data matrix was performed

To evaluate the potential of the volatile fingerprints obtained in this study in distinguishing the Eureka lemons according to their geographical region, the statistical analysis of the volatile data matrix was performed using the MetaboAnalyst 4.0 network tool, and the results are shown in the following figure:


As can be seen from the figure, the total variance of the first principal component (PC1) of PCA is 52.1%, which can distinguish lemon varieties grown in mainland Portugal and Madeira, (ethanol, ethyl ester, octanoate, trans- βα, basaldehyde and volatile organic compounds volatile organic compounds). The second principal component (PC2) accounted for 24.4% of the total variance of the model and separated the varieties produced in South Africa from those produced in Argentina (α -pinene, α -thujene, toluene, toluene, 1-butanol, d-limonene, and 2-methyl-2-heptene).

 

Conclusion

In this work, we report the identification of lemons using a simple analytical layout and a rather economical experimental setup for their geographical origin.

 

NTME / GC-MS provides an in-depth and comprehensive understanding of the volatile components of lemon peel (exocarp) of Eureka varieties grown in ——, Portugal (Portugal), Argentina and South Africa. A total of 75 VOCs were identified in lemon peel of the Eureka variety, a number slightly higher number than previously published findings on the same breed. The monoterpene family is the most dominant VOCs, accounting for about 95% of the volatile components of the Eureka variety lemon peel. D-limonene, β -ene, and γ -terpenes were the major volatiles identified in lemon peel of targeted geographic origin. The VOCs identified in this study were able to distinguish lemons based on their geographical area. Thus, butanaldehyde, α -ene, α -butene, 2-heptanone, D-limonene, 2-methyl-2-heptene, nonenal, decaldehyde, 1-octanol, limonene oxide, β -lytenene and 2,6-dimethyl 2,6-adiene were the VOCs that contributed the most to this distinction.

 

 INNOTEG NeedleTrap



INNOTEG The new dynamic pin capture device (Needle Trap), which fills the adsorbent in the needle tip, can be filled with up to three different commercial solid fillers. It is a new solvent-free microextraction technology, integrating sampling, extraction, concentration and injection, and is suitable for the analysis of trace volatile and semi-volatile organic compounds.

 

INNOTEG Needle Trap Dynamic needle capture technology provides a new sample preparation method for trace analysis in gaseous matrix. By increasing the amount of adsorbent and composite different kinds of adsorbent in increasing the adsorption capacity, especially the adsorption of small molecules. Rapid analysis of small sample volume and thermal analysis of internal expansion airflow without condensation device is conducive to trace grade gas analysis, with high sensitivity and low detection limit.

 

technical feature

 

1. INNOTEG Needle Trap technology is easy to operate and use, and can be used for field sampling technology;

 

2. High sensitivity, filled with a variety of adsorpb / ppt low concentration range of volatile organic compounds;

 

3. INNOTEG Needle Trap is small, the sample volume is small, the thermal resolution rate is only 30s, on the one hand, does not need the cold trap focus to desorb the sample and will not cause the tail peak, on the other hand, the input cost and use cost are greatly reduced;

 

4. Strong sample collection and storage stability, PTFE plug seal at both ends of the needle, easy to save and convenient transportation.


Size of Product

The Luer-Lock connection header

 

Length: between 50mm to 70mm

 

Diameter: the three sizes are optional

0.7mm/0.4mm；

No.22 specification (0.72mm/0.4mm);

No.23 specification (0.64mm/0.35mm);

 

Tip form: conical (side hole, blunt surface, or customized)

 

Filler: different kinds of adsorbents can be filled according to the target components to increase the adsorption capacity and adsorption range



If you are interested in this product,please email:[email protected]