Objectives: Development and validation of the method for qualitative and quantitative determination of limonene in tangerine, grapefruit, sweet orange and lemon commercial essential oils, using gas chromatography, with the aim of reducing the analysis duration in order to save time and gasses. Material and Methods: Samples of Pranarom essential oils were used in the research, dissolved in pentane and methanol, and standard solution of limonene dissolved in methanol with mass concentrations ranging from 10 to 5×10-3 mg/mL. Column oven temperature rate was altered, while other operating conditions were kept constant. A split/splitless injector, heated to 250 ºC and with a 100:1 split ratio, was used for the analysis, with helium at constant flow rate of 1,000 mL/min as mobile phase. A capillary column with liquid, non-polar stationary phase was used. Oxygen and hydrogen were used as a fuel in the flame ionization detector, whereas nitrogen was used as makeup gas. Results: The obtained chromatograms show a good separation of sample components despite the variety of oven program rates applied. All the components take about 15 minutes to elute from the column, which is why the method involving two different oven program rates was selected as optimal. As expected, an increase in the oven temperature rate resulted in reduced retention time of limonene, but was reproducible by using the same method. It was demonstrated that there is no significant difference in results obtained by the use of methanol as solvent as opposed to the use of pentane, which is why methanol, due to the fact it is easier to handle, was selected as the solvent of choice. Conclusions: An increase in the oven program rates was shown to lead to a significant reduction of the duration of analysis - from 90 minutes in the first method down to 23 minutes and 51 seconds in the last. Regardless of the program rate, the quality of the results was kept, i.e. good separation of components and reproducible limonene retention time. Due to reduced gas consumption, the application of the optimal method results in a decrease of analysis costs.