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Li, Y., Ye, Z., Wang, W., Yang, C., Liu, J., Zhou, L., Shen, Y., Wang, Z., Chen, J., Wu, S., and Zhang, L. (2018). "Composition analysis of essential oil from Melaleuca bracteata leaves using ultrasound-assisted extraction and its antioxidative and antimicrobial activities," BioRes. 13(4), 8488-8504.


To extract essential oil from Melaleuca bracteata leaves without thermal degradation, ultrasound-assisted extraction (UAE) was developed and optimized using a response surface method (RSM) based on the Box-Behnken design (BBD). Under the optimized extraction conditions, a higher essential oil yield of 4.55% was achieved in comparison to that of 1.02% via the conventional hydrodistillation extraction method, which suggested that UAE could be used as an alternative and efficient extraction method for the essential oil from M. bracteata leaves. Furthermore, the composition of the essential oil extract was analyzed by gas chromatography-mass spectrometry. The results showed that 42 constituents, including methyl eugenol (86.5%), methyl cinnamate (4.33%), 3,4,5-trimethoxybenzoic acid, methyl ester (1.77%), and germacrene D (1.24%) were identified in the essential oil of M. bracteata leaves. The essential oil showed strong 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2′-azino-bis(3-ethylbenzthiazoline-6-sulphonic acid) (ABTS) radical scavenging activity, and reducing property. Additionally, remarkable bacteriostatic activity was observed against the tested pathogens, including Chromobacterium violaceum ATCC31532, Pseudomonas aeruginosa PAO1, Serratia marcescens MG1, and Serratia marcescens H30. These results indicated that the essential oil from M. bracteata leaves had potential applications due to its antioxidative and antimicrobial activities.

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Composition Analysis of Essential Oil from Melaleuca bracteata Leaves Using Ultrasound-assisted Extraction and its Antioxidative and Antimicrobial Activities

Yongyu Li,a,b Zhengmei Ye,a Wenting Wang,a Chao Yang,a Jingyuan Liu,a Liting Zhou,a Yuze Shen,a Zhiheng Wang,a Jianjun Chen,b,* Shaohua Wu,a,* and Liaoyuan Zhang c,*

To extract essential oil from Melaleuca bracteata leaves without thermal degradation, ultrasound-assisted extraction (UAE) was developed and optimized using a response surface method (RSM) based on the Box-Behnken design (BBD). Under the optimized extraction conditions, a higher essential oil yield of 4.55% was achieved in comparison to that of 1.02% via the conventional hydrodistillation extraction method, which suggested that UAE could be used as an alternative and efficient extraction method for the essential oil from M. bracteata leaves. Furthermore, the composition of the essential oil extract was analyzed by gas chromatography-mass spectrometry. The results showed that 42 constituents, including methyl eugenol (86.5%), methyl cinnamate (4.33%), 3,4,5-trimethoxybenzoic acid, methyl ester (1.77%), and germacrene D (1.24%) were identified in the essential oil of M. bracteata leaves. The essential oil showed strong 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2′-azino-bis(3-ethylbenzthiazoline-6-sulphonic acid) (ABTS) radical scavenging activity, and reducing property. Additionally, remarkable bacteriostatic activity was observed against the tested pathogens, including Chromobacterium violaceum ATCC31532, Pseudomonas aeruginosa PAO1, Serratia marcescens MG1, and Serratia marcescens H30. These results indicated that the essential oil from M. bracteata leaves had potential applications due to its antioxidative and antimicrobial activities.

Keywords: Melaleuca bracteata; Essential oil; Component; Antioxidant activity; Antimicrobial activity; Ultrasound-assisted extraction

Contact information: a: College of Horticulture, Fujian Agriculture and Forestry University, Fuzhou 350002, P.R. China; b: Environmental Horticulture Department and Mid-Florida Research and Education Center, Institute of Food and Agricultural Sciences, University of Florida, Apopka, FL 32703, USA; c: College of Life Sciences, Fujian Agriculture and Forestry University, Fuzhou 350002, P.R. China;

* Corresponding authors:;;


Melaleuca bracteata is an evergreen shrub or small tree with dense foliage belonging to the Myrtaceae family. It is aborigine throughout the eastern coast of Australia and now is widespread in many countries such as South Africa, Egypt, Thailand, China, and Indonesia (Aboutabl et al. 1991; Naidu 2003; Kardinan and Hidayat 2013; Osunsanmi et al. 2015). This plant is popularly used as an ornamental plant due to its aroma oil production. It has been reported to be rich in essential oils, betulinic acid, proline (betaine) analogues, and oleanolic acid (Naidu 2003; Wilkinson and Cavanagh 2005; Adesanwo et al. 2009; Osunsanmi et al. 2015). Melaleuca bracteata essential oil (BEO) has been regarded as an excellent source of biological agricultural chemical ingredients, and is primarily used as an antiseptic due to its antibacterial, antiulcer, antimicrobial, and insecticidal properties (Aboutabl et al. 1991; Wilkinson and Cavanagh 2005; Kardinan and Hidayat 2013; Oyedeji et al. 2014). Chemical composition analysis showed that the ingredients and their contents in BEO were remarkably different among Melaleuca species (Yatagai et al. 1998). Besides the difference of Melaleuca species, other factors such as the BEO extraction methods and conditions also affected the analysis of the ingredients and their contents, and then resulted in different BEO bioactivity (Samaram et al. 2015; Ben Ahmed et al. 2016).

Ultrasound-assisted extraction (UAE) is a relatively new, facile, and cost-effective alternative to the conventional technique for recovery essential oils from a wide variety of sources (Sereshti et al. 2012; Samaram et al. 2015). Moreover, sonication can improve the extraction efficiency and rate of target compounds despite a short processing duration, low temperature, reduced solvent consumption, and less energy input (Kowalski et al. 2015). Hence, UAE may be designated as a green and ideal option in the edible oils industry for low processing temperatures that preserve the structural and molecular properties of bioactive compounds from thermal degradation (Tian et al. 2013). To study the potential industrial applications of M. bracteata as a raw material, a UAE method for efficiently extracting essential oils from M. bracteata leaves was developed, and a higher yield was achieved under the optimal extraction conditions. The essential oil obtained by UAE was analyzed to reveal the chemical composition via gas chromatography-mass spectrometry (GC-MS). Additionally, the essential oils from M. bracteata exhibited excellent antioxidant and antimicrobial activities.



The pest-free and disease-free leaves of M. bracteata without deformity were collected from Minhou county, Fujian province of China (East of China-Fujian: north latitude 25° 47′- 26° 37′, east longitude 118° 51′- 119° 25′, altitude 29 m). These leaves were cleaned, pitted, and vacuum-dried (Four-Ring Science Instrument Co., Beijing, China) to a constant weight, followed by electric grinding (IKA-Works, Staufen, Germany). The ground powder was sieved through a 425 μm screen, collected, sealed, and preserved at 4 °C until further use.

1,1-Diphenyl-2-picrylhydrazyl (DPPH), butylated hydroxytoluene (BHT), 2,2’-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid) (ABTS), n-alkanes, dichloromethane, ampicillin, and kanamycin were obtained from Sigma-Aldrich Chemie GmbH (Steinheim, Germany). Petroleum ether (b.p. 60 °C to 90 °C), anhydrous sodium sulfate, absolute ethyl alcohol, methanol, sodium dihydrogen phosphate (NaH2PO4), disodium hydrogen phosphate (Na2HPO4), potassium ferricyanide, iron trichloride, trichloroacetic acid (TCA), and potassium persulfate (K2S2O8) were purchased from China National Pharmaceutical Group Co. (Beijing, China). Only analytical grade chemicals and solvents were used.

The tested microorganisms included S. marcescens H30, S. marcescens MG1, S. aureus ATCC25933, C. violaceum ATCC31532, and P. aeruginosa PAO1 purchased from the China Center of Industrial Culture Collection (Beijing, China) and the American Type Culture Collection (Manassas, VA, USA), respectively. The bacteria were cultured on a nutrient agar (NA) medium that was sterilized at 121 °C for 20 min in an autoclave.


UAE of essential oils

In this study, an ultrasonic extraction crasher Scientz-IID (25 kHz, maximum to 950 W, Scientz, Ningbo, China) was used for the recovery of essential oils from M. bracteata leaves. Dried ground leaves samples were mixed into petroleum ether solution (300 mL) to prepare the UAE-based system. Different experimental parameters, including ultrasonic power (X1, 190 W to 570 W), ultrasonic time (X2, 5 min to 25 min), solvent-to-solid ratio (X3, 5 mL/g to 25 mL/g), and extraction temperature (X4, 20 °C to 40 °C), were used to conduct the extraction process as described in a previous study (Samaram et al. 2015). The effect of each parameter was analyzed independently to determine the appropriate range of each variable using single-factor experiments, and subsequently their optimal levels for high extraction yield were obtained using response surface methodology (RSM). After UAE, the slurry was centrifuged at 8000 × g for 10 min to collect the supernatant in a volumetric flask. Each trial was conducted five times. The extract was preserved in dark vials at 4 °C until further use.

Box-Behnken design and optimization

The RSM based on the Box-Behnken design (BBD; Design-Expert, version 8.0.6, Stat-Ease Inc., Minneapolis, MN, USA) with three coded levels was employed to determine the optimal essential oil extraction conditions of the ultrasound power (X1), ultrasound time (X2), and solvent-to-solid ratio (X3). The level of each factor was designed in Table 2 according to the results of single-factor experiments. The low, middle, and high levels of each independent variable were designated as −1, 0, and +1, respectively, and the dependent variables were the extraction yields of the essential oil.

The correlation between the coded and real values, for statistical analysis, was established by Eq. 1,


Where  indicates the coded value of the variable,  indicates the true value of  at the centre point, and  is the step change in the variable.

Thus, herein, a three-level-three-factor BBD was employed that required 17 experiments, including 12 factorials and 5 replicates at the center point, for the optimization of the extraction parameters. The experimental yields were fitted to the second-order polynomial equation (quadratic model) for the prediction of the optimized parameters of the extraction process as follows (Eq. 2),


where Y represents the response function (in this case the extraction yield of essential oils), βo indicates a constant coefficient, βіβіi, and βіj indicate the regression coefficients of linear, quadratic, and interactive terms, respectively; and Xi and Xj represent the coded independent variables (ultrasound power, ultrasound time, solvent-to-solid ratio). A statistical analysis was conducted using Design-Expert 8.0.6 software. The results were fitted to a second-order polynomial regression model comprised of the coefficient of individual linear, quadratic, and interactive parameters. An analysis of variance (ANOVA) with a 95% confidence level for each response variable examined the significance and suitability of the model.

Conventional hydrodistillation extraction (CHE) of essential oils

Essential oils in M. bracteata leaves were extracted using a traditional hydrodistillation method following the methods of Sereshti et al. (2012). Briefly, 50 g of each leaf powder were immersed in 500 mL water and hydrodistilled in a full glass Clevenger-type apparatus to extract for 2 h (until no more essential oil was obtained). Then, the system was cooled down and the condensed essential oil was decanted. To improve the recovery, the essential oils were immersed in n-pentane, dried under anhydrous sulphate, and stored in a dark glass bottle at 4 °C until their use.

Determination of extraction yield

The extraction yield was computed as the amount of the extracted essential oils divided by the initial amount of leaf powder. For an accurate measurement, a 0.0001 g analytical balance (Mettler-Toledo International, Greinfensee, Switzerland) was used. The final percentage of the extraction yield was obtained as follows (Samaram et al. 2015) (Eq. 3):

Extraction yield (%) = [Essential oil amount / Initial sample amount] × 100 (3)

GC-MS analysis

The essential oil extracted from the M. bracteata leaf was subjected to a GC-MS analysis using an Agilent 6890N GC (Agilent Technologies Co. Ltd., Palo Alto, USA) equipped with an Agilent DB-5MS quartz capillary column (30 m × 0.25 mm, 0.25-μm film thickness) and an Agilent 5973I mass selective detector in the electronic ionization (EI) mode (Mothana et al.2013; Chen et al. 2014a) with slight modification. Helium served as the carrier gas at a flow rate of 1 mL/min, ionization energy 70 eV with a scan time of 1 s, mass range 45 m/z to 550 m/z, and solvent delay of 3.5 min. The temperature of the injector and detector was 250 °C and that of the transport line was 300 °C. The ion source and quadrupole temperatures were set as 230 °C and 150 °C, respectively. The column temperature was initially set at 50 °C (maintained for 5 min), and then increased to 100 °C at a rate of 3 °C/min (maintained for 5 min), followed by a rate of 5 °C/min up to 250 °C, which was maintained for 2 min. A 1 µL sample using a split mode with 20:1 was loaded into the GC column. The volatiles were extracted and analyzed six times. The chromatographic peaks were considered as signals when simultaneously they were different from the blank control and the signal-to-noise ratio was higher than 3:1. The data obtained were validated by comparison of the mass spectrum either to those of the reliable compounds or to the published date for the identification of the volatile leaf compounds. The relative concentrations of the components were obtained by peak area normalization.

Determination of antioxidant activity

The antioxidative properties of BEO were evaluated by the scavenging activity against DPPH and ABTS radicals and the determination of reducing power according to the methods described by Chen et al. (2014b), Dahmoune et al. (2015), and Huang et al. (2009), respectively.

Determination of antimicrobial ability

The inhibitory zone (IZ) assay of the essential oil on tested microorganisms was performed using the disc diffusion method (Al-Abd et al. 2015) with slight modifications. In brief, the essential oil was diluted to between 10 mg/mL and 40 mg/mL using dimethyl sulfoxide (DMSO) and filter-sterilized through 0.22-mm Millipore filters. All of the tested strains, adjusted to a microbial suspension of 106 CFU/mL, were cultured in nutrient medium (per liter: peptone 10 g, beef powder 3 g, NaCl 5.0 g, and a pH of 7.3) at 35 °C for 24 h with 150 rpm agitation.

A 30 μL filter-sterilized essential oil sample was spotted on a sterile paper disc (6-mm diameter), which was then placed on the surface of the agar plate (NA) preinoculated with the tested strains. Similar discs were prepared for ampicillin and methyl eugenol (10 mg/mL to 40 mg/mL) that served as positive controls, whereas DMSO was used as the negative control. These samples diffused into the agar plates for 1 h, and then the plates were inverted and incubated at 35 °C for 24 h. The diameter of the inhibition zone (mm) was measured to evaluate the antimicrobial activity of essential oil from M. bracteata leaves. Each assay was performed in triplicate and repeated at least twice to confirm the results as average values.

The minimum inhibition concentration (MIC) was determined via a broth dilution method as previously described (Al-Abd et al. 2015) with slight modifications. Each microorganism was evaluated with the essential oil sample in the concentration range of 0.08 mg/mL to 40 mg/mL and diluted by using the nutrient medium solution. A 180 μL mixture of nutrient medium and essential oil DMSO solution sterilized with a 0.22-mm Millipore filter was loaded into a 96-well plate. Then, 20 μL microorganism suspension (106 CFU/mL) was inoculated and cultured at 30 °C for 24 h with 150 rpm in a rotary shaker.

The culture concentration was determined using a microplate reader (iMark; Bio-Rad Laboratories Inc., Hercules, USA) after incubation. Culture medium without bacterial inoculation was used as the negative control. The MIC value was estimated as the minimum concentration of the sample in the 96-well where there was no visible bacterial growth after incubation.

According to the MIC values, 5 μL of the culture medium that showed no increase in turbidity was transferred from each well and streaked on a solid NA culture medium, followed by incubation at 35 °C for 24 h. The lowest concentration in the medium without bacterial growth was deemed as the minimum bactericide concentration (MBC) (Al-Abd et al. 2015).

Statistical analysis

All of the experiments were performed in triplicate, and the data were recorded as mean ± SE (standard error). The statistical analysis was used to evaluate the significance of differences between groups using the Statistical Product and Service Solutions version 19.0 software (IBM Corporation, Armonk, NY, USA). The comparisons between the groups were determined by Fisher’s Least Significant Difference (LSD) at P < 0.05 or P < 0.01. The IC50 (the concentration of antioxidant at which 50% of the reaction was inhibited) was determined using SPSS for Windows, version 19.0 (IBM Corporation, Armonk, NY, USA).


Optimizing BEO Yield Through Ultrasound-assisted Extraction using RSM

The designs and results of the single-factor experiments are shown in Table 1 and Fig. 1. The ultrasound power, extraction time, and liquid-to-solid ratio showed obvious effects on the BEO yield, while only slight influence on the BEO yield was observed when the extraction temperature was tested in the range from 20 °C to 40 °C.

Table 1. Single-factor Experimental Design

Fig. 1. The effect of ultrasound power (A), extraction time (B), liquid-to-solid ratio (C), and extraction temperature (D) on the yield of essential oil extracted from M. bracteata leaves (n = 3)

To achieve the high BEO yield, three factors, including ultrasound power, extraction time, and liquid-to-solid ratio, were further optimized to confirm the optimal levels by using RSM based on the Box-Behnken design. The experimental design and corresponding response data for BEO are shown in Table 2. Out of the 17 experiments that also included 5 replicates, experiment 9 (ultrasound power 380 W, extraction time 25 min, and liquid-to-solid ratio 20 mL/g) produced the highest BEO yield at 4.51%, while the lowest yield of 4.20% was observed in experiment 4 (ultrasound power 285 W, extraction time 15 s, and liquid-to-solid ratio 15 mL/g).

The multiple regression analysis on the experimental data demonstrated that the response variable and the independent variables correlated by the following second-order polynomial model as follows (Eq. 4),

where Y is the predicted BEO yield and X1X2, and X3 are the coded values for ultrasound power, extraction time, and liquid-to-solid ratio, respectively.

The model was further substantiated by the ANOVA. The regression coefficient and ANOVA of the second-order polynomial model for BEO yield are presented in Table 3. Only two linear parameters, ultrasound power (X1) and the liquid-to-solid ratio (X3), were significant (P < 0.05). Two quadratic parameters, ultrasound power (X1) and extraction time (X 2), were highly significant (P < 0.01). The interactions X1X2X1X3, and X2X3 were also significant (P < 0.05 or P < 0.01).

Table 2. Experimental Design and the Observed Responses Value with Different Combinations of Factors for the Trials of Box-Behnken

Table 3. Estimated Regression Coefficients of the Quadratic Polynomial Model and ANOVA for the Experimental Results of Essential Oil Extracted from M. bracteata Leaves Using UAE Method

a Coefficients refer to the general model; b Degree of freedom

The ANOVA analysis of the experimental results summarized in Table 3 implied that the quadratic polynomial model was highly significant (P < 0.0001) for representing the actual relationship between the response and parameters. Furthermore, the determination coefficient (R2) of 0.98 and the adjusted determination coefficient (R2Adj) of 0.95 were obtained for the response of BEO, which further validated the adequacy of the model. However, a large R2 value does not necessarily indicate the reliability of the regression model; however, the R2Adjshould be statistically comparable to R2 (Dahmoune et al. 2015). As shown in Table 3, the R2 and R2Adj values for the model did not differ greatly. The model also showed a statistically insignificant lack of fit at 95% confidence, which thereby indicated the adequacy of the fitted models. The value of pure error was low, which suggested the reliability and reproducibility of the model was in agreement with the previous data obtained by ANOVA. These results indicated the suitability of the model for the prediction of BEO extract from M. bracteata leaves.

The levels of the variables for BEO yield from M. bracteata leaves were determined using two-dimensional and three-dimensional surface plots of multiple non-linear regression models, which are displayed in Fig. 2. The response surface plots were constructed in Table 3 to assess the significant (P < 0.05) effect of the ultrasound extraction variables’ interaction on the BEO yield. The UAE process at the high ultrasound power and time with a high liquid-to-solid ratio resulted in a highly efficient extraction of essential oils from M. bracteata leaves.

Fig. 2. Response surface plots (3D, right) and contour plots (2D, left) of the essential oil yield extracted from M. bracteata leaves using UAE as a function of significant interactions between factors: (A) ultrasound power and extraction time; (B) ultrasound power and liquid-to-solid ratio; and (C) extraction time and liquid-to-solid ratio

Using the Design Expert 8.0.6 software, the authors identified the optimum values of ultrasound power (408.99 W), extraction time (21.08 min), and the liquid-to-solid ratio (20 mL/g), which were the three key conditions for BEO extraction from M. bracteata leaves. Additionally, these parameters predicted a maximum extraction yield of 4.55% BEO. The reliability of the model was validated by five verification experiments under optimum conditions. The mean value of BEO extraction from this experiment was 4.55 ± 0.01% (w/w, N = 5), which coincided with the predicted value and was not significant (P > 0.05) by a paired t-test. This experiment showed that the RSM model was accurate and reliable. The BEO yield from this study was considerably higher than that obtained using a conventional hydrodistillation method (1.02 ± 0.01%). As a result, the regression model was considered adequate for predicting the BEO yield extracted from M. bracteata leaves using the UAE process. Furthermore, this extraction method was straightforward and rapid.

Chemical Composition of the M. bracteata Essential Oil

The essential oil extracted from M. bracteata leaf under the optimized UAE conditions was colorless and possessed an aromatic and minty odor. The GC-MS chromatogram of the BEO is presented in Fig. 3. Table 4 illustrates the chemical components and their peak area ratios of BEO. A total of 42 volatile constituents, encompassing 98.5% of the total oil, were identified by GC-MS data. The major components of essential oil were methyl eugenol (86.5%), methyl cinnamate (4.33%), 3,4,5-trimethoxybenzoic acid, methyl ester (1.77%), and germacrene D (1.24%). The chemical compounds were characterized by the presence of three major biochemically-related groups of components. The majority of the volatiles were aromatic compounds, which accounted for 87.1% of the total. The next most abundant group of volatiles was aliphatic compounds (7.60%), followed by the third group that included the terpenoids (3.76%), such as germacrene D, α-phellandrene, p-cymene, terpinolene, β-caryophyllene, bicyclogermacrene, and calamenene.

Fig. 3. GC-MS chromatogram of essential oil obtained from M. bracteata leaves

Table 4. Chemical Components of the Essential Oil from M. bracteata Leaves