Studies of hybrid drying optimisation of ultrasound assisted osmotic dehydration (UOAD) and hot-air drying on Eucalyptus Deglupta (rainbow Eucalyptus)
Cite as: AIP Conference Proceedings 2137, 020006 (2019); https://doi.org/10.1063/1.5120982 Published Online: 07 August 2019
Khor Yit Cheng, Chua Bee Lin, and Tee Lee Hong
Studies Of Hybrid Drying Optimisation Of Ultrasound Assisted Osmotic Dehydration (UOAD) And Hot-Air Drying
On Eucalyptus Deglupta (Rainbow Eucalyptus)
Khor Yit Cheng
1,a), Chua Bee Lin
1,b)and Tee Lee Hong
1,c)1School of Engineering, Taylor’s University Lakeside Campus, No. 1 Jalan Taylor’s, 47500 Subang Jaya, Selangor, Malaysia
a) YitChengKhor@gmail.com
b) Corresponding author: BeeLin.Chua@taylors.edu.my c) LeeHong.Tee@taylors.edu.my
Abstract. Eucalyptus Deglupta is one of the medicinal plants from the Myrtaceae family that exhibits promising antioxidant activity in comparison to the commercial antioxidant Butylated hydroxyanisole (BHA). As a result, the isolation of bioactive compounds from medicinal plants has become priorities. It is in this perspective that our study was undertaken with the objective to optimise the hybrid drying conditions of Eucalyptus Deglupta leaves to increase the yield of total phenolic content (TPC). The optimisation was performed using Central composite experimental design (CCD) to evaluate the effect of four independent variables which were temperature, time, the intensity of ultrasound and osmotic concentration at 20-60 °C, 60-100 min, 198-330 W and 30-50% (w/v). Under optimal drying conditions which were temperature at 59.91 °C, duration of ultrasound at 60.13 min, intensity of ultrasound at 99.77% (330 W) and osmotic concentration at 30.63%, the TPC value was 5.029 mg GAE/g dried leaves.
INTRODUCTION
Over the centuries, natural products originating from plants have formed the basis for the traditional medical system all over the world. Such substances draw the attention of researchers due to their diversity of applications and act as a fundamental role in empowering the discovery of new drugs for medication. Eucalyptus Deglupta (Rainbow Eucalyptus) is a precious plant which categorised under Mytaceae family that originates from Australia[1]. As reported in the past findings, the most valuable part of the plant which is the leaves of Eucalyptus Deglupta [2]. Studies show that there is a large range of biological activities present in the most of the Eucalyptus leaves, for instance, antimicrobial, larvicide, cytotoxic, antioxidant, antidiabetic and anti-inflammatory [3-5] .
Antioxidants are the substances that protect cells against the effect of free radicles as free radicles may be a factor in heart disease and cancer [6]. In the previous findings, some research papers showed that the main contributor to antioxidant activity is the phenolic compounds which were influenced by the existence of p-cymene and -pinene in Eucalyptus Deglupta [7]. Therefore, in this study, the leaves of Eucalyptus Deglupta are chosen to optimise the yield of the total phenolic content (TPC).
The primary aim of this study is to reinvestigate at the concept of isolating bioactive compounds from a new perspective. So far, most studies on isolating the bioactive compounds have focused on improvising the extraction technique. In this study, the focus has been shifted to the drying treatment with a combination of osmotic dehydration coupled with ultrasound pre-treatment and hot-air drying instead of extraction for the effective recovery of TPC as it is a necessary pre-treatment step to enabling the extraction process.
Drying is a primary process prior to the phytochemical extraction process. It is a mass transfer process that deals with the removal of moisture content from another matter. There are multiple commercially used drying methods existing in the industry such as osmotic dehydration, conventional hot air drying, freeze drying and solar drying.
However, the above-mentioned methods have some obvious drawbacks such as high energy consumption, time- consuming, high cost and, low retention of bioactive compound [8-10]. Hence, a preliminary drying is being introduced in this study to reduce the negative impacts caused by conventional methods.
Osmotic dehydration method is a technique that is commonly applied in the industry. This method is the phenomenon of water removal from a lower concentration of solute to a higher concentration of solute permeating through a semi-permeable membrane to achieve equilibrium. It is affected by various parameters such as sucrose concentration, temperature and the ratio of sucrose solution to sample [10]. Food preservation industry typically as it serves to slow down spoilage and rancidity which are caused by micro-organism. However, osmotic dehydration has a slow diffusional characteristic and not able to fully reduce the moisture content in the raw product.
On the other hand, convective hot-air drying is also another frequently utilized method commercially in the industry. This method involves the distribution of hot air in a chamber with the aid of a fan or blower with a heating element. However, this drying method has been found to exhaust a large amount of energy and time, which also affects the quality of the final product [11]. Consequently, by introducing an ultrasound pretreatment to the drying process, these shortcomings can be eradicated.
Ultrasound is a key-technology in achieving the objective of sustainable “green” chemistry and drying [12]. The positive effects of introducing ultrasound assisted drying have been proven in the drying of numerous fruits and vegetables. However, to date, there is yet to have a study that has investigated the influence of ultrasound-assisted drying effect on Eucalyptus Deglupta, particularly to retain and maximise TPC. High-intensity ultrasound pre- treatment can be utilised to further improve the conventional hot-air drying technique by enhancing the heat and mass transfer both by diffusion inside the material and by convection close to the material surface. This kind of agitation serves to reduce external resistance to mass transfer by increasing the bulk transport within the fluid [13].
This will lead to the increase of the pore sizes on the surface of the leaves so that the mass transfer of the water on the surface of the leaves can take place more efficiently. According to the previous studies, it was reported that the use of ultrasonic waves as a supporting factor increased the rate of drying without affecting the quality of the product [14, 15].
To the best of authors’ knowledge, there is no known study on the sequential osmotic dehydration and hot-air drying enhanced with ultrasound to optimise the TPC from Eucalyptus Deglupta extract. Therefore, in this study, a hybrid drying method, namely ultrasound assisted osmotic dehydration (UAOD) with hot-air drying, which comprises of contracting ultrasound system coupled with osmotic dehydration and hot-air drying oven will be applied for the dehydration of Eucalyptus Deglupta leaves to remove all the moisture content in the Eucalyptus Deglupta leaves to further determine the TPC presented in the leaves. The ultrasound pre-treatment conditions which are temperature, ultrasound intensity, duration of the ultrasound and the concentration of the osmotic solution will be optimised via response surface methodology (RSM) to obtain the highest yield of TPC [16].
METHODOLOGY
This section discussed the methods that were carried out in this research in order to accomplish the objectives mentioned above.
Experimental Setup
2 kg of Eucalyptus Deglupta leaves were rinsed and cleaned with distilled water to remove dirt on the surface.
Absolute ethanol with a purity of 99.5% (HPLC Grade) and sucrose crystals of the multi-compendial grade was purchased from J.T. Baker (UK). Gallic acid. Folin-Ciocalteu reagent, sodium carbonate were purchased from Sigma Aldrich (USA). Ultrapure water was utilised throughout the experiment to prepare all the aqueous solutions and serial dilutions.
Experimental Design
The effects of pre-drying temperature (Tp, °C), pre-drying duration (Tpd, min), the intensity of the ultrasound (Ip, W) and osmotic solution concentration (Op, %) with two different levels were studied on the extraction yield of phenolic content (TPC). The selected independent variables and their variation ranges were determined based on past findings that applied to the drying of the medicinal plants [6] [15] [17, 18]. Response surface methodology (RSM) with CCD was employed in this. Table 1 below shows all the experimental variables involved in the study.
TABLE 1. RSM parameters
Variable Definition and units Nomenclature Value or Range
Fixed Liquid to solid ratio of extraction (v/w)
Shaking speed (rpm) LSR
SPD 20 g/mL
120 Independent Pre-drying temperature (°C)
Pre-drying duration (min) Intensity of ultrasound (W)
Osmotic solution concentration (%) (w/v)
Tp
Tpd
Ip
Op
20-50 °C 60-300 min 198-330 W 30-50%
Dependent Total phenolic content (mg GAE/g dried leaf) Y1
Experimental data were fitted using a second-order polynomial described by the Eq. (1):
(1)
Where k represents the number of variables, represents the constant term, represents the coefficients of linear parameters, represents the variables, represents the residual associated and represents the coefficients of the interaction parameters of the experiments. The ranges of each factors were normalized from -1 to 1 by applying coding scheme equation described by Eq. (2):
2 2
(2)
Where represents the normalized values of the factors, X represents the experimental values of factors, represents the maximum experimental values of factors and is the minimum experimental values of factors.
Table 2 shows the extraction parameters and levels.
TABLE 2. Extraction parameters and levels
Parameters Code Levels
-1 0 1
Pre-drying temperature (°C) Tp 20 40 60
Pre-drying duration (min) Tpd 60 80 100
Intensity of ultrasound Ip 198 264 330
Osmotic solution concentration (%) Op 30 40 50
Pre-Drying of Eucalyptus Leaves (Ultrasound Assisted Osmotic Dehydration)
The osmotic solution of sucrose was prepared by mixing food grade sucrose with water [10] ranging from 30%
(w/v) to 50% (w/v) [3] [17] [19]. The water to leaves ratio was maintained at 7:1 (weight basis) throughout the whole experiment to maintain the consistency of the results.
The samples immersed in the osmotic solution was then placed into the ultrasonic bath (ELMA P120H, Germany) filled with distilled water and were subjected to ultrasonic waves for a period of 60 to 100 minutes. The pre-drying was carried out under the temperature ranging from 20°C to 60°C [3]. The frequency of the ultrasonic waves was kept at 80 kHz [20]. The intensity of the ultrasound was studied at a range of 198 W to 330 W in this study. The samples were removed and wiped with tissue paper before proceeding into the next step to prevent the forming of sucrose crystals.
Complete Moisture Removal with Hot-Air Drying
Adopting the optimised ultrasound conditions, samples were then completely dried in the second stage which was hot air drying (HAD) at 60 °C using an oven (Memmert, Germany) [21, 22]. The oven temperature was kept constant at 60 °C [9] [11] [23]. The drying was deemed to be completed when the weight of the leaves was constant which weighed using weighing balance (Pioneer Ohaus PA4102, USA). After heating, the leaves were ground and sieved through a 500 µm mesh size using sieve shaker machine (Haver & Boecker RX-812-1, Canada). The sieved powders are being sealed airtight in Scott’s bottle and being stored in the chiller for future uses [9] [17] [24].
Extraction of Essential Oil
The extraction of essential oil was performed according to [25] with slight modification. 1 g of dried powder was placed in a centrifugal tube using aqueous ethanol (HPLC Grade) as the solvent. The ratio of solid to solvent is being kept at 1:5 g/mL and place in an orbital shaker (YIHDER LM-400D, China) with a shaking speed of 120 rpm and 25°C for 30 minutes. Then the centrifuge tube containing the extract is then centrifuged at 10000 rpm to separate the solution from solids [25, 26].
Determination of Total Phenolic Content (TPC)
Total phenolic content (TPC) was determined by Folin-Ciocalteu (FC) method using microplate reader from [27]
with slight modifications. Briefly, 25 µL of Gallic acid with concentration ranging from 0 to 0.5 mg/mL mixing with 25 µL with FC reagent which was diluted 1:2 (v/v) with ultrapure water, and 75 µL of ultrapure water. The mixtures were mixed by using orbital shaker (YIHDER LM-400D, China) for 1 minute and left to sit for 5 minutes. Then, 100 µL of 75 g/L of a sodium carbonate solution was added into each well and left to sit for 90 minutes. The absorbance of each mixture was measured using microplate reader (BioTek Epoch 2, USA) at a wavelength of 760 nm and the calibration curve is generated. Note that all the experiments are performed in a dark room and triplicated to obtain the average value. The steps were repeated by replacing the gallic acid with the Eucalyptus leaves extract and the results were expressed as mg of gallic acid equivalents (GAE)/0.1 g dried leaf.
Statistical Analysis
The significance levels of the factors in the models were then determined using analysis of variance (ANOVA) for each response. The degree of confidence in the data was estimated using a t-test to determine the probability level to be less than 5% (p < 0.05). The model accuracy was checked by the coefficient of determination (R2) and root mean square (RSME) as shown in Eq. (3) and Eq. (4) [14].
1 ∑
∑
Where Mp represents the predicted data, Me represents the experimental data, represents the average experimental data and N is the number of observations.
Validation of Optimised Conditions
The validation was performed using the optimised conditions suggested by RSM to prove that the optimum condition yields the highest TPC content.
RESULTS AND DISCUSSIONS Gallic Acid Calibration Curve
In this work, the total phenolic content of the dried Eucalyptus Deglutpa leaves was determined using gallic acid as a standard ranging from 0 mg/mL to 0.5 mg/mL. The tests were triplicated to obtain an average result to increase the reliability of the results. The results were shown in Table 3 and the calibration curve was plotted as Fig. 1 below.
TABLE 3. Absorbance of gallic acid at different concentration Concentration
(mg/mL)
Absorbance
Run 1 Run 2 Run 3 Average
0.0 0.065 0.062 0.066 0.064
0.1 0.677 0.599 0.643 0.640
0.2 1.272 1.320 1.267 1.289
0.3 1.927 1.864 1.884 1.892
0.4 2.554 2.597 2.62 2.590
0.5 3.250 3.245 3.317 3.271
FIGURE 1. Gallic acid calibration curve using average value
According to the calibration curve, the model generated had a coefficient of determination (R2) of 0.999 which means the model generated as shown in Eq. (5) and the calibration curve is reliable.
y = 6.4245x + 0.0182 R² = 0.999
0 1 2 3 4
0 0.1 0.2 0.3 0.4 0.5 0.6
Absorbance
Gallic acid concentration (mg/mL)
Gallic Acid Calibration Curve
(3)
∑ (4)
6.4245 0.0182 (5)
Control Assay
In this study, the control assay is hot-air drying performed at 60°C. All the different tests were conducted for control assay were triplicated to obtain an average value to ensure the result is consistent. The results were shown in Table 4 below.
TABLE 4. TPC in control assay (hot-air drying only)
Types of Tests Results
Run 1 Run 2 Run 3 Average
Folin-Ciocalteu 0.322 0.307 0.298 0.309 (mg GAE/0.1 g
dried leaf)
Optimisation of Response Surface Methodology (RSM)
The optimisation of the UOAD pre-treatment process using RSM would not only provide a visual aid to have a better idea about the effects of various independent pre-treatment parameters using UOAD, but it’ll also assist us to identify and locate the optimised region and combinations. RSM coupled with central composite design (CCD) was applied to optimise the level of the significant extraction parameters from the literature review. The purpose of the application of RSM was to obtain the highest extraction yield of TPC within the UOAD pre-treatment parameters where the feasibility of the experiment was taken into consideration.
Pre-drying temperature (Tp, °C), pre-drying duration (Tpd, min), the intensity of the ultrasound (Ip, W) and osmotic solution concentration (Op, %) were the independent variables selected to be optimised for the yield of TPC from Eucalyptus Deglupta. Extraction yield of TPC (Y1) was taken as the responses of the design experiments. The experiments conducted in this sub-section were targeted toward constructing a quadratic model consisting of twenty- seven runs. In brief, sixteen experiments of different combination with different levels were augmented with eleven combinations using center points of the parameters were carried out to evaluate the pure error in the experiments.
Central Composite Design (CCD) of the Extraction Yield of TPC
Table 5 below shows the design matrix and the corresponding experimental and the predicted result of CCD for the extraction yield of TPC (Y1) designed with Design Expert 8.0.6. The experimental results were expressed as mean values as all the tests are triplicated.
Referring to Table 5, result shows that the extraction yield of TPC ranging from 0.3047 to 0.5273 mg GAE/0.1g dried leaf. Experiment 6 (Tp = 20 °C, Tpd = 100 min, Ip = 60% (198 W) and Op = 50.00%) gave the highest yield of TPC content (0.5273 mg GAE/0.1g dried leaf) and experiment 10 (Tp = 60°C, Tpd = 60 min, Ip = 60% (198 W) and Op = 50%) gave the lowest yield of TPC content which is 0.3047 mg GAE/0.1g dried leaf.
Statistical analysis performed on the data of the triplicated experiments using average value (mean) were carried out using analysis of variance (ANOVA) procedure of the Design-Expert 8.0.6 software. ANOVA was carried out to determine the coefficient of determination (R2), lack of fit and the significance of linear, quadratic and interaction effects of the independent variable on the response. Table 5 below shows the results of the statistical analysis performed by ANOVA for the response surface quadratic polynomial model for the extraction yield of TPC.
TABLE 5. Central composite design with experimental and predicted yield of TPC
Std Run Temp,
Tp
(°C)
Duration,
Tpd (min) Intensity, Ip (%)
Osmotic Conc,
Op (%)
Yield of TPC, Y1 (mg GAE/0.1 g dried leaf)
Experimental Predicted
18 1 20 60 60 30 0.4135 0.408
23 2 20 60 60 50 0.3827 0.381
2 3 20 60 100 30 0.5129 0.496
9 4 20 60 100 50 0.4922 0.502
16 5 20 100 60 30 0.4724 0.478
7 6 20 100 60 50 0.5273 0.518
3 7 20 100 100 50 0.3933 0.408
13 8 20 100 100 50 0.4154 0.408
17 9 60 60 60 30 0.4705 0.462
6 10 60 60 60 50 0.3047 0.305
15 11 60 60 100 30 0.5211 0.531
24 12 60 60 100 50 0.4887 0.472
25 13 60 100 60 30 0.4820 0.473
8 14 60 100 60 50 0.4419 0.448
4 15 60 100 100 30 0.3453 0.337
12 16 60 100 100 50 0.3471 0.345
5 17 40 80 80 40 0.4022 0.432
27 18 40 80 80 40 0.4281 0.432
20 19 40 80 80 40 0.4339 0.452
21 20 20 80 80 40 0.4539 0.441
11 21 60 80 80 40 0.4048 0.423
26 22 40 60 80 40 0.4319 0.446
14 23 40 100 80 40 0.4208 0.418
19 24 40 80 60 40 0.4384 0.423
1 25 40 80 100 40 0.4336 0.428
10 26 40 80 80 30 0.4267 0.437
27 27 40 80 80 50 0.4429 0.427
Analysis of Variance (ANOVA) for Quadratic Polynomial Model
The significance of each regression coefficient and the strength of the interaction between each linear independent variable were determined using Fisher’s F-test and p-value. The level of significance is determined by having a large F-value and a smaller p-value [28]. The data is plotted in Table 6 below that shows the regression analysis based on the experimental results.
TABLE 6. ANOVA analysis for quadratic model of RSM (Yield of TPC)
Source Sum DF Mean
Square
F Value
p-value Prob > F of squares
Model 0.070783 14 0.005056 20.54195 < 0.0001
Tp -Temperature 0.001601 1 0.001601 6.503713 0.0255
Tpd -Duration 0.001951 1 0.001951 7.926619 0.0156
Ip -Intensity 5.67E-05 1 5.67E-05 0.230234 0.6400
Op -Osmotic
concentration 0.000308 1 0.000308 1.251767 0.2851
TpTpd 0.000281 1 0.000281 1.14249 0.3062
TpIp 0.000207 1 0.000207 0.841633 0.3770
TpOp 0.007278 1 0.007278 29.57044 0.0002
TpdIp 0.0338 1 0.0338 137.3273 < 0.0001
TpdOp 0.00386 1 0.00386 15.68286 0.0019
IpOp 0.00098 1 0.00098 3.983374 0.0692
Tp2 0.000136 1 0.000136 0.550595 0.4723
Tpd2 6.38E-05 1 6.38E-05 0.259131 0.6199
Ip2 4.56E-05 1 4.56E-05 0.185115 0.6746
Op2 2.56E-05 1 2.56E-05 0.103982 0.7527
Residual 0.002954 12 0.000246
Lack of Fit 0.00214 9 0.000238 0.87616 0.6162
Pure Error 0.000814 3 0.000271
Cor Total 0.073737 26
Std. Dev 4.33
Mean 31.67
R2 0.9509
Adj-R2 0.8935
Adeq Precision 16.129
The p-value for both models was determined to be less than 0.0001 and the Fisher’s F-test had a high F-value for the polynomial model, which was 20.54195, implying the derived model is significant. Hence, the analysis of variance revealed that the model generated was adequately fitted the experimental data for the extraction yield of TPC from the low p-value.
As for the lack of fit, the p-value for was 0.6162 which indicated the lack of fit is not significant relative to the pure error. This shows that there was a satisfactory fit between response surface models and the experimental data [18] [29].
The coefficient of determination (R2) was also employed in this study to check the adequacy of the fitted quadratic model for the response. It is shown R2 value is larger than 0.95 which proved the response was a good model fit. Adequate precision measures the error related to the predicted response and the desired value was above 4. The results showed that the model’s adequate precision value was 0.9509 which represented the feasibility of the model that could be used inside the operating region [18] [29].
Fitting the Polynomial Models
By applying a multiple regression analysis from the central composite design (CCD), it was found that a second- order polynomial model produced a satisfactory fitting of experimental data based on the yield of TPC extracted from Eucalyptus Deglupta leaves. A mathematical model was generated in Eq. (7) below to describe the effects of the four independent processing variables which are pre-drying temperature (Tp), pre-drying duration (Tpd), ultrasound intensity (Ip) and concentration of osmotic solution (Op).
0.43 0.011 0.013 0.002145 0.004571 0.005249
0.004544 0.016 0.06 0.017 0.00841
0.008497 0.003783 0.004191 0.003141
(7)
Effect of the independent parameters on TPC
Effect of Pre-Drying Temperature on Yield of TPC
FIGURE 2. Significance of pre-drying temperature on TPC of Eucalyptus Deglupta
Figure 2 shows that the yield of TPC was slightly affected by the temperature as it decreased inverse proportionally to the pre-drying temperature. This parameter was very significant because the p-value for the yield of TPC was small with p<0.05. The yield of TPC was at the lowest when the essential oils were associated with a temperature of 60 °C. Therefore, using the high temperature during pre-drying phase gave rise to low yields of TPC of the medicinal plant and this result aligned with other researchers [12] [15]. This was because the essential oil content decreased significantly with the increasing of drying temperature as there was more essential oil loss as a result of compromising the biological structure of the oil glands. [30] reported that the epithelial cells in the leaves can collapse at the split at a higher temperature which allows the essential oil to flow out of the leaves which caused the lower TPC yield present in the leaves.
Effect of Pre-Drying Duration of Yield of TPC
FIGURE 3. Significance of pre-drying duration on TPC of Eucalyptus Deglupta
In this study, the duration of pre-drying duration on the effect of the yield of TPC was significant as shown in the graphs in Fig. 3. Longer duration of pre-drying might reduce the time needed for hot air drying as more moisture content are being lost to the osmotic solution in the process. However, longer duration allows the mass transfer for the phenolic compounds to be travelled to the osmotic solution as the cavitation occurs on the pores of the leaves which facilitate the mass transfer of the essential oil as well [10] [31].
Effects of Ultrasound Intensity on the Yield of TPC
FIGURE 4. Significance of ultrasound intensity on TPC for Eucalyptus Deglupta
As shown in Fig. 4, the ultrasound intensity barely had any significance to the yield of TPC. The p-value for the response was larger than 0.05 (p > 0.05). This was most likely due to the limitation of the equipment where the maximum intensity of the ultrasound that it could produce was at a range of 115 W to 330 W only. Based on previous studies, high intensity of ultrasound could attribute to the higher amplitude of ultrasound passing through the product, which resulted in intense cavity collapse [12]. This resulted in an increase in physical effects such as cracked or damaged cell walls, increased solute diffusion, local energy dissipation and interfacial turbulence which caused more TPC flowing into the osmotic solution.
Effects of Concentration of Osmotic Solution on the Yield of TPC
FIGURE 5. Significance of osmotic concentration on TPC of Eucalyptus Deglupta
As seen in Fig. 5, the concentration of osmotic solution alone exhibited minimal significance on the yield of TPC. However, both TPC and osmotic concentration exhibited an inversely proportional relationship. This was because any further increases in osmotic concentration might increase the yield of TPC as the viscosity of the osmotic solution increases. This phenomenon inhibited the fluidity of the mass transfer of TPC content out of the leaves as the viscosity of the solvent exhibited external resistance on the Eucalyptus leaves but the effect for moisture removal might be affected [10] [31].
Validation of the Model
Validation experiments were designed to check the adequacy and the reliability of the model equations under the best combination of the parameters (to maximise yield of TPC) as predicted by Design Expert 8.0.6. The yield of the TPC obtained was 5.047 mg GAE/g dried leaves which agreed with the predicted value of 5.029 mg GAE/g
dried leaves and scavenging activity by applying the model equation. The relative error for measured value and the theoretical value was 0.358%.
CONCLUSION
Present study involved the application of ultrasound-assisted osmotic dehydration (UOAD) for the recovery of phenolic compound with 4 different linear variables which were temperature of pre-drying (40 to 60°C), duration of pre-drying (60 to 100 min), ultrasound intensity (198 to 330 W) and osmotic concentration of (30 to 50%).
Experimental data was collected in the form of the yield of total phenolic content (TPC). The integration of this pre- treatment was to evaluate the effects on the TPC of the Eucalyptus Deglupta leaves.
The objective which was to optimise the UOAD pre-treatment conditions of Eucalyptus Deglupta based on the highest yield of TPC had been achieved via response surface methodology (RSM). The optimisation of the pre- treatment conditions was successfully carried out using CCD utilising its desirability function to maximise the yield of TPC. It was proven to be a success as the R2 value obtained from TPC was higher than 0.95. The optimum pre- drying conditions were: Temperature at 59.91 °C, duration of ultrasound at 60.13 min, Intensity of ultrasound at 99.77% (330 W) and osmotic concentration at 30.63%, the response values were 5.029 mg/g dried leave. The models were further validated by repeating the experiment at the optimum condition and the error obtained were 4.06% for the yield of TPC. Therefore, the results depicted the suitability and validation of the extraction model adopted and confirmed that the response model could adequately reflect the expected optimisation.
ACKNOWLEDGEMENT
The authors gratefully acknowledge the financial support provided by Taylor’s University Lakeside via Taylor’s Research Grant Scheme (TRGS/MFS/1/2017/SOE/008) for this study.
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