Heat assisted extraction of phenolic compounds from Eleutherine bulbosa (Mill.) bulb and its bioactive profiles using response surface methodology

Industrial Crops & Products 144 (2020) 112064

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Heat assisted extraction of phenolic compounds from Eleutherine bulbosa (Mill.) bulb and its bioactive profiles using response surface methodology

T

Ammar Akram Kamarudina, Norhaizan Mohd. Esaa,b,*, Norazalina Saadc, Nor Hafiza Sayutia, Nor Asma Ab. Razaka a

Laboratory of Molecular Biomedicine, Institute of Bioscience, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia Department of Nutrition and Dietetics, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia c Laboratory of Cancer Research UPM-MAKNA (CANRES), Institute of Bioscience, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia b

ARTICLE INFO

ABSTRACT

Keywords: Eleutherine bulbosa Response surface methodology Central composite design Phenolics Antioxidant HPLC

Eleutherine bulbosa Mill. bulb or Dayak onion was reported to have various health benefits. However, the study of the phenolic content and antioxidant activity of this plant is scarce. This work was aimed to optimise the extraction of phenolic compounds from E. bulbosa bulb using response surface methodology (RSM). The antioxidant activities of the extracts were then analysed. Central Composite Design (CCD) was employed with four factors at five coded levels. The extraction parameters employed were temperature (XA ), extraction time (), solid-liquid ratio (X C ), and ethanol concentration (XD ), which were found to affect response variables significantly; thus, fitted the second-order polynomial. The optimum extraction conditions obtained were temperature (XA ): 45 °C, extraction time (XB ): 70 min, solid-liquid ratio (X C ): 10:146 (w/v), and ethanol concentration (XD ): 90 %. HPLC analysis revealed eight biologically active constituents such as eleutherine, gallic acid, chlorogenic acid, quercetin, kaempferol, rutin, epicatechin gallate, and myricetin. The findings suggested the potential application of a useful, clean, cost-effective method of RSM to acquire these biologically active compounds from E. bulbosa bulb that could be utilised in food applications and future pharmaceutical industries.

1. Introduction Eleutherine bulbosa (E. bulbosa) or Dayak onion is a herbaceous plant that belongs to the family of Iridaceae. The plant is widely cultivated across South America, Africa, and South East Asia, such as Indonesia (Kusuma et al., 2010; Insanu et al., 2014). It has several scientific names such as Eleutherine americana and Eleutherine palmifolia. However, E. bulbosa is currently the accepted scientific name for this particular plant species, according to Kew and Missouri Botanic Garden databases (Couto et al., 2016). Morphologically, this plant is herbaceous and perennial with a red bulb that has a close similarity to onions (Rivella, 2000). The bulb of E. bulbosa comprises of three major compounds groups, i.e. naphthalene, anthraquinone, and naphtoquinone (Betteridge, 2000; Wang et al., 2015). Meanwhile, the isolated compounds from this herbaceous plant are eleutherin, isoeleutherin, eleutherol, isoeleutherol, hongconin, eleutherinol, elecanacin, eleutherinoside A and B, as well as eleuthraquinone A and B (Insanu et al., 2014).

Pharmacologically, the bulb has been reported to exhibit various biological properties, for instance, antimicrobial, anti-inflammatory, antihypertension, anti-diabetic and anti-melanogenetic activities as well as an analgesic (Insanu et al., 2014; Do et al., 2014). Extraction is the most crucial step to attain bioactive compounds from plant matrices. However, conventional extraction process has limitation in terms of time and yield since extensive optimisation of process variables needs to be done to increase the yield. According to Aybastıer et al. (2013), the efficiency of the extraction procedure can be affected by many aspects, for instance, temperature, extraction time, solid-liquid ratios, and the type of solvent used. Phytochemical compounds with potential therapeutic effects have been traditionally extracted using organic solvents such as methanol, acetone, and chloroform. However, these organic solvents could be harmful and toxic to human health (Li et al., 2006). A simple and economical method using ethanol was developed for phenolic extraction of E. bulbosa bulb. Since ethanol can dissolve both polar and non-polar compounds, it would be the best candidate to extract phenolic compounds from E. bulbosa bulb.

Corresponding author at: Department of Nutrition and Dietetics, Faculty of Medicine and Health Sciences, Universiti Putra Malaysia, 43400, Serdang, Selangor, Malaysia. E-mail addresses: [email protected] (A.A. Kamarudin), [email protected] (N. Mohd. Esa), [email protected] (N. Saad), [email protected] (N.H. Sayuti), [email protected] (N.A. Ab. Razak). ⁎

https://doi.org/10.1016/j.indcrop.2019.112064 Received 2 August 2019; Received in revised form 17 December 2019; Accepted 19 December 2019 0926-6690/ © 2019 Published by Elsevier B.V.

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Table 1 Central composite design (CCD) for process parameters and corresponding response variables. Runs

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 a b c d

Extraction condition

Response variables

Points

Temperature (XA -°C)

Time (XB - min)

Solid-Liquid ratio (XC - w/v)

Concentration of ethanol (XD - %)

TPCa (mg GAE/g sample)

TFCb (mg RE/g sample)

DPPHc (%)

Axial Fact Fact Centre Fact Fact Fact Fact Centre Fact Axial Centre Axial Centre Axial Fact Centre Axial Fact Fact Fact Fact Fact Axial Fact Fact Axial Axial Centre Fact

50 40 40 50 40 40 40 60 50 60 50 50 50 50 70 60 50 50 60 40 40 60 60 30 60 60 50 50 50 40

70 (0) 90 (1) 50 (-1) 70 (0) 50 (-1) 90 (1) 50 (-1) 90 (1) 70 (0) 50 (-1) 110 (2) 70 (0) 70 (0) 70 (0) 70 (0) 90 (1) 70 (0) 70 (0) 50 (-1) 50 (-1) 90 (1) 90 (1) 90 (1) 70 (0) 50 (-1) 50 (-1) 30 (-2) 70 (0) 70 (0) 90 (1)

175 (2) 50 (1) 100 (-1) 125 (0) 150 (1) 100 (-1) 100 (-1) 100 (-1) 125 (0) 100 (-1) 125 (0) 125 (0) 125 (0) 125 (0) 125 (0) 150 (1) 125 (0) 125 (0) 150 (1) 150 (1) 150 (1) 150 (1) 100 (-1) 125 (0) 150 (1) 100 (-1) 125 (0) 75 (-2) 125 (0) 100 (-1)

80 (0) 70 (-1) 90 (1) 80 (0) 70 (-1) 70 (-1) 70 (-1) 90 (1) 80 (0) 90 (1) 80 (0) 80 (0) 100 (2) 80 (0) 80 (0) 90 (1) 80 (0) 60 (-2) 70 (-1) 90 (1) 90 (1) 70 (-1) 70 (-1) 80 (0) 90 (1) 70 (-1) 80 (0) 80 (0) 80 (0) 90 (1)

71.16 ± 2.55 72.79 ± 9.86 95.63 ± 7.85 95.63 ± 0.81 73.86 ± 4.20 59.89 ± 11.13 74.14 ± 5.04 92.94 ± 4.25 88.89 ± 2.21 88.89 ± 5.10 76.20 ± 7.20 86.62 ± 2.78 97.55 ± 13.95 92.87 ± 3.30 79.82 ± 23.06 88.82 ± 18.21 91.80 ± 1.83 71.87 ± 2.66 75.70 ± 18.55 101.80 ± 16.18 96.91 ± 11.30 70.38 ± 19.12 87.76 ± 0.77 77.83 ± 2.60 77.83 ± 1.93 74.35 ± 6.28 77.40 ± 1.60 72.79 ± 5.10 88.68 ± 11.31 100.74 ± 2.48

21.94 26.20 26.06 39.82 26.34 17.90 22.72 27.26 44.57 24.99 20.03 39.96 30.67 47.40 34.43 29.60 48.82 21.31 22.16 30.31 27.55 29.82 30.88 22.09 28.96 20.74 25.84 18.18 42.23 26.48

58.18 57.05 69.16 72.28 57.28 49.68 52.35 70.48 72.51 66.75 58.48 73.67 68.33 72.47 64.54 65.06 75.33 51.97 53.48 71.83 69.69 54.61 58.18 57.73 67.96 55.51 58.97 58.71 72.06 71.72

(0) (-1) (-1) (0) (-1) (-1) (-1) (1) (0) (1) (0) (0) (0) (0) (2) (1) (0) (0) (1) (-1) (-1) (1) (1) (-2) (1) (1) (0) (0) (0) (-1)

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

2.56 6.33 0.75 2.10 4.36 4.69 1.73 1.95 5.20 1.07 9.64 1.61 1.89 2.56 14.37 18.90 0.77 2.46 13.21 22.03 11.47 12.57 6.27 2.30 1.38 2.28 5.71 1.13 2.33 11.28

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

ABTSd (%) 3.36 0.53 0.90 0.64 2.35 5.70 2.19 0.20 6.90 1.83 3.51 1.86 0.63 2.83 1.41 2.10 5.12 2.01 2.87 0.34 0.85 1.50 4.56 2.73 0.56 1.79 0.97 0.39 5.12 2.10

59.17 58.89 70.81 73.96 61.64 51.24 54.89 74.24 71.71 72.89 61.14 71.93 75.42 72.16 60.74 71.03 69.97 56.97 57.65 77.05 72.67 54.89 60.35 60.63 68.90 55.91 62.43 56.36 70.25 75.48

± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ± ±

0.64 0.19 0.26 0.26 0.10 3.98 2.39 0.29 0.19 1.56 0.39 0.10 3.41 0.10 0.10 0.10 0.00 0.10 0.35 0.10 0.10 0.29 0.35 0.26 0.10 0.10 0.10 0.45 0.35 0.45

TPC: Total phenolic content. TFC: Total flavonoid content. DPPH: 2, 2-diphenyl-1-picrylhydrazyl. ABTS: 2, 2’-azinobis (3-ethylbenzothiazoline-6-sulphonic acid) radical scavenging activity.

Besides, it is among the least toxic alcohols that are very applicable for industrial uses such as food colourings and flavourings. Thus, to reduce the length of the labour-intensive process, response surface methodology has been extensively used to optimise the experimental conditions. It is a useful mathematical tool used to calculate the region of interest. This tool enables users to maximise or minimise the process variables as it evaluates multiple responses simultaneously (Azahar et al., 2017). Apart from that, RSM can also reduce time consumption as it evaluates multiple responses without avoiding the effects of interaction between variables. Conventional optimisation, such as one-variable-at-a-time approach is ineffective to determine the optimum conditions when there are interaction effects in the models (Ibrahim and Elkhidir, 2011). Thus far, it could be confirmed that there is no data available regarding the cumulative effects of temperature, extraction time, solidliquid ratio, and solvent concentration on the extraction of phenolic compounds from E. bulbosa bulbs. Hence, this is the first study that emphasises the utilisation of RSM, particularly Central Composite Design (CCD) for the extraction of phenolic compounds from E. bulbosa bulb. RSM was employed to investigate the effects of temperature (XA ), extraction time (XB ), solid-liquid ratio (XC ), and ethanol concentration (XD ), as well as their interactions on the model responses, which were phenolic, flavonoid, and antioxidant activities. The bioactive constituents in the bulb extracted under the optimal extraction condition were further quantified through HPLC analysis. Besides, it could also improve the understanding of phenolic compounds presence in E. bulbosa bulb for future application in food and pharmaceutical industries, as it can be used as phytogenic feed additives and provides a good

source of antioxidant respectively (Ooi et al., 2018; Maftuch et al., 2018). 2. Materials and method 2.1. Chemicals and reagents Gallic acid, sodium carbonate, Folin Ciocalteau reagent, rutin, 2,2diphenyl-1-picrylhydrazyl (DPPH), and potassium persulfate were purchased from Sigma-Aldrich, (Missouri, United States). Aluminium chloride was procured from R&M Marketing (Essex, United Kingdom), while 6-hydroxy-2, 5, 7, 8-tetra-methylchroman 2- carboxylic acid (Trolox) was purchased from Calbiochem (San Diego, United States). Reagents like 2,2′-azinobis (3-ethylbenzo-thiazoline-6-sulphonic acid) disodium salt (ABTS), methanol, formic acid, and acetonitrile were obtained from Merck KGaA (Germany). Phenolic standards (chlorogenic acid, epicatechin gallate, rutin, quercetin, kaempferol, and myricetin) were purchased from Sigma (St. Louis MO, USA) while eleutherine was obtained from BioCrick (Chengdu). All chemicals were of analytical and HPLC grade. 2.2. Raw material and sample preparation The bulbs of E. bulbosa were purchased from Probolinggo, East Java, Indonesia. The bulbs were washed and dried in a warm air oven at 40°C overnight. Then, the dried bulbs were grounded to fine powder, sieved using 400 μm sieve, and stored at 4°C for further analysis. Identification of the plant sample was conducted by the Biodiversity Unit, Institute of 2

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2.4. Phytochemical analysis

Table 2 The regression coefficient, coefficient of determination, and the probability value to fit the second order polynomial models for antioxidant study. Factor Intercept Linear

XA XB XC XD

Quadratic

X2A X2B

X 2C X2D XAB XAC XAD XBC XBD X CD

Cross product

Reduced cubic

X3A X3B

X 3C R2 Adjusted R2 F value (model) F value (lack of fit)

X3D

TPCa

TFCb

DPPHc

ABTSd

90.75 −1.76 0.23 −0.81 10.75*** −2.12*

43.80 −0.12 1.60 1.68 1.26 −3.58***

73.05 −1.13 0.049 0.086 8.18*** −2.60***

71.66 −0.58 −0.15 0.52 9.10*** −2.19***

−2.62*

−4.91***

−3.20***

−1.92**

−3.83**

−5.63***

−3.27***

−2.93***

−0.64

−4.15***

−2.84***

−0.82

2.39 −2.89* −4.63** −0.54 1.41 −0.59 0.56

1.75* −0.66 −0.63 −0.16 −0.77 −0.040 0.80

0.44 −1.42* −1.10 −0.65 0.021 −0.64 0.71*

0.71 −1.80* −0.69 −0.91 0.53 −0.90 0.15

−0.27

−0.76

−0.085

−0.088

0.20

−0.18

−0.11

0.090

−1.08

0.27

−1.02**

−1.12*

0.8863 0.7802 8.35*** 3.10

0.9364 0.8582 11.97*** 0.54

0.9655 0.9230 22.74*** 4.36

0.9435 0.8831 15.60*** 4.71

2.4.1. Total phenolic content Total phenolic content (TPC) was determined according to the Folin Ciocalteau method described by Yusri et al. (2012) with slight modifications. For this assay, an aliquot of the extract (100 μL) was mixed with 500 μL of 10 % Folin Ciocalteau reagent and vortexed for 10 s. Then, 400 μL of 7.5 % sodium carbonate was added, and the mixture was vortexed for 10 s to produce a homogenous solution. The reaction mixture was incubated for 1 h in the dark at 40°C. The reaction mixture formed two layers, and the supernatant (200 μL) layer was loaded into the 96-well microplate. Gallic acid served as a standard solution for this study, with concentrations ranging from 3.125–200 μg/mL. The TPC of the extract was determined at 765 nm with deionised water as the blank. The results of the analysis were expressed in mg gallic acid equivalent per mg sample (mg GAE/g sample). 2.4.2. Total flavonoid content Total flavonoid content (TFC) was determined according to the aluminium chloride colourimetric assay described by Yusri et al. (2012) with slight modifications. In this study, 150 μL of ethanol extract was mixed with 150 μL aluminium chloride (20 mg/mL in methanol). Subsequently, the reaction mixture was incubated for 10 min at room temperature and later centrifuged at 7500 rpm for 10 min at 25°C. The level of TFC was determined from the absorbance reading of the aliquot (200 μL) at 435 nm. Rutin acted as a standard solution with the series of concentrations similar to gallic acid in the TPC assay. The results were expressed as mg rutin equivalent per g sample (mg RE/g sample).

XA: Temperature (°C); XB: Extraction time (min); XC: Solid-liquid ratio (w/v); XD: Ethanol concentration (%); R2: Coefficient of determination. Level of significance: *p < 0.05, **p < 0.01, ***p < 0.001. a TPC: Total phenolic content. b TFC: Total flavonoid content. c DPPH: 2, 2-diphenyl-1-picrylhydrazyl. d ABTS: 2, 2’-azinobis (3-ethylbenzothiazoline-6-sulphonic acid) radical scavenging activity.

2.5. Antioxidant activity 2.5.1. DPPH free radical scavenging activity assay The procedure was conducted as performed by Pandey et al. (2018) with several adjustments. The ethanol extract (50 μL) was pipetted into the 96-well plate, and 195 μL of DPPH solution (0.2 mM) was added. The mixture was then incubated for 1 h in the dark, and the absorbance was recorded at 540 nm. Trolox (1 mg/mL) served as the standard, and the radical scavenging activity was determined through the percentage of inhibition using the following equation:

Bioscience, UPM Serdang, Selangor, Malaysia (Voucher specimen: MFI 0055/19). 2.3. Extraction procedure

Radical scavenging activity (%) =

The powdered sample of E. bulbosa (10.0 g) was mixed with different solid-liquid ratios (75–175 mL) using ethanol as the solvent (60 %–100 %). The mixtures were exposed to various temperatures ranging from 30°C to 70°C, while the extraction time was set between 30 min–110 min. All parameters in the experimental design were generated by Design Expert version 6.0 (State Ease, Inc.). The ethanol extracts were filtered with Whatman No.1 filter paper and evaporated using the rotary evaporator.

2.5.2. ABTS scavenging activity assay ABTS scavenging assay was conducted according to the procedures described by Re et al. (1999) with slight modifications. Approximately 13.0 mg of potassium persulfate was mixed with 2 mL of deionised water and agitated until it was completely dissolved. The final volume of the potassium persulfate solution was brought to 20 mL with deionised water. Meanwhile, 76.8 mg of ABTS was weighed and mixed with 2 mL of deionised water and agitated until dissolved. Then, 18 mL of deionised water was added to make the final volume of 20 mL. The ABTS solution was then mixed with the prepared potassium persulfate solution and incubated for 16 h at room temperature in the dark. The absorbance of the mixture reagent was adjusted to 0.7 ± 0.2 at 735 nm with deionised water. The aliquot (24 μL) of ethanol extract and Trolox (1 mg/mL) as standard were mixed with 216 μL of ABTS solution and vortexed for 2 min. Next, the mixture was incubated for 1 h, and the absorbance was recorded at 735 nm. Trolox served as the standard (1 mg/mL), and the radical scavenging activity was determined using the same formula as DPPH scavenging assay.

2.3.1. Experimental design In Design Expert, RSM has been selected to identify the effects of process parameters on the responses. Precisely, central composite rotatable design has been chosen to optimise four independent variables (XA = temperature, XB = extraction time, XC = solid-liquid ratio, and XD = concentration of ethanol) at five coded levels. The process parameters are coded at -2, -1, 0, 1, and 2 with 30 experimental runs generated, as shown in Table 1. The observed values are then fitted into a second-order polynomial, and the regression coefficient (β) is generated, as shown in Table 2. Hence, the predicted optimum condition in the quadratic model was displayed as:

Yk = bk 0

3 i=1

bki xi +

3 i=1

bkii x i2 +

3 j=1

Control OD - Sample OD × 100 Control OD

bkij xi x j

2.6. Validation of the model

where bk0, bki, bkii and bkij were the constant regression estimate (β) whereas xi and xj were the process variables.

The extraction condition was optimised to obtain maximum 3

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polyphenolic compounds (phenolic and flavonoid) and antioxidant activities (DPPH and ABTS) by employing RSM. The responses were determined under generated optimum extraction conditions. The experimental data were compared with the predicted values to observe the variation within them based on student’s t-test.

The CCD comprised of four process parameters, five coded levels, and six centre points. The observed values of 30 runs were presented in Table 1. In the meantime, Meanwhile, the results of ANOVA were tabulated in Table 2. The level of significance where p < 0.05, 0.01, and 0.001 indicating that the model terms were significant, highly significant, and remarkably significant respectively. The values that were greater than 0.05 indicated that the model was insignificant. Overall, the ANOVA table revealed that all model responses (TPC, TFC, DPPH, and ABTS) were remarkably significant (p < 0.001) while the lack of fit was insignificant for all model responses (p > 0.05). The non-significant lack of fit indicated that the model term adequately explained the relationship between the process parameters and model responses. The coefficient of determination (R2) and the adjusted coefficient of determination (Adj. R2) were nearly fitted to 1 for all model responses, which displayed a strong correlation between observed and predicted values. Meanwhile, three-dimensional (3D) response surface graphs displayed interaction effects between process parameters towards the model responses, if any (Fig. 1a-e).

displayed non-significant F-value (F = 3.10), which indicated that the proposed model is well-fitted. Besides that, the proposed model displayed a good model prediction (R2 = 0.8863; Adj. R2 = 0.7802). The linear effect of ethanol concentration (XD ) showed a remarkably significant positive effect (p < 0.001) towards the yield of TPC. In the quadratic model, it could be seen that temperature (X2A ), extraction time (X2B ), and solid-liquid ratio (XC2 ) all yielded negative effects on TPC (p < 0.05 for X2A and X2B respectively; p < 0.01 for XC2 ; Table 2). In terms of interaction effect, temperature and solid-liquid ratio (XAC ) illustrated a significant negative outcome (p < 0.05; Table 2). Fig. 1a illustrated that the amount of phenolic decreases with increasing extraction temperature and solid-liquid ratio. The temperature is a crucial parameter for the production of TPC, as heat activation initiates the diffusion of the phenolic compound from the plant matrices, with the aid of solvent extraction. However, at a certain threshold of temperature, the yield of TPC may be effected solely due to thermal lability (Roselló-Soto et al., 2019). The interactive effect between temperature and ethanol concentration (XAD) displayed a highly significant adverse effect on the amount of TPC (p < 0.01) in Table 2. Increasing ethanol concentration enhances the production of TPC because organic solvent like ethanol can extract more phenol groups compared to non-phenol compounds such as carbohydrate and terpene (Do et al., 2014). Thus, reducing the aqueous mixture of ethanol may increase the yield of TPC obtained, as shown in Fig. 1b. In terms of structure, some phenolics have complex formations which are only soluble in organic solvents, for instance, ethanol and methanol as described by Do et al. (2014). Thus, increasing ethanol concentration may enhance soluble phenolic compounds extracted from plant matrices. Besides that, the polar properties in ethanol as the solvent of choice enhances the bioactive compounds extracted, such as eleutherinol while serving as a green solvent for human and animal (Bahtiar and Annisa, 2018). In the meantime, increasing extraction temperature enhances more diffusion rate of soluble phenolic compounds due to heat activation. Our current study utilised ethanol as the solvent of choice because it is permitted in food additives (FDA, 2019). A previous study by Shi et al. (2019) also determined TPC in various parts of E. bulbosa (leaves, flower, and bulb). However, they utilised various type of solvents, such as acetone, hexane, petroleum ether, ethyl acetate, and hydrochloric acid. The amount of TPC extracted from E. bulbosa bulb in our study (Table 3) is higher (161.04 mg GAE/g DW) as compared to conventional extraction conducted by Shi et al. (3.29 mg GAE/g DW; 2019). Thus, it indicates that ethanol is suitable to extract bioactive compounds from E. bulbosa bulb and this bioactive compounds could be applied in the industry, especially as food additives (Ooi et al., 2018; Maftuch et al., 2018). Additionally, it also showed that the optimisation through RSM was a reliable technique, as the amount of TPC obtained was much improved. The optimisation of extraction parameters are very crucial to ensure the maximum amount of phenolic compounds obtained. The extraction conditions were optimised collectively on response variables without overlooking the interaction effects within independent variables. Thus, this study provides a comprehensive antioxidant study on E. bulbosa bulb that focuses on the optimisation of extraction condition instead of conventional extraction method.

3.2. The effect of process parameters on total phenolic content (TPC)

3.3. The effect of process parameters on total flavonoid content (TFC)

Based on Table 2, ANOVA results showed that ethanol concentration (XD ) exhibited a remarkably significant linear effect on TPC. Similarly, there were also significant quadratic (X2A , X2B , XC2 ) and interaction (XAC , XAD) effects observed in the response. By fitting the secondorder polynomial, the equation for TPC could be expressed as follows:

The temperature (X2A ), extraction time (X2B ), solid-liquid ratio (XC2 ), and ethanol concentration (X2D ) displayed a remarkably significant negative quadratic effects on TFC (p < 0.001; Table 2). However, there was no significant effect detected in linear and reduced cubic models. Thus, the fitted second-order polynomial equation for the production of TFC was generated as follows:

2.7. High performance liquid chromatography analysis (HPLC) The optimum condition for the extraction of polyphenolic compounds was utilised in HPLC analysis using the Shimadzu model (Shimadzu, Japan) supplemented with reverse-phase Zorbax Eclipse Plus C18 column (4.6 × 150 mm) according to the method described by Rodríguez-Pérez et al. (2015) with slight modifications. The dried extract was dissolved with DMSO and passed through a 0.45 μm nylon syringe filter. Two types of mobile phases were used, i.e., Solvent A: 0.5 % formic acid in water and Solvent B: acetonitrile. The elution program was generated as follows: 0–9 min (5 % B); 10–14 min (35 % B); 15–17 min (95 % B), and 18–22 min (5 % B). The flow rate was operated at 0.5 mL/min, and the injection volume was 10 μL. The separation was detected by the UV detector at 280 nm. The chemical composition of E. bulbosa bulb was determined by comparing the retention times with the corresponding standards. 2.8. Statistical analysis All data generated through RSM were analysed statistically to determine the significant parameters and the interaction effects between each variable. Specifically, analysis of variance (ANOVA) was conducted to identify which models were significant and fitted the secondorder polynomial. Besides, student’s t-test was also carried out to observe the variation between experimental values obtained and predicted values generated. 3. Results and discussion 3.1. Model fitting

YTPC = 90.75 + 10.75XD

2.12X2A

2.62X2B

3.83XC2

4.63XAD

YTFC = 43.80 - 3.58X2A - 4.91X2B - 5.63X 2C - 4.15X2D + 1.75XAB

From the analysis, it was observed that the lack of fit in Table 2 4

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Fig. 1. The interaction effects between process parameters on (a–b) total phenolic content (TPC), (c) total flavonoid content (TFC), (d) 2, 2-diphenyl-1-picrylhydrazyl (DPPH) and (e) 2, 2′-azino-bis (3-ethylbenzothiazoline-6-sulphonic acid) (ABTS) scavenging activity.

5

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3.4. The effect of process parameters on antioxidant activity (AA)

Table 3 Predicted vs. experimental values under optimal extraction conditions. Model responses

Predicted values

Experimental values

TPCa (mg GAE/g sample) TFCb (mg RE/g sample) DPPHc (%) ABTSd (%)

99.97 37.91 75.52 77.20

80.52 32.01 75.23 74.86

± ± ± ±

As presented in Table 2, ANOVA revealed that the antioxidant models (DPPH and ABTS) were remarkably significant (p < 0.001) respectively. DPPH was mainly affected by ethanol concentration (XD) in the linear model, while X2A , X2B , XC2 , and X2D in the quadratic model, and X3A and X3D in the reduced cubic model. For interactive effect, only temperature and solid-liquid ratio (XAC ) showed a significant adverse effect on DPPH (p < 0.05). At low extraction temperature, DPPH increased with increasing solid-liquid ratio (Fig. 1d). The increment of the solidliquid phase promotes the penetration of the solvent into plant matrices; thus, increasing the amount of antioxidant produced (Al-Farsi and Lee, 2008; Cacace and Mazza, 2003; Wang et al., 2008). On top of that, heat also plays an essential role in degrading plant cell wall, which enhances soluble phenolic compounds and contributes to the yield of antioxidant. ABTS was primarily influenced by XD, followed by X2A , X2B , XC2 and X3D in the linear, quadratic, and reduced cubic models, respectively. Similar to DPPH, only temperature and solid-liquid ratio (XAC ) recorded a significant negative effect on ABTS assay (p < 0.05). Hence, it could be stated that the antioxidant activities, particularly DPPH and ABTS, were mainly affected by temperature and solid-liquid ratio. The models of antioxidant activities (DPPH and ABTS) were represented as follows:

1.30 0.49 5.36 1.32

Experimental values were expressed as mean ± standard deviation. a TPC: Total phenolic content. b TFC: Total flavonoid content. c DPPH: 2, 2-diphenyl-1-picrylhydrazyl. d ABTS: 2, 2’-azinobis (3-ethylbenzothiazoline-6-sulphonic acid) radical scavenging activity.

In addition, the lack of fit shown in Table 2 indicated that the model was fitted with the proposed model as the F-value recorded was not significant (F = 0.54) with the good prediction of terms (R2 = 0.9364; Adj. R2 = 0.8582). Besides that, adequate precision recorded was greater than 4 (AP = 10.078), indicating that the model was reliable to be explored throughout the design space (Elsen and Ramesh, 2015). The interactive effect between temperature and extraction time (XAB) showed a significant positive effect on flavonoid content (p < 0.05; Table 2). Fig. 1c demonstrated that the amount of flavonoid increases as temperature and extraction time increases. However, the prolonged extraction time with increasing temperature reduces the yield of flavonoid produced. According to Chen et al. (2007), increasing extraction temperature promotes the total solubility of flavonoid content, thereby, enhances the yield of flavonoid content. Nonetheless, prolonged extraction time exposes bioactive compound particularly flavonoid to thermal degradation. The amount of flavonoid extracted from E. bulbosa bulb also showed improvement through optimisation using RSM. The optimised extraction of TFC obtained was 64.02 mg GAE/g DW (Table 3), which was higher compared to the conventional extraction conducted by Shi et al. (2019). The findings confirmed that the amount of TFC extracted and optimised through RSM were reliable and could be used in large scale industrial application.

YDPPH = 73.05 + 8.18XD - 2.60X2A - 3.20X2B - 3.27X C2 - 2.84X2D - 1.42XAC + 0.71X3A

1.02X3D

YABTS = 71.66 + 9.10XD - 2.19X2A - 1.92X2B - 2.93XC2 - 1.80XAC

1.12X3D

The lack of fit from ANOVA (Table 2) for DPPH and ABTS illustrated that the F-values were acceptable (F = 4.36 and F = 4.71, respectively) to be fitted into the second-order polynomial as models were non-significant to the data points. Table 2 also displayed that the models were in good prediction (R2 = 0.9655 and R2 = 0.9435, respectively; Adj. R2 = 0.9230 and 0.8831, respectively). Apart from that, it could also be seen that the interaction effect between temperature and solid-liquid ratio (XAC) affected both

Fig. 2. HPLC profiles of phenolic compounds detected at 280 nm. Chromatograms: Gallic acid (1); Epicatechin gallate (2); Chlorogenic acid (3); Myricetin (4); Quercetin (5); Rutin (6); Kaempferol (7) and Eleutherine (8). 6

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A.A. Kamarudin, et al.

Table 4 Bioactive compounds detected under optimized extraction conditions. Compounds

Retention time (min)

Content (mg/g sample)

Regression equation

Gallic acid Epicatechin gallate Chlorogenic acid Myricetin Quercetin Rutin Kaempferol Eleutherine

2.787 3.421 3.713 4.390 5.460 6.046 6.853 20.189

97.37 80.17 3.79 1.34 64.80 29.94 1.51 33.42

Y = 466.35 + 4956.8x, r2 = 0.9986 Y = 525851 – 25659x, r2 = 0.9947 Y = 6175.3 – 657.88x, r2 = 0.9941 Y = 1987 + 494.37x, r2 = 0.9947 Y = 9393.1 – 3815.3x, r2 = 0.9923 Y = 23394 + 1082.1x, r2 = 0.9951 Y = 2811.4 + 5658.2x, r2 = 0.9976 Y = 56158 – 5524.3x, r2 = 0.9935

antioxidant activities (DPPH and ABTS) and phenolic compounds (TPC) (Fig. 1). Hence, due to these effects, the amount of various phenolic compounds present may contribute to the high antioxidant activity (Benmeddour et al., 2013; Boubekri et al., 2015; Santos et al., 2016).

i.e. chlorogenic acid, gallic acid, epicatechin gallate, eleutherine, rutin, quercetin, myricetin, and kaempferol. The optimised extraction conditions may be useful in the food industry and pharmaceutical analysis as it provides a convenient method of extraction, separation and safe solvent for the production of phenolic compounds. The findings could be useful for future application in food science and pharmacological research such as food colourings, flavourings and cancer research respectively.

3.5. Optimisation of design parameters and model validation The determination of optimum condition for polyphenol extraction was carried out using Design Expert Version 6.0 (Stat-Ease, Inc.). Hence, the optimum extraction conditions generated for maximum phenolic contents (TPC and TFC) and antioxidant activities (DPPH and ABTS) were obtained with temperature (XA ) of 45°C, extraction time (XB ) 70 min, solid-liquid ratio (XC ) 10:146 (w/v), and ethanol concentration (XD) of 90 % (v/v). All measurements under the optimised conditions are conducted in triplicate as tabulated in Table 3. There was no statistically significant difference between predicted and experimental values at 1 % confidence interval. The results indicated that both experimental and predicted values were in agreement and reliable for the extraction process.

Funding This research is supported by Research Management Centre (RMC), Universiti Putra Malaysia, Serdang, Selangor, MalaysiaUPM/700-2/1/ GPB/2017/9549900. CRediT authorship contribution statement Ammar Akram Kamarudin: Methodology, Formal analysis, Investigation, Writing - original draft. Norhaizan Mohd. Esa: Conceptualization, Writing - review & editing, Supervision, Project administration, Funding acquisition. Norazalina Saad: Conceptualization, Writing - review & editing, Visualization, Supervision. Nor Hafiza Sayuti: Methodology, Validation, Writing review & editing. Nor Asma Ab. Razak: Software, Resources, Writing review & editing, Supervision.

3.6. HPLC analysis Bioactive compounds extracted from E. bulbosa bulb under optimised conditions were determined through HPLC. Overall, there were eight bioactive compounds successfully detected by UV–vis detector at 280 nm (Fig. 2). The peak area was calculated for each compound, and the amount obtained was tabulated in Table 4. Overall, the amount of each phenolic compounds could be arranged as follows: gallic acid > epicatechin gallate > quercetin > eleutherine > rutin > chlorogenic acid > kaempferol > myricetin. These compounds may have a synergistic effect on antioxidant activity of E. bulbosa by free radicals scavenging, suppressing lipid peroxidation, and metal ions chelating (Baeza et al., 2016; Wang et al., 2017). Eleutherine is one of the lead compounds in this extract. It could be seen that the amount of this compound was quite remarkable in the HPLC profile. Studies showed that eleutherine is effective in inhibiting the proliferation of K562 cells, human topoisomerase II, and lipopolysaccharide-activated mouse macrophage cells (Hara et al., 1997; Komura et al., 1983; Xu et al., 2006).

Declaration of Competing Interest The authors declared no conflict of interests with respect to authorship and/or publication of this article. Acknowledgement Special thanks to Laboratory of Molecular Biomedicine, Institute of Bioscience for providing us the facilities during the work. References Al-Farsi, M.A., Lee, C.Y., 2008. Optimization of phenolics and dietary fibre extraction from date seeds. Food Chem. 108 (3), 977–985. Aybastıer, Ö., Işık, E., Şahin, S., Demir, C., 2013. Optimization of ultrasonic-assisted extraction of antioxidant compounds from blackberry leaves using response surface methodology. Ind. Crops Prod. 44, 558–565. Azahar, N.F., Gani, S.S.A., Mokhtar, N.F.M., 2017. Optimization of phenolics and flavonoids extraction conditions of Curcuma Zedoaria leaves using response surface methodology. Chem. Central J. 11 (1), 96. Baeza, G., Sarriá, B., Mateos, R., Bravo, L., 2016. Dihydrocaffeic acid, a major microbial metabolite of chlorogenic acids, shows similar protective effect than a yerba mate phenolic extract against oxidative stress in HepG2 cells. Food Res. Int. 87, 25–33. Bahtiar, A., Annisa, R., 2018. Effects of dayak onion bulbs (Eleutherine bulbosa (Mill.) Urb) on bone development of the hipoestrogen model rat. Pharm. J. 10 (2), 299–303. Benmeddour, Z., Mehinagic, E., Le Meurlay, D., Louaileche, H., 2013. Phenolic composition and antioxidant capacities of ten Algerian date (Phoenix dactylifera L.) cultivars: a comparative study. J. Funct. Foods 5 (1), 346–354. Betteridge, D.J., 2000. What is oxidative stress? Metabolism 49 (2), 3–8. Boubekri, C., Lanez, T., Djouadi, A., 2015. A comparative study on antioxidant activities and phenolic contents of five Algerian eggplant cultivars. Sci. Study Res. Chem.

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