Food Anal. Methods DOI 10.1007/s12161-014-9822-x
Extraction of Antioxidants from Aloe vera Leaf Gel: a Response Surface Methodology Study Seol Kim & Leonid Asnin & Awraris D. Assefa & Eun Young Ko & Kavita Sharma & Se Won Park
Received: 19 November 2013 / Accepted: 3 February 2014 # Springer Science+Business Media New York 2014
Abstract Extraction of antioxidants from aloe gel powder with water–ethanol solvents was studied using response surface methodology. The independent variables were solvent composition, temperature, extraction time, and the liquid-tosolid (L/S) ratio. The concentrations of potentially antioxidant compounds (aloin A and B, aloesin, total phenolics, and total carbohydrates) and a few indicators of antioxidant capacity (DPPH, FRAP, CUPRAC) served as the response functions. It was found that aloe gel contains both phenolic and nonphenolic antioxidants, and it was supposed that the phenolic fraction consists almost exclusively of chromones and anthrones. Different approaches to the optimization of extraction procedures are discussed, and here, the maximum recovery yield of antioxidants is achieved with 34 % ethanol at 60 °С and a L/S ratio of 46 in 1 h. The use of 90 % ethanol results in a higher antioxidant capacity of the product, but also results in a much lower extraction yield, decreasing the overall productivity of the process.
Keywords Response surface methodology (RSM) . Antioxidants . Extraction . Aloe vera
Electronic supplementary material The online version of this article (doi:10.1007/s12161-014-9822-x) contains supplementary material, which is available to authorized users. S. Kim : A. D. Assefa : E. Y. Ko : K. Sharma : S. W. Park (*) Department of Molecular Biotechnology, College of Life and Environmental Sciences, Konkuk University, 1 Hwayang-dong, Gwangjin-Gu, Seoul 143-701, Republic of Korea e-mail:
[email protected] L. Asnin Department of Chemistry and Biotechnology, Perm National Research Polytechnic University, Perm 614990, Russian Federation, Russia
Introduction Aloe vera (L.) Burm. f., also known as Aloe barbadensis Mill, is the most famous species of the genus Aloe and probably one of the most commercially important, being cultivated globally (International Aloe Science Council 2004) on an area of 23,600 to satisfy the great demand of the pharmaceutical, cosmetic, and food industries (Eshun and He 2004; Waller et al. 2004). Functional foods, including health and soft drinks, are other fields of utilization of A. vera gel, grown in an important segment of the aloe industry (Eshun and He 2004; Park and Hyung 2006; Ahlawat and Khatkar 2011). During the last decade, there has been developing interest in antioxidant properties of A. vera gel extracts (Rodríguez et al. 2010). In part, this interest may be explained by a quest for new areas of application of A. vera products. The substitution of synthetic food additives in order to prevent oxidative processes in foodstuff may be one such application. In the experiments by Hu et al. (2003), an ethanol A. vera extract demonstrated radical scavenging potential comparable to that of the synthetic antioxidant butylated hydroxytoluene. The authors, however, obtained the samples from the whole leaves rather than from the leaf gel. According to Rajasekaran et al. (2005), an ethanolic extract of the A. vera leaf gel reduced the oxidative stress in diabetic rats. Lee et al. (2000) suggested the use of aloe gel in anti-aging agents, since it contains phenolic compounds which are known to function as free radical terminators (Shahidi et al. 1992). A few phenolic-type substances, derivatives of aloesin, with antioxidant activity were isolated from aloe gel (Lee et al. 2000; Yagi et al. 2002). A chromon from A. vera with unspecified structure was found to be useful in protection against kidney damage induced by the chemotherapeutic agent cisplatin and associated with the generation of reactive oxygen species (Choung 2006). In addition to low molecular weight compounds, glycoproteins (Yagi et al. 2003) and polysaccharides (Liu et al. 2007) of A. vera may possess the activity in question.
Food Anal. Methods
While it is of practical interest to obtain an extract with the highest antioxidant capacity, this is not a trivial task because many compounds of different nature, both hydrophilic and lipophilic, contribute to the antioxidant potency of the leaf gel, and because many experimental parameters influence the efficacy of extraction, solvent composition, extraction time, temperature, and solid-to-liquid ratio being the most important. There have been few reports in literature relating to the topic (Tang et al. 2011; Wang et al. 2011, He et al. 2012). None of them considered a liquid–solid extraction of antioxidants thoroughly, except the work by Hu et al. (2005), which focused on the optimization of extraction with supercritical fluid rather than with a range of solvents. A few studies were devoted to the effect of the solvent on the yield and biological activities of the extracts, but without attempting to optimize the process (Habeeb et al. 2007; Loots et al. 2007). Thus, the problem of the isolation of the antioxidant fraction from the aloe gel still requires a focused and systematic investigation, which is the purpose of the present work. A water–ethanol system was selected as the extractant in this study, based on previous reports (Hu et al. 2005; Wang et al. 2011) and because of low cost and low toxicity of the solvents. The effect of four process parameters enumerated above on the yield and chemical composition of the product was examined using response surface methodology (Deming and Morgan 1993), a statistical technique proved to be useful in optimizing complex extraction procedures (Li et al. 2010). Several methods were applied to characterize different aspects of the antioxidant activity of the extracts: the 2,2-diphenyl-1picrylhydrazyl (DPPH) assay (Brand-Williams et al. 1995), Cu(II) reduction capacity (CUPRAC) assay (Apak et al. 2004), and ferric reducing antioxidant power (FRAP) assay (Benzie and Strain 1996). While the DPPH method evaluates the free radical scavenging capacity of a sample, the CUPRAC and FRAP methods evaluate the content of reducing species with a certain redox potential, to better understand the relationship between antioxidant power and chemical composition of extracts, total phenolic content, and the concentrations of typical aloe phenolic compounds, the anthroneC-glycosides aloin A and B, and the chromone aloesin. The amount of total polysaccharides extracted was also measured.
DAEJUNG. Ammonium acetate, ferric trichloride hexahydrate, and 2,4,6-tripyridyl-s-triazine (TPTZ) were from JUNSEI (Japan). Sodium acetate and DPPH were from Fluka (Switzerland). Acetic acid, the Folin–Ciocalteu reagent, and sodium carbonate were from Sigma-Aldrich (Switzerland). Standards of aloin A, D-mannose, and gallic acid were purchased from Sigma-Aldrich as well as Neocuproin. Aloin B, aloesin, and 6-hydroxy-2,5,7,8-tetramethylchromane-2carboxylic acid (Trolox) were obtained from the ChromaDex (USA), Santa Cruz Biotechnology, Inc. (USA), and MP Biomedical (USA), respectively. All reagents used for analysis were of analytical or higher purity grade. Plant Material Freeze-dried A. vera powder was a gift from Kim Jeong Moon Aloe Co., LTD (Seoul, Korea). This product was prepared from the inner gel of 3-year-old plants collected from a plantation on Jeju Island (Korea) in 2012. Extraction and Sample Preparation Each extraction experiment used 8 g of the Aloe powder and was performed in duplicate. The sample was mixed with 240– 480 ml of a water–ethanol mixture in a 500-ml Erlenmeyer flask. The extraction process was performed in a thermostated shaking water bath at agitation rate 180 rpm. Extraction conditions were set according to an experimental design plan explained below. Once extraction was completed, the supernatant was separated from the insoluble solid by centrifugation at 9,000 rpm for 10 min at 4 °С. The remaining solid phase was then washed with a small volume of the extraction solvent and was centrifuged again. The two supernatant phases were pooled together, followed by concentration under reduced pressure using a rotary evaporator. The semi-dried extract was then freeze-dried at −70 °С and homogenized using liquid nitrogen. The extract stock solution for analytical assays was prepared by dissolving 250 mg of the powder in the same solvent that was used for extraction in a 25-ml measuring flask. If not used immediately, the solution was stored in a freezer at −20 °С. Experimental Design
Materials and Methods Chemicals In this study, ethanol and water were used as extraction solvents. Ethanol (DAEJUNG Chemicals, Korea) was of 99 % purity. Water was purified using a Millipore Milli-Q Reference system. Solvents for chromatography, acetonitrile, and water were both of HPLC grade (DAEJUNG). Hydrochloric acid, phenol, and sulfuric acid were also supplied by
The response surface methodology was applied to investigate the effects of experimental conditions on the extraction yield and on the composition of extract. The independent variables were extraction time (x1) varying within a 1–4-h range, the ethanol percentage x2 of water–ethanol solvent (0–100 %, v/v), temperature x3 (25–60 °С), and the liquid-to-solid (L/S) ratio x4 (30–60 ml/g). The response variables were extraction yield, concentrations of aloins A and B, aloesin, total polysaccharides, and total phenolics, as well antioxidant activities,
Food Anal. Methods
which were evaluated according to different approaches. An inscribed central composite design was used in this study with 16 factorial points, 8 axial points, and 2 replicates at the center point, which gave 26 experiments in total. All the experimental runs were performed randomly to minimize the effect of unexpected variability in the observed response. The independent variables or factors were coded according to the following equation: Xi ¼
xi −x0 Δxi
ð1Þ
where Xi is the coded value of the factor, xi its actual value, x0 the actual value at the center point, and Δxi the step change in the variable xi. The levels of the experimental variables in the coded and uncoded coordinates are given in Table 1. Experimental data were fitted to the following second-order polynomial model: Y ¼ β0 þ
k X i¼1
βi X i þ
k X i¼1
βii X 2i þ
k k−1 X X
β ij X i X i
ð2Þ
i¼1 j>i
where Y is the predicted response, β0 is the interception coefficient, βi are the linear terms, βii are the quadratic terms, and βij are the interaction terms. Response surface regression followed by analysis of variance (ANOVA) to assess goodness of fit and significance of regression coefficients was performed using Minitab 16 (Minitab Inc., USA) software. Determination of Aloin A, Aloin B, Aloesin, and Total Chromones and Anthrones The aloe chromones and anthrones were determined by means of HPLC using an Agilent 1100 chromatograph (Agilent, USA) equipped with a solvent delivery system, an autosampler, a DAD detector, and a ChemStation data acquisition system. The chromatographic column was a Kromasil 100-5 C18 (250×4.6 mm) which was protected with a C18-type guard column from Phenomenex (USA). The column was thermostated at 25 °С. The separation was performed using a binary gradient consisting of A (70:30 (v/v) acetonitrile– water) and B (0.001 M CuSO4 in water acidified with 0.5 % (v/v) acetic acid). The elution program was as follows: 0–10 min, 20–25 % of solvent A; 10–20 min, an isocratic step at 25 % A; 20–30 min, 25–40 % A; 30–40 min, 40–50 % A. Each run was preceded by a 10-min re-equilibration step at 20 % of solvent A. The flow rate was set at 1 ml/min. The injection volume was 20 μl. Aloins were monitored at a wavelength of 360 nm, whereas chromones, including aloesin, were monitored at 298 nm. The detector responses were calibrated with respect to each analyte by means of the external standard
method. Aloesin was used as the calibration standard for all chromones in the chromatograms because of the lack of reference compounds. The sum of four major chromones and two major anthrones (aloin A and B) found in the chromatograms (Fig. 1) was used as an estimate of the total amount of chromones and anthrones in the extracts.
Total Phenolics The total phenolic (TP) content was determined by the Folin– Ciocalteu method according to the protocol of Loots et al. (2007) with slight modifications. Briefly, the stock extract solution was mixed with 200 μl of the Folin–Ciocalteu reagent and 1,150 μl of water. The mixture was kept at room temperature for 7 min, and then 600 μl of 20 % sodium carbonate was added. The reaction was allowed to continue for a further 60 min. Finally, the absorbance was measured at 765 nm using a Shimadzu UV-1700 spectrophotometer calibrated against gallic acid, and the results were reported in milligram of gallic acid equivalents (GAE) per gram of aloe extract.
Total Carbohydrates The carbohydrate content (TC) in the extracted solid matter was assessed using the phenol–sulfuric acid method (Hu et al. 2003). The stock extract solution was diluted 16 times with the same ethanol solvent that was used to obtain this particular sample. Fifty microliters of the diluted sample was mixed with 500 μl of 4 % phenol in a test tube, then 2,500 μl of sulfuric acid was added. The mixture was kept at room temperature for 10 min, followed by reading the absorption value at 490 nm. The calibration curve was measured with standard solutions of D-mannose (5–25 g/l). Results were expressed as milligram Dmannose per gram.
FRAP Assay The ferric reducing antioxidant potential of Aloe extracts was estimated by the method of Benzie and Strain (1996). The method requires the preparation of FRAP reagent from 25 ml of 300 mM acetate buffer (pH 3.6), 2.5 ml of 10 mM TPTZ solution in 40 mM HCl, and 2.5 ml of 20 mM FeCl3 ·6H2O solution. The reagent must be prepared immediately before measurements. The assay procedure consisted of mixing 3,000 μl of FRAP reagent, 300 μl of water, and 100 μl of test sample or standard Trolox solution. The reaction mixture was kept at 37 °C for 24 h. Readings were taken at 593 nm, converted into the FRAP values using the Trolox calibration curve, and reported as milligram of Trolox equivalent (TE) per gram.
Food Anal. Methods Table 1 Experimental design levels of independent variables in the actual and coded (in brackets) form
Design point
Time, h (X1)
EtOH, % (X1)
T, °С (X3)
L/S ratio, ml/g (X4)
1 2 3 4 5
1 (−1) 1 (−1) 1 (−1) 1 (−1) 1 (−1)
0 (−1) 0 (−1) 0 (−1) 100 (1) 100 (1)
25 (−1) 25 (−1) 60 (1) 60 (1) 60 (1)
30 (−1) 60 (1) 60 (1) 60 (1) 30 (−1)
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22
1 (−1) 1 (−1) 1 (−1) 4 (1) 4 (1) 4 (1) 4 (1) 4 (1) 4 (1) 4 (1) 1.44 (−0.707) 2.5 (0) 2.5 (0) 2.5 (0) 3.56 (−0.707) 2.5 (0) 2.5 (0)
0 (−1) 100 (1) 100 (1) 0 (−1) 100 (1) 100 (1) 0 (−1) 0 (−1) 100 (1) 0 (−1) 50 (0) 14.7 (−0.707) 50 (0) 50 (0) 50 (0) 85.4 (−0.707) 50 (0)
60 (1) 25 (−1) 25 (−1) 25 (−1) 25 (−1) 60 (1) 25 (−1) 60 (1) 25 (−1) 60 (1) 42.5 (0) 42.5 (0) 30.1 (−0.707) 42.5 (0) 42.5 (0) 42.5 (0) 54.9 (−0.707)
30 (−1) 60 (1) 30 (−1) 30 (−1) 30 (−1) 30 (−1) 60 (1) 60 (1) 60 (1) 30 (−1) 45 (0) 45 (0) 45 (0) 34.4 (−0.707) 45 (0) 45 (0) 45 (0)
23
2.5 (0)
50 (0)
42.5 (0)
55.6 (−0.707)
24 25 26
2.5 (0) 2.5 (0) 4 (1)
50 (0) 50 (0) 100 (1)
42.5 (0) 42.5 (0) 60 (1)
45 (0) 45 (0) 60 (1)
CUPRAC Assay The procedure of the CUPRAC assay was adopted from Apak et al. (2004). Briefly, 1 ml of 10 mM CuCl2 solution, 1 ml of ammonium acetate buffer (pH 7), and 1 ml of 7.5 mM neocuproine solution were mixed together in a test tube. To this mixture were added x milliliter of extract sample (or standard) solution and (1−x) milliliter of water. The tubes were then left in a dark place for 6 h and the absorbance was measured at 450 nm. The assay was calibrated with standard solutions of Trolox to express results in TE units. DPPH Assay
Fig. 1 A typical chromatogram of an ethanol extract of aloe leaf gel. The detector signal is shown at 298 nm (specific to chromones) and 360 nm (specific to anthrones). Peak assignment: 1, 2, 4 = unidentified chromones; 3=aloesin; 5=aloin B; 6=aloin A
The evaluation of the radical scavenging activity of the extracts with the DPPH free radical was carried out using the protocol described by Sharma and Bhat (2009) with some modifications. Two working solutions of DPPH with a concentration of 0.1 mM were prepared, one in pure ethanol and another in 60 % ethanol. The former solution was used to analyze aloe extracts obtained with pure ethanol. The water– ethanol DPPH solution was used for the evaluation of extracts
Food Anal. Methods
obtained with solvents containing 50 or less percents of ethanol. Dilution of the assay mixture with water in this case was necessary because a white precipitate was observed otherwise. The assay procedure was carried out as follows. Two hundred fifty microliters of the stock extract solution was mixed with 2.5 ml of a respective DPPH solution and was made up to 3 ml with ethanol or 60 % ethanol. The mixture was shaken vigorously and left in a dark place for 80 min. Preliminary experiments have shown that such a long interval is required to accomplish the reaction. The absorbance was measured at a wavelength of 517 nm. Pure ethanol or 60 % ethanol were used as references accordingly. The same measurements were carried out with standard Trolox solutions to determine a calibration curve. The antiradical activity was expressed in terms of TE.
Results and Discussion Raw experimental data are presented in Table 2. Their primary analysis was made using the correlation analysis techniques as described below. For a more detailed consideration, a multiple regression method in combination with ANOVA was employed, the results of which are given in Tables S1–S24 in supporting information. The response surface models thus obtained were used for the optimization of extraction conditions with respect to the recovery yield of antioxidants. Finally, the nature of aloe oxidants is discussed based on the present findings. Correlation Analysis The correlation coefficient for two random variables, x and y, which are supposed to be in a certain relation to each other, is qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi ffi equal to R ¼ 1− σΔy =σy 2 (Minkin 2011). The variance σ2Δy characterizes the scatter of data around the best fit straight line y(x) and σ2y is the variance of y. If σ2Δy accounts for a half of σ2y , R will be ca. 0.7. We shall consider this value as a voluntary border between unimportant and important correlation. The lack of any correlation may be suggested with a confidence probability of greater than 0.99 if |R|0.9) and well explainable correlations are found between aloin A and B, and between either aloin or the extraction yield. In this latter case, the correlation is negative as water-enriched solvents are necessary for a high extraction yield but ethanolenriched solvent facilitates the extraction of lipophilic aloins. These two anthrones also strongly correlated with total phenolic content, suggesting that the conditions favorable to the extraction of aloins are also so for the isolation of the whole
phenolic fraction. Its content negatively correlates with the extraction yield and with the values of the antioxidant assays FRAP and CUPRAC. The values of the DPPH test do not correlate with any of the measured parameters, not even with the other antioxidant assays. We explain this finding by a large scatter of data associated with this test. Response Surface Models Analysis of response surfaces gives the most complete information concerning relationships between influencing factors and dependent variables. The results of this analysis are presented in Tables S1–S24 in the supporting information, and a summary is given in Table 4. As can be seen from Table 4, the full second-order model (Eq. 2) perfectly approximates the response surface for the extraction yield (EY) and the concentrations of aloin A and B in the extract. Approximation is still satisfactory for TP and TC as well as for the FRAP assay and the concentration of aloesin, in which case the adjusted coefficient of determination R2adj > 0.78. The CUPRAC assay is characterized by a low determination coefficient and the DPPH assay, which demonstrates the lack of fitting, and is due to the above-mentioned large scatter of data, rather than due to imperfection within the model, as deduced from the analysis of variance (Table S6). Interestingly, when we consider the products of EY and a response function rather than the response functions themselves, the quality of fitting is improved for most responses (Table 5). It is dramatically improved for the DPPH and CUPRAC assays, with R2adj values increasing from 0.15 to 0.91, and from 0.63 to 0.94, respectively. The value EY⋅Y is the recovery yield of the characteristic Y or, in other words, the amount of Y in the extract expressed per gram of the sample (aloe powder). Effect of Experimental Conditions According to the data in Table 4, all responses depend on solvent composition as the correlation analysis predicted, constituting a non-linearly response in most cases. Moreover, the ethanol percentage is the most important of all the variables, which follows from the comparison of the model coefficients in Tables S1–S6 (see supporting information). In the cases of EY, aloins, antioxidant assays (except DPPH, which is not considered in this section because of poor statistical indicators), and TP, the factor of ethanol percentage interacts with other factors (temperature for EY, FRAP, CUPRAC, and TP; L/S for aloin A, aloin B, and TP). It interacts with the factor of time for aloin A, but not for aloin B. Extraction time affects the concentrations of both aloins in the extract. The influence is negative, that is, the concentration of the anthrons is lowered with a longer extraction period. Obviously, it is due to the reactivity of aloins that experience oxidation with a subsequent polyphenolic condensation (Waller et al. 2004) in
Food Anal. Methods Table 2 Experimental results for the response variables measured in the experimental design (Table 1) points Design point
EY (%)
Aloin A (mg/g)
Aloin B (mg/g)
Aloesin (mg/g)
Ch+Ana (mg/g)
DPPH (mg TE/g)
FRAP (mg TE/g)
CUPRAC (mg TE/g)
TP (mg GA/g)
TC (mg D-Man/g)
1 2 3 4 5 6 7 8 9 10 11
76.7 73.4 76.9 23.9 18.3 73.1 11.6 8.0 76.8 11.5 21.5
0.54 0.46 0.43 2.88 4.04 0.67 3.24 3.64 0.44 3.17 2.94
0.24 0.22 0.22 1.03 1.42 0.30 1.11 1.22 0.21 1.16 1.13
1.24 1.28 1.35 0.71 0.90 1.34 0.60 0.64 1.26 0.78 0.73
4.69 4.64 4.93 9.22 12.2 5.63 9.68 10.6 4.66 9.89 11.9
2.69 3.00 2.57 3.85 4.16 2.73 3.07 3.26 3.68 3.22 3.51
11.9 12.7 12.2 23.0 25.6 13.0 17.9 20.6 13.0 15.7 23.0
27.8 28.0 29.8 38.8 41.5 27.8 30.0 34.8 28.8 33.5 41.8
3.71 3.72 3.84 5.73 7.36 3.84 5.34 5.94 3.57 5.56 6.76
397 406 389 552 582 366 619 609 396 551 613
12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
78.4 74.8 17.0 73.4 75.2 77.0 71.6 69.4 72.6 34.7 71.9 74.0 75.1 76.6 24.1
0.50 0.39 2.63 0.27 1.25 0.74 1.11 1.18 0.96 2.46 1.03 0.94 1.02 1.05 3.14
0.23 0.20 0.95 0.15 0.48 0.32 0.45 0.47 0.42 0.88 0.42 0.39 0.40 0.42 1.13
1.23 1.32 0.58 1.18 1.04 1.08 1.07 1.18 1.12 1.19 1.25 1.16 1.13 1.19 0.77
5.15 4.80 9.27 5.00 5.82 5.50 5.92 5.96 5.41 8.37 6.13 5.49 5.56 5.51 8.79
2.97 2.85 3.88 2.78 4.45 3.24 3.95 3.65 3.15 4.35 3.43 3.56 3.27 3.26 3.79
12.3 13.9 18.9 12.1 17.9 15.3 16.5 16.1 15.5 22.5 18.9 14.3 14.2 15.3 24.5
29.0 24.5 33.3 30.0 31.8 29.5 32.0 32.0 30.0 44.3 33.0 30.5 29.5 26.5 36.3
3.82 4.04 4.93 3.84 4.67 4.07 4.14 4.47 4.40 6.22 4.54 4.32 4.21 4.21 6.99
351 417 586 356 448 397 421 386 447 574 454 393 414 448 647
Mean values of duplicate experiments a
Ch+An=the sum of chromones and anthrones
a course of extraction. Process duration also affects TC and the results of the FRAP test through interaction terms, although the effect is minor, accounting for not more than 3 % of either indicator’s value with any combination of variables. Temperature also influences the total concentration of phenolics as
Table 3 Coefficients of correlation between response functions EY Aloin A Aloin B Aloesin DPPH FRAP CUPRAC TP TC
well as the extraction yield of the antioxidant species, as measured by the FRAP and CUPRAC assays. This influence is positive, although nonlinear in the case of TP, and the FRAP-detected species. The situation is somewhat different with the CUPRAC-active antioxidants. The effect of
EY
Aloin A
Aloin B
Aloesin
DPPH
FRAP
CUPRAC
TP
TC
1.000 −0.958 −0.955 0.866 −0.279 −0.728 −0.652 −0.821 −0.894
1.000 0.997 −0.840 0.382 0.819 0.708 0.899 0.895
1.000 −0.834 0.393 0.822 0.718 0.910 0.892
1.000 −0.317 −0.647 −0.474 −0.652 −0.801
1.000 0.612 0.495 0.458 0.364
1.000 0.796 0.881 0.795
1.000 0.786 0.652
1.000 0.822
1.000
Food Anal. Methods Table 4 Summary of multiple regression analysis on experimental responses Response
Significant influencing factors (p=0.05)
EY Aloin A
EtOH; Temp; L/S; EtOH×EtOH; EtOH×Temp Time; EtOH; L/S; EtOH×EtOH; Time×EtOH; Time×L/S; EtOH×L/S Aloin B Time; EtOH; L/S; EtOH×EtOH; Time×L/S; EtOH×L/S Aloesin EtOH; Temp DPPH EtOH FRAP EtOH; Temp; EtOH×EtOH; L/S×L/S; Time×L/S; EtOH×Temp CUPRAC EtOH; Temp; EtOH×EtOH; EtOH×Temp TP EtOH; Temp; EtOH×EtOH; EtOH×Temp; EtOH×L/S TC EtOH; EtOH×EtOH; L/S×L/S; Time×Temp
a
R2adj a full model 0.9868 0.9741 0.9701 0.7847 0.1496 0.8104 0.6330 0.8685 0.8416
Full model=Eq. (2) including all 15 terms
temperature in this case is coupled with the effect of solvent composition through the interaction term X2X3 (EtOH × Temp). The L/S ratio affects most response functions considered, except CUPRAC and aloesin content. The importance of this variable ranges from minor for FRAP, EY, and TC to moderate for aloin A and B, and TP as follows from relative contributions of L/S-related terms to the total value of a response function. For example, the sum of the terms X1X4 and X42 does not exceed −1.5 % of the FRAP value for any combination of variables, while for aloin A, a respective contribution varies from −120 to +60 %. To avoid misunderstanding, it must be noted that partial contributions can exceed 100 % in the modulus because some of them are positive and some are negative, giving after summation the whole value of a response. As seen from the above instances, the L/S ratio
Table 5 Summary of multiple regression analysis on functions (EY× Response) Response
Significant influencing factors (p=0.05)
R2adj a full model
EY⋅Aloin A
EtOH; Temp; EtOH×EtOH; EtOH×Temp
0.7922
EY⋅Aloin B EY⋅Aloesin EY⋅DPPH EY⋅FRAP
EtOH; Temp; EtOH×EtOH; EtOH×Temp EtOH; Temp; EtOH×EtOH EtOH; EtOH×EtOH; EtOH×Temp EtOH; Temp; EtOH×EtOH; L/S×L/S; EtOH×Temp EtOH; Temp; EtOH×EtOH; EtOH×Temp EtOH; Temp; EtOH×EtOH; EtOH×Temp EtOH; Temp; L/S; Time×Time; EtOH×EtOH; L/S×L/S; EtOH×Temp
0.8027 0.9658 0.9066 0.9269
EY⋅CUPRAC EY⋅TP EY⋅TC a
Full model=Eq. (2) including all 15 terms
0.9423 0.9511 0.9440
effect may be negative, or may vary from negative to positive, depending on experimental conditions. It contradicts a common expectation that the amount of solute in the liquid phase increases with the volume of solvent. Consequently, other physicochemical phenomena besides solubility play a role. Optimization of Extraction Parameters and Validation of the Models Two approaches to optimization are considered in this study. The first one is targeted at achieving the maximum value of a selected response variable in the extract. The second approach consists of the optimization of the product EY⋅Y. This allows us to attain a high level of a target property along with the highest possible EY, which is of interest in the context of commercial production. The respective calculations were carried out using the response surface models described above by means of the Response Optimizer utility of the Minitab16 software. A summary of the results is given in Table 6. The best conditions for EY presuppose a relatively diluted ethanol (30 %) at high temperature and high L/S ratio, which suggests the main contribution to the extracted solids to come from water soluble carbohydrates, both of low and of high molecular weight. A closer look at the experimental data (Fig. 2) shows that a wide range of water–ethanol mixtures, from pure water to ca. 30 % EtOH, extract sample solutes with close to the maximum EY. Within this range, neither temperature nor L/S ratio affects EY importantly. Process time is not a significant variable, implying that 1 h is a sufficient time for complete isolation of the extractable matter. There is little information in the literature on the issue in question, and hence, little data which is comparable to ours. The only known report has been published by Sultana et al. (2009), who studied the whole Aloe leaves. They found that the dilution of methanol or ethanol with 20 % water leads to better EY compared with pure alcohol. As opposed to the total extracted amount, pure ethanol favors the extraction of particular fractions of aloe chemicals, except aloesin (Table 6). In this latter case, the consideration of the experimental data shows that 90–95 % ethanol at 40 °С has the extractive power with respect to aloesin comparable to that of pure water (Fig. 3). These findings are in a reasonable compliance with a tendency to use 75–100 % alcohol extracts in the determination of antioxidant activity of different Aloe varieties (Hu et al. 2003; Loots et al. 2007; Botes et al. 2008; Sultana et al. 2009) and with the results by He et al. (2006) establishing the optimal ethanol percentage for the extraction of total polysaccharides from Aloe arborescens Mill. to be 80 % at 85 °С. Alcohol-enriched mixtures were proven to be effective in the extraction of anthraquinones from Rheum palmatum L. (Zhao et al. 2011) and chromones from Radix saposhnikoviae (Li et al. 2010). In contradiction to our results, Xiao et al. (2012) reported that water at 35 °С is the optimal
Food Anal. Methods Table 6 Optimized extraction conditions Response function
Optimized conditions
EY Aloin A Aloin B
Time h ns 1 1
EtOH % 29.3 100 100
Temperature °С 60 ns ns
L/S ratio ml/g 60 30 30
Aloesin DPPH FRAP CUPRAC TP TC EY⋅Aloin A EY⋅Aloin B EY⋅Aloesin EY⋅DPPH EY⋅FRAP EY⋅CUPRAC EY⋅TP EY⋅TC
ns 1 1 ns 1 4 ns ns ns ns ns ns ns 4
0 100 100 100 100 100 64.4 58.6 14.2 30.3 35.4 32.8 36 34.3
60 60 60 60 54.3 60 60 60 60 25 60 60 60 60
ns 44.9 43.3 ns 33.6 44.8 ns ns ns ns 46.1 ns ns 47
ns not significant at p=0.05
solvent for the extraction of aloin A from A. vera. They, however, used a microwave-assisted extraction technique, which is different from the conventional batch extraction method considered here. Aqueous alcohol solutions with high content of water (up to 50 %) are commonly used for the extraction of phenolic compounds from many natural products including foods (Prasad et al. 2011). The necessity of the water component is
Fig. 3 Concentration of aloesin in the extracted solids as a function of ethanol percentage and temperature. Points represent experimental data. An interpolation surface is plotted for the sake of better visualization using the distant method of the Minitab software
explained by the presence in samples of a fraction of glycosylated compounds with a relatively high hydrophilicity (Escribano-Bailon and Santos-Buelga 2003). In aloe gel, the main constituents of the total phenolic fraction, anthraquinons, chromones, and anthrones are lipophilic compounds. Therefore, lipophilic solvents with no or low fraction of water give the best recovery of total phenolics. Unlike aloe gel, the whole leaves of A. vera contain a tangible part of flavonoids (Hu et al. 2003), probably, concentrated in the leaf skin. This might explain why Sultana et al. (2009) found that 80 % ethanol extracts phenolics from the whole leaves better than pure alcohol. For product functions EY⋅Y, the best extraction conditions are achieved with water-enriched solvents (Table 6). This is explained by the influence of the EY function increasing with decreasing ethanol percentage. The maximum yield of quantity, Y, per gram of sample, which is the physical meaning of the product EY⋅Y, requires high extraction temperature, except in the case of the DPPH indicator which is optimized at 25 °С. Extraction time is not a significant variable for all the indicators but TC in accordance with the regularity discussed in the above paragraph. The L/S ratio is mostly insignificant. Only for the FRAP and TC quantities the optimal conditions are located at x4 =46–47 %. Validation of Optimal Conditions
Fig. 2 Extraction yield as a function of ethanol percentage and temperature. Points represent experimental data. An interpolation surface is plotted for the sake of better visualization using the distant method of the Minitab software
Three validation experiments were carried out, the conditions of which are listed in Table 7. The first experiment (trial I) verified the conditions predicted to achieve the highest EY. The two other experiments were aimed at obtaining a product with high antioxidant activity. Instead of considering an individual indicator of antioxidant capacity, FRAP or CUPRAC
Food Anal. Methods Table 7 Conditions of validation experiments
Optimized function
Trial I Trial II Trial III
EY EY+FRAP+CUPRAC EY⋅FRAP+EY⋅CUPRAC
(DPPH was not used because of poor statistical characteristics), we performed optimization on both these functions simultaneously in order to extract a wider spectrum of antioxidant species. Two strategies were applied. First, the FRAP, CUPRAC, and EY response functions were optimized simultaneously (trial II). Second, the product functions EY FRAP and EY CUPRAC were optimized simultaneously (trial III). The first approach suggested extraction with an 88 % ethanol solvent during 2.3 h, whereas the second approach required 34 % ethanol and 1 h extraction time. As will be shown below, these approaches lead to different compositions and mass of the product. The results of the experiments summarized in Table 8 show that response surface models predict within 10 % the extraction yield and the concentrations in extracts of total phenolics and of the FRAP and CUPRAC assay sensitive antioxidants. The response model for TC demonstrates a reasonable predictive power, within 21 %. The worst accuracy was observed for the response variables estimated chromatographically, the extract concentrations of aloins and aloesin. In trial I, the difference between the experimental and predicted level of aloesin is a full order of magnitude. It is essentially better in trials II and III (within 15 %) though. As for the accuracy of the estimate of the functions EY Y, it is similar to that of the response functions themselves (Table 9). The experimental data, in general, agree with the theoretical predictions regarding the results of extraction. So, trial II
Time
EtOH
Temperature
L/S ratio
h
%
°С
ml/g
1 2.3 1
29.3 88.9 34.3
60 60 60
60 44.5 46.2
gave a product with the largest concentration of the FRAP and CUPRAC antioxidants (Table 8). At the same time, the EY was the lowest in this trial and, as a result, was the lowest recovery yield of antioxidants (Table 9). One can suppose that alcohol-enriched solvents are more suitable for the extraction of solids of high active lipophilic antioxidant species, but not the abundant fractions of more hydrophilic and less active antioxidants including carbohydrates. Therefore, the total recovery yield of antioxidants is higher with 30 %, where 90 % EtOH is used as a solvent, although the specific antioxidant capacity is somewhat lower in the former case. Aloe Antioxidants Finally, it is relevant to the topic of the paper to discuss the nature of aloe antioxidants based on the above analysis and the data collected in Table 2. For the convenience of the reader, we compiled the maximal and minimal values of some response variables expressed on a molar concentration basis in Table 10. The first observation is that the applied antioxidant assays evaluate different (possibly, partially overlapping) fractions of antioxidant species. While the DPPH method evaluates the free radical scavenging capacity of a sample, the CUPRAC and FRAP methods evaluate the content of electron-donating species with a certain redox potential (Prior et al. 2005). As seen, the concentration of the radical scavenging species is three to ten times less than the
Table 8 Experimental and predicted values for response variables in trials I–III Response
Trial I Optimized EY
Trial II Optimized (CUPRAC+FRAP+EY)
Trial III Optimized (EY CUPRAC+EY FRAP)
Extraction yield (%) Aloin A (mg/g)
Experimental 78.3±0.05 0.85±0.05
Predicted 82.5 0.58
δ, % 5.4 −25.7
Experimental 38.6±0.2 2.27±0.03
Predicted 38.0 2.64
δ, % −1.6 11.9
Experimental 73.3±1.6 0.83±0.02
Predicted 80.5 0.84
δ, % 9.8 1.6
Aloin B (mg/g) Aloesin (mg/g) DPPH (mg TE/g) FRAP (mg TE/g) CUPRAC (mg TE/g) TP (mg GAE/g) TC (mg D-Man/g)
0.36±0.02 0.18±0.03 4.10±0.10 16.5±0.5 116±4 4.06±0.13 411±18
0.27 1.21
−32.1 572
0.95 0.90
16.4 −15.1
−0.4 −13.3
−9.5 7.0 2.8 −21.1
22.7 154 6.23 590
17.1 −0.3 −2.2 −2.4
0.35±0.01 1.36±0.01 2.75±0.56 12.3±0.3 114±3 4.76±0.11 456±41
0.35 1.18
15.0 124 4.20 324
0.85±0.01 1.06±0.07 3.77±0.22 19.4±1.2 154±8 6.37±0.09 605±24
16.1 127 4.39 396
28.2 10.9 −7.8 −13.1
Food Anal. Methods Table 9 Experimental and predicted values of response variables in trials I–III expressed per gram of aloe powder (EY Response) Response
Trial I Optimized EY
Trial II Optimized (CUPRAC+FRAP+EY)
Trial III Optimized (EY CUPRAC+EY FRAP)
EY Aloin A (mg/g a.p.) EY Aloin B (mg/g a.p.) EY Aloesin (mg/g a.p.)
Experimental 0.66±0.05 0.28±0.02 0.14±0.02
Predicted 0.72 0.30 0.98
δ, % 8.1 6.3 600
Experimental 0.88±0.02 0.33±0.01 0.41±0.02
Predicted 0.80 0.30 0.36
δ, % −8.7 −8.9 −11.2
Experimental 0.61±0.00 0.26±0.00 1.00±0.02
Predicted 0.76 0.32 0.96
δ, % 25.6 22.6 −3.8
EY DPPH(mg Tro/g a.p.) EY FRAP (mg Tro/g a.p) EY CUPRAC (mg Tro/g a.p.) EY TP (mg GA/g a.p.) EY TC (mg D-Man/g a.p.)
3.25±0.12 13.0±0.6 91.3±3.1 3.18±0.14 322±15
2.67 12.6 97.8 3.51 320
−17 −2.5 7.6 9.7 −0.4
1.46±0.08 7.49±0.44 59.5±3.1 2.46±0.04 234±10
1.42 7.84 54.3 2.12 196
−0.4 4.7 −8.7 −13.6 −16.3
1.99±0.42 9.2±0.2 84±2 3.49±0.09 334±28
2.70 12.8 98.0 3.53 338
40.7 38.6 17.0 1.1 1.1
a.p. aloe powder
concentration of the FRAP-sensitive antioxidants. Of course, the latter fraction may include partly or entirely the radical scavengers, which may be reductants too. It should be mentioned that the DPPH·radical may not be sensitive to some antioxidant molecules, in particular, to those of a larger size (Prior et al. 2005). Consequently, the results of the DPPH assay may underestimate the radical absorbance capacity of the extracts to a degree. The CUPRAC test, evidently, titrates the widest spectrum of antioxidant compounds. Therefore, it stands to reason that its indicators are 1.5–2.9 times higher than the results of the FRAP assay. TP content is much less than FRAP and CUPRAC concentrations, meaning that the phenolic species are not the only constituents of the aloe antioxidants. This conclusion agrees with observations of other researchers on the antioxidant activities of non-phenolic aloe compounds (Yagi et al. 2003; Liu et al. 2007). The chromatograms of the extracts we studied (Fig. 1) contain four major peaks of chromones and the peaks of aloin A and B (identified based on retention times and UV spectra). No noticeable peaks that could be attributed based on their UV spectra to flavonoids were detected. The sum of the major peaks converted into milligram/gram units is systematically higher than TP content by 6 to 100 %, depending on extraction conditions (Table 10), and may be considered a coincidence based on assumptions accepted for estimating the summary phenolic content chromatographically. The fact that molecular weights of
chromones and anthrones are larger than that of gallic acid (the standard) may contribute to an overrated (with respect to GAE) chromatographic estimate of TP. So, the specific response of aloin in the Folin–Ciocalteu assay is 2.25 times less than the response of gallic acid, which is well explained by the ratio of respective molecular weights 418/170=2.45.
Conclusion A. vera gel antioxidants comprise both phenolic and nonphenolic compounds. These latter, most likely carbohydrates, account for a considerable part of total antioxidant capacity. Titration of Aloe gel extracts with different probers deliver widely ranging estimates of antioxidant capacity, suggesting that the fraction of aloe antioxidants includes compounds with very different reducing and radical quenching abilities. In order to isolate this fraction with the highest recovery yield, 34 % ethanol at elevated temperature (60 °С in this study) should be used with a liquid-to-solid ratio of 46 ml/g dry weight. A process time of 1 h is sufficient. Using ethanolenriched solvents with an alcohol percentage of around 90 % will result in a high concentration of antioxidants in the extracted substance, but the product yield will be low, as will the recovery of the target compounds. Statistical analysis shows that solvent composition is the main influencing factor in the extraction of aloe gel powder,
Table 10 Extreme values of the DPPH, FRAP, CUPRAC, and TP assays (molar concentration) and of the TP and Ch+An assays (mass concentration) found in the extraction experiments (Table 2)
Minimum Maximum
DPPH (μM TE/g)
FRAP (μM TE/g)
CUPRAC (μM TE/g)
TP (μM GA/g)
TP (mg GA/g)
Ch+An (mg/g)
8.25 18.5
43.0 105.8
92.8 178.3
19.4 46.3
3.30 7.87
4.37 13.4
Ch+An the sum of chromones and anthrones evaluated chromatographically
Food Anal. Methods
followed by temperature and L/S ratio. Extraction time, when higher than 1 h, feebly affects the efficacy of the process. Second-order polynomial models do not always approximate the raw experimental data with high accuracy, and even fail to give an adequate fit to the concentration of aloesin and to the CUPRAC assay results. On the contrary, composite data (extraction yield × response) can be well approximated by second-order polynomials (R2adj >0.9) for all the response variables considered, except for the concentrations of aloins, in which case R2adj >0.76. Although the rationale beyond such an improvement in statistical indicators is not clear, the use of the composite response function may be recommended for engineering and design calculations in the aloe industry.
Acknowledgments This paper resulted from the Konkuk University research support program. Compliance With Ethics Requirements The authors declare that the design, performance, and reporting of research funded under the Bio-industry Technology Development Program (111093-3) grants is free from bias resulting from investigator financial conflicts of interest. No financial relationship with other institutions or private industry has influenced the results of this study. Conflict of Interest Seol Kim declares that he has no conflict of interest. Leonid Asnin declares that he has no conflict of interest. Awraris D. Assefa declares that he has no conflict of interest. Eun Young Ko declares that he has no conflict of interest. Kavita Sharma declares that he has no conflict of interest. Se Won Park declares that he has no conflict of interest. This article does not contain any studies with human or animal subjects.
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