Ultrasonics Sonochemistry 22 (2015) 446–453
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Application of ultrasound for enhanced extraction of prebiotic oligosaccharides from selected fruits and vegetables Ruzica Jovanovic-Malinovska, Slobodanka Kuzmanova, Eleonora Winkelhausen ⇑ Department of Food Technology and Biotechnology, Faculty of Technology and Metallurgy, University SS. Cyril and Methodius, Rudjer Boskovic 16, 1000 Skopje, Former Yugolav Republic of Macedonia
a r t i c l e
i n f o
Article history: Received 13 February 2014 Received in revised form 20 May 2014 Accepted 21 July 2014 Available online 28 July 2014 Keywords: Ultrasound assisted extraction Prebiotic Oligosaccharides Fruit Vegetable
a b s t r a c t Ultrasound assisted extraction (UAE) was used to extract oligosaccharides from selected fruits (blueberry, nectarine, raspberry, watermelon) and vegetables (garlic, Jerusalem artichoke, leek, scallion, spring garlic and white onion). The individual fractions of the oligosaccharides were analyzed: 1-kestose (GF2), nystose (GF3) and 1F-b-fructofuranosylnystose (GF4) from the fructo-oligosaccharides (FOS), and raffinose and stachyose from the raffinose family oligosaccharides (RFO). Extraction parameters including solvent concentration (35–85% v/v), extraction temperature (25–50 °C) and sonication time (5–15 min) were examined using response surface methodology (RSM). Ethanol concentration of 63% v/v, temperature of 40 °C and extraction time of 10 min gave maximal concentration of the extracted oligosaccharides. The experimental values under optimal conditions were consistent with the predicted values. UAE increased the concentration of extracted oligosaccharides in all fruits and vegetables from 2 to 4-fold compared to conventional extraction. The highest increase of total oligosaccharides extracted by UAE was detected in Jerusalem artichoke, 7.17 ± 0.348 g/100 g FW, compared to 1.62 ± 0.094 g/100 g FW with conventional method. Ó 2014 Elsevier B.V. All rights reserved.
1. Introduction Diet rich in fruits and vegetables has been proven to exert a positive effect on preventing the development of a considerable number of chronic diseases such as cancer and cardiovascular diseases. This protective effect has been attributed to the high concentrations of functional compounds [1]. For the effective utilization of ingredients present in consumed foods, gut microflora plays an important role [2]. In this context, prebiotic oligosaccharides are considered to be key compounds. Since the late 1990s and the birth of the prebiotic concept, many scientists have started studying the health properties of prebiotic compounds which resulted in a number of scientific publications describing them in relation to human health [3,4]. The major prebiotic oligosaccharides in the market are fructo-oligosaccharides and galacto-oligosaccharides whose bioactive properties have been evaluated using a range of in vitro and in vivo methods [5–8]. The oligosaccharides are obtained by extraction from natural sources or by chemical or enzymatic synthesis [9–12]. For extraction of low-molecular weight carbohydrates such as oligosaccharides from plant material, the optimal solvent is water [13]. ⇑ Corresponding author. Tel.: +389 2 3088 256; fax: +389 2 3065 389. E-mail address: [email protected] (E. Winkelhausen). http://dx.doi.org/10.1016/j.ultsonch.2014.07.016 1350-4177/Ó 2014 Elsevier B.V. All rights reserved.
However, water also facilitates interference between carbohydrates and other water-soluble substances such as certain polysaccharides and proteins [14]. Thus, most of the conventional extraction methods for oligosaccharides often use high concentrations of alcohol [15]. The use of ultrasound assisted extraction (UAE) instead of traditional extraction has been increasing and its use has been investigated in the pharmaceutical, chemical and food industries. UAE became a good alternative extraction method when compared to classical extraction methods because of its high efficiency, low energy requirement and low water consumption (no reflux or refrigeration are needed) [16]. The improvement of the extraction process caused by ultrasound is attributed to the disruption of the cell wall, reduction of the particle size and the enhancement of the mass transfer of the cell content to the solvent caused by the collapse of the bubbles produced by cavitation [17]. Therefore, UAE provides increased extraction yield, increased rate of extraction, reduced extraction time and higher processing throughput along with the advantage of usage of reduced temperature and solvent volume which is very advantageous for the extraction of heat labile compounds [18]. The application of UAE in food processing technology is of interest for enhancing extraction of components from plant and animal materials such as phenolic compounds, anthocyanins, aromatic compounds, polysaccharides, oils and functional
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compounds [19–25]. Among all applications, UAE is nowadays considered as the most feasible and economically profitable largescale application of ultrasound in the food field [26]. The aim of this study was to enhance the extraction of oligosaccharides from selected fruits and vegetables by application of ultrasound assisted method. To optimize the extraction conditions, that is the type and the concentration of solvent, extraction time and ultrasound temperature, response surface methodology (RSM) was used. Ultrasound extraction under optimized conditions was performed to look into the individual fractions of fructooligosaccharides (FOS) such as 1-kestose (GF2), nystose (GF3), and 1F-b-fructofuranosylnystose (GF4) as well as raffinose family oligosaccharides (RFO) such as raffinose and stachyose. Furthermore, a comparison between conventional extraction method and ultrasound assisted extraction was conducted. To our knowledge there have been no published data on ultrasound extraction of oligosaccharides and their subsequent analysis for individual fractions.
2. Materials and methods 2.1. Samples and sample preparation The foods selected for analysis were 4 fruits and 6 vegetables, with the highest content of oligosaccharides according to our previous investigation [27]. Fresh food samples were collected from local green markets (nectarine and watermelon) and grocery stores (Jerusalem artichoke) or directly from producers (blueberry, raspberry, garlic, leek, scallion, spring garlic and white onion). The food samples were transferred to the laboratory and analyzed immediately. Approximately 500 g of each sample was chosen at random. The edible part was cut into small pieces (5–15 mm) and dried at 50 °C in a vacuum oven (Heraeus Instruments vacutherm VT 6025, Hanau, Germany) over period of 12 to 24 h until constant dry mass was reached. Dried samples were crushed with a laboratory grinder to a particle size less than 1 mm before extraction. 2.2. Conventional extraction of oligosaccharides The dried and grind samples (200 mg) were extracted with ethanol (85% v/v; 20 mL) as described by Espinosa-Martos et al. [28]. Extractions were performed in screw-capped tubes, at 50 °C in a water bath with constant shaking for 1 h. After cooling at room temperature, the samples were centrifuged at 3000g for 15 min. Ten mL of supernatants were evaporated in a vacuum rotary evaporator at 50 °C until the samples were completely dried. The extracts were redissolved in deionized water (1.5 mL) and passed through 0.45 lm filters (Econofilter, Agilent Technologies, Santa Clara, CA, USA) just before high-performance liquid chromatography (HPLC) analysis. 2.3. Ultrasound assisted extraction of oligosaccharides The dried and grind samples (200 mg) were extracted with 20 mL ethanol, methanol or acetone (20–96% v/v). Extractions were performed in screw-capped tubes, at different temperatures (20–60 °C) in an ultrasound water bath at 40 kHz (Cole-Parmer 8890, Vernon Hills, Illinois, USA) with constant shaking for 5, 10, 20 or 30 min. After cooling at room temperature, the samples were centrifuged at 3000g for 15 min. Ten mL of supernatants were evaporated in a vacuum rotary evaporator at 50 °C until the samples were completely dried. The extracts were redissolved in deionized water (1.5 mL) and passed through 0.45 lm filters (Econofilter, Agilent Technologies) just before high-performance liquid chromatography (HPLC) analysis.
2.4. Determination of oligosaccharides by high-performance liquid chromatography Twenty microliters of prepared samples were injected into Agilent Technologies 1200 HPLC fitted with Zorbax carbohydrate analysis column (4.6 150 mm, 5 lm particle size), Zorbax NH2 guard column (4.6 12.5 mm) (Agilent, USA) and refractive index (RI) detector. The mobile phase was 75:25 (v/v) acetonitrile/water and the flow rate was 1.4 mL/min. The column temperature was kept at 30 °C. Appropriate dilutions of a solution containing each of the carbohydrates, 1-kestose, nystose, 1F-b-fructofuranosylnystose, raffinose and stachyose, all purchased from Sigma–Aldrich (St. Louis, Missouri, USA) HPLC grade were used as calibration standards. 2.5. Experimental design 2.5.1. Single factor experiments 2.5.1.1. Selection of solvent type. By fixing extraction time (10 min) and extraction temperature (50 °C), samples were extracted with 60% (v/v) acetone, 60% (v/v) ethanol, and 60% (v/v) methanol respectively. The extraction procedure was described in Section 2.3. The solvent type was selected according to the value of extracted oligosaccharides (g/100 g FW). 2.5.1.2. Effect of solvent concentration on extraction of oligosaccharides. Using the best solvent type selected in single factor experiments, Section 2.5.1.1, samples were extracted with solvent ranging from 20% to 96% (v/v) by fixing the extraction time and extraction temperature at 10 min and 50 °C, respectively. 2.5.1.3. Effect of extraction time on extraction of oligosaccharides. Samples were extracted using the best solvent type and the best solvent concentration selected in single factor experiments, Sections 2.5.1.1 and 2.5.1.2, respectively. The extraction procedures were repeated as described in section of single factor experiments by varying the extraction time from 5 to 30 min while setting up the extraction temperature constant at 50 °C. 2.5.1.4. Effect of extraction temperature on extraction of oligosaccharides. Using the best solvent type at its corresponding concentration selected in single factor experiments, Sections 2.5.1.1 and 2.5.1.2, the samples were extracted at various extraction temperatures ranged from 20 to 60 °C at the optimum time determined in single factor experiments, Section 2.5.1.3. 2.5.2. Response surface methodology The oligosaccharides content was further optimized through the response surface methodology (RSM) approach. Based on the results of the single factor experiments, ranges of the three factors, solvent concentration (X1), ultrasound time (X2) and ultrasound temperature (X3) were determined. The experiments were designed to evaluate the effect of these factors on the yield of oligosaccharides using ultrasound extraction method (Table 1). Predicted response values for the total oligosaccharide concentration were obtained using Box–Behnken Design (BBD). The mathematical model representing the concentration of oligosaccharides as a function of the independent variables within the range studied was expressed as follows:
Y ¼ b0 þ
3 3 2 X 3 X X X bi X i þ bii X 2i þ bii X i Y j i¼1
i¼1
ð1Þ
i¼1 j¼iþ1
where Y is the estimated response; b0 is a constant; and bi, bii, bij are the linear, quadratic and interactive coefficients of the model,
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Table 1 Independent variables and the response of Box–Behnken RSM model for ultrasound assisted extraction of oligosaccharides in scallion. Assay
X1 solvent concentration (% v/v)
X2 ultrasound time (min)
X3 ultrasound temperature (°C)
Concentration of total OS (g/100 g FW)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
60 35 85 35 60 35 60 60 85 35 60 85 60 85 60
5 15 10 10 10 10 5 15 15 5 10 5 15 10 10
55 40 55 25 40 55 25 25 40 40 40 40 55 25 40
6.9 6.3 7.0 6.1 7.8 6.6 6.7 7.0 7.1 6.0 7.6 6.6 7.3 6.8 7.9
respectively. X1, X2, and X3 represent the levels of the independent variables, concentration, time and temperature correspondingly. 2.6. Statistical analysis All experiments were performed in triplicates. The results were expressed as g per 100 g fresh weight (FW), and represent mean values ± standard deviation (n = 3). Descriptive statistics and oneway analysis of variance (ANOVA) were performed on the parameters to evaluate the significant differences among the samples at 95% confidence interval (p 6 0.05) according to Tukey’s test using Minitab 15 statistical software. 3. Results and discussion 3.1. Effect of single factors on extraction of oligosaccharides assisted by ultrasound 3.1.1. Solvent type The selection of solvent is a first crucial step for parameters optimization, and critical for the complex food samples as it will determine the amount and type of oligosaccharides being extracted. In this study scallion was chosen as a test sample for optimization of the parameters because of its high content of total oligosaccharides [27]. Fig. 1A showed that aqueous acetone was slightly better than aqueous methanol and aqueous ethanol in ultrasound extraction of oligosaccharides from scallion under same extraction conditions (50% v/v, 50 °C, and 10 min). However, the differences among the extracted concentrations of oligosaccharides by all solvents applied were not significant (p > 0.05). Johansen et al. [14] showed that the aqueous ethanol (50% v/v) was as effective as 50% (v/v) methanol for conventional extraction of raffinose family oligosaccharides. Therefore, ethanol, which is categorized as GRAS (Generally Recognized as Safe) and is preferred for application in food systems, was chosen as the extraction solvent for the next experiments. 3.1.2. Ethanol concentration The effect of ethanol concentration on ultrasound extraction of oligosaccharides from scallion is shown in Fig. 1B. The concentration of oligosaccharides increased with the increment of ethanol concentration up to 60% v/v (7.49 ± 0.82 g/100 g FW). After this point, the concentration of oligosaccharides gradually declined reaching 5.60 ± 0.69 g/100 g FW at ethanol concentration of 96%
v/v. Similarly, Ekvall et al. [29] reported that maximum yield of raffinose family oligosaccharides from immature green peas was obtained at about 50% v/v ethanol followed by a decreased yield with further increase of ethanol concentration. Knudsen and Li [13] also found that increased ethanol concentration beyond 60% v/v noticeably reduced the amount of raffinose oligosaccharides extracted from plant material. A remarkable drop in oligosaccharides content at 96% v/v ethanol revealed that concentrated solvent did not ensure a good recovery of oligosaccharides compared to aqueous ethanol. Thus, ethanol concentrations of 35%, 60% and 85% v/v were selected as the lower, middle and upper level, respectively, to be employed in RSM optimization. 3.1.3. Extraction time The range of extraction time was designed based on the practical and economical aspects. The effect of time on the release of oligosaccharides extracted by ultrasound assisted technique is shown in Fig. 1C. The concentration of oligosaccharides increased with the time and reached 7.33 ± 0.22 g/100 g FW at the 10th minute. After that, the concentration of extracted oligosaccharides was almost constant and further increase in process duration did not significantly (p > 0.05) improve the recovery of oligosaccharides. This observation can be well explained by Fick’s second law of diffusion, which stated that the final equilibrium between the solute concentrations in the solid matrix (plant matrix) and in the bulk solution (solvent) will be achieved after certain time. Hence, an excessive extraction time did not lead to enhanced extraction of oligosaccharides. In contrast, Han and Bail [30] reduced the content of raffinose family oligosaccharides in legumes by applying ultrasound treatment for a pretty long time, 1.5 and 3 h. According to Balachandran et al. [31], sonication leads to an increase in the effective diffusivity of the mass transfer process and this effect is maximal at short sonication times as was verified for oligosaccharides extraction. Taking into account these facts, extraction time of 5, 10 and 15 min was selected for RSM optimization. 3.1.4. Extraction temperature Temperature is the most important factor in the extraction of heat sensitive compounds. Along with the increase of temperature, the solvent diffusion rate and the mass transfer intensification result in the dissolution of components. The concentration of extracted oligosaccharides increased from 5.90 ± 0.23 to 7.55 ± 0.32 g/100 g FW when extraction temperature increased from 20 to 50 °C as reflected in Fig. 1D. Jiang et al. [32], optimizing the parameters of the ultrasound assisted extraction of oligosaccharides from longan fruit pericarp, found the optimal temperature to be 65 °C. However, it should be noted that increasing the temperature beyond certain values might promote possible concurrent decomposition of oligosaccharides which were already mobilized at lower temperatures or even the degradation of oligosaccharides that were still present in the plant matrix. It was reported that significant hydrolysis of FOS took place at T P 60 °C [33]. Additionally, high temperatures may encourage solvent loss through vaporization and increase the cost of the extraction process. Therefore, extraction temperatures of 25, 40 and 55 °C were chosen as the lower, middle and upper levels, respectively, to be applied in RSM optimization. 3.2. Optimization of ultrasound assisted extraction by response surface methodology The extraction conditions not only affect the concentration of extracted oligosaccharides, but might additionally cause structural changes. Multiple regression analysis using the quadratic polynomial model (Eq. (1)) was performed based on the results in Table 1. The values of the independent process variables considered
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Fig. 1. Effect of (A) solvent type; (B) ethanol concentration; (C) extraction time; and (D) extraction temperature on total oligosaccharides content in scallion extracted by ultrasound. Values marked by different letters are significantly different (p < 0.05).
(ethanol concentration-X1, time-X2 and temperature-X3), as well as the measured and predicted values of the response (concentration of oligosaccharides), are given in Table 2. By applying multiple regression analysis on the experimental data, the response variable and the test variables were found to be related by the following polynomial equation:
Table 2 Analysis of the variance of the regression coefficients of the fitted polynomial quadratic equation for oligosaccharide concentration. Source
Sum of squares
Degree of freedom
F-value
p-Value
Ethanol concentration (X1) Time (X2) Temperature (X3) X1 X2 X1 X3 X2 X3 X21 X22 X23 Regression Linear Square Interaction Residual error Lack-of-fit Pure error Total
0.32000
1
48.27
0.001
0.12500 0.18000 0.06250 0.02250 0.00250 1.34776 0.13376 0.24665 2.44067 0.62500 1.72817 0.08750 0.11667 0.07000 0.04667 2.55733
1 1 1 1 1 1 1 1 9 3 3 3 5 3 2 14
2.47 14.67 2.68 0.96 0.11 57.76 10.22 14.64 11.62 17.89 24.69 1.25
0.177 0.012 0.163 0.371 0.757 0.001 0.024 0.012 0.007 0.004 0.002 0.385
1.00
0.435
R2 = 0.954
R2adj = 0.892
Y ¼ 3:299 þ 0:009 X 1 þ 0:035 X 2 þ 0:009 X 3 3:776 X 21 4:067 X 22 6:008 X 23 þ 1:250 X 1 X 2 8:333 X 1 X 3 þ 4:444 X 2 X 3
ð2Þ
The adequacy of the model was checked with ANOVA which was tested by Tukey‘s statistical analysis (Table 2). The F-value and p-value of the lack of fit were 1.07 and 0.457 respectively, implying an insignificant difference relative to the pure error and a good fitness of the model. Coefficient of determination (R2) is defined as the ratio of the explained variation to the total variation, and R2 = 0.954 approaching unity suggested a good relevance of the dependent variables in the model. The adjusted determination coefficient of the model (R2adj = 0.892) confirmed that the model was significant, indicating a good degree of correlation between the actual values and the predicted values of total oligosaccharides. The coefficient estimates of the model equation, along with the corresponding F-values and p-values are presented in Table 2. The p-value is used as a tool to check the significance of each coefficient, and also indicates the interaction strength between each independent variable. A small p-value indicates a more significant coefficient [34]. It can be seen that X1, X3, X21, X22, and X23 were significant model terms. The effect of solvent concentration, extraction time and temperature for UAE on the concentration of extracted total oligosaccharides is shown in Fig. 2. The relationship between independent and dependent variables is illustrated by three-dimensional representation of the response surfaces and the two-dimensional contours generated by the model. Two variables within the experimental range are depicted in three-dimensional surface plots when the
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Fig. 2. Response surface plots (A–C) and contour plots (D–F) showing the effect of the variables on the concentration of extracted oligosaccharides by ultrasound assistance.
third variable is kept constant at zero level. From these threedimensional profiles, the interactions between any two factors can be easily observed. The shapes of the contour plots, elliptical or circular, indicate whether the interactions between the corresponding variables are significant or not [19]. An elliptical contour plot means the interactions between the variables are significant while a circular contour plot means otherwise. Ethanol concentration had a high impact on the concentration of extracted oligosaccharides. Higher amount of oligosaccharides was extracted by ethanol concentration ranging from 52% to 66% v/v, temperature range of 35–50 °C (Fig. 2A), and ultrasound time between 9 and 13 min (Fig. 2B). Increase in the oligosaccharide concentration was observed when extraction time and temperature were kept
at their middle values (Fig. 2C). From the Fig. 2A–C, maximal concentration of oligosaccharides could be obtained at optimal value between every two factors. All parameters showed significant quadratic effect; time and temperature at p < 0.05 while ethanol concentration at p < 0.005 (Table 2). Based on these results and the model equation, it was found out that the optimal combination of the independent variables was ethanol concentration of 63% v/v at 40 °C for 10 min, corresponding to the maximal concentration of extracted oligosaccharides in scallion of 7.95 ± 0.135 g/100 g FW. To compare the predicted results with the experimental ones, experimental rechecking was performed using optimal conditions. The good correlation between experimental and predicted values confirmed the adequacy of the
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response model. A chromatographic profile of oligosaccharides extracted by ultrasound assistance from scallion under optimized conditions is shown in Fig. 3. 3.3. Individual fractions of oligosaccharides yielded by ultrasound assisted extraction The concentration of individual fractions of fructo-oligosaccharides, 1-kestose (GF2), nystose (GF3) and 1F-b-fructofuranosylnystose (GF4) as well as raffinose family oligosaccharides, raffinose and stachyose, in 6 vegetables (garlic, Jerusalem artichoke, leek, scallion, spring garlic and white onion) and 4 fruits (blueberry, nectarine, raspberry and watermelon) obtained by ultrasound extraction are shown in Fig. 4. The UAE was performed under optimized conditions (63% v/v ethanol concentration, 40 °C, and
451
10 min) as obtained by response surface methodology. The optimized conditions for UAE developed for scallion were extrapolated and applied for extraction of oligosaccharides in other fruits and vegetables. As shown in Fig. 4, vegetable with statistically significant content of total FOS was scallion (6.22 ± 0.171 g/100 g FW) while fruit with the highest amount of total FOS was nectarine (1.75 ± 0.084 g/100 g FW). Individual fractions of FOS were found in all fruit and vegetable samples. In fruits, GF2 was found to be the highest in watermelon (0.53 ± 0.027 g/100 g FW), whereas in vegetables GF2 was the highest in scallion (2.85 ± 0.159 g/ 100 g FW). On the other hand, GF3 was the highest in nectarine (1.19 ± 0.057 g/100 g FW), while in vegetables, GF3 was the highest in Jerusalem artichoke (3.25 ± 0.173 g/100 g FW). There was a wide range of GF4 content in the samples, from 0.09 ± 0.003 g/100 g FW in raspberry to 1.25 ± 0.063 g/100 g FW in scallion. RFO were not
Fig. 3. HPLC profile of oligosaccharides extracted by ultrasound assistance from scallion under optimized conditions (ethanol concentration 63% v/v, 40 °C, time 10 min); F: fructose, G: glucose, S: sucrose, GF2: 1-kestose, GF3: nystose, GF4: 1F-b-fructofuranosylnystose, R: raffinose.
Fig. 4. Individual fractions of FOS and RFO in selected fruits and vegetables yielded by ultrasound assisted extraction under optimized conditions (ethanol concentration 63% v/v, 40 °C, time 10 min).
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Fig. 5. Conventional (ethanol concentration 85% v/v, 50 °C, 60 min) versus ultrasound assisted (ethanol concentration 63% v/v, 40 °C, 10 min) extraction of total oligosaccharides from selected fruits and vegetables.
detected in fruits. Of the vegetables analyzed, scallion had the highest content of RFO, 1.73 ± 0.061 g/100 g FW, mainly raffinose whilst stachyose was present only in Jerusalem artichoke (1.29 ± 0.053 g/100 g FW). 3.4. Comparison of ultrasound and conventional extraction of oligosaccharides A comparison of total oligosaccharides extracted conventionally [27] and by ultrasound method is presented in Fig. 5. The results showed that ultrasound method can considerably increase oligosaccharides extraction throughput. The increased content of total oligosaccharides ranged from 2 to 4-fold. The highest increase of total oligosaccharide content was spotted in Jerusalem artichoke, from 1.96 g/100 g FW with conventional extraction to 7.17 g/ 100 g FW with UAE. This change could have resulted from the enzymatic hydrolysis of fructans, molecules with high degree of polymerization (DP) present in Jerusalem artichoke. Lingyun et al. [24] reported that some low molecular weight fragments had formed by the action of ultrasound, changing the chemical composition of extracted inulin from Jerusalem artichoke. Degradation of polysaccharides was also reported by Yang et al. [35] during their experiments with ultrasound extraction of Flammulina velutipes polysaccharides. Our results also showed high increase in the amount of total oligosaccharides extracted by UAE in spring garlic (from 1.31 to 5.53 g/100 g FW) onion (from 2.24 to 6.78 g/ 100 g FW) and leek (from 1.07 to 3.05 g/100 g FW) in comparison with conventional extraction. As previously noted by Muir et al. [36], these vegetables have longer DP length (DP 8-11). The selection of an extraction method mainly depends on the advantages and disadvantages of the processes such as extraction yield, complexity, production cost, environmental friendliness and safety [37]. According to the results of this study, beyond increase in extraction efficiency, there was a significant decrease in extraction time. Ultrasound assisted method for oligosaccharide
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Application of ultrasound for enhanced extraction of prebiotic oligosaccharides from selected fruits and vegetables Ruzica Jovanovic-Malinovska, Slobodanka Kuzmanova, Eleonora Winkelhausen ⇑ Department of Food Technology and Biotechnology, Faculty of Technology and Metallurgy, University SS. Cyril and Methodius, Rudjer Boskovic 16, 1000 Skopje, Former Yugolav Republic of Macedonia
a r t i c l e
i n f o
Article history: Received 13 February 2014 Received in revised form 20 May 2014 Accepted 21 July 2014 Available online 28 July 2014 Keywords: Ultrasound assisted extraction Prebiotic Oligosaccharides Fruit Vegetable
a b s t r a c t Ultrasound assisted extraction (UAE) was used to extract oligosaccharides from selected fruits (blueberry, nectarine, raspberry, watermelon) and vegetables (garlic, Jerusalem artichoke, leek, scallion, spring garlic and white onion). The individual fractions of the oligosaccharides were analyzed: 1-kestose (GF2), nystose (GF3) and 1F-b-fructofuranosylnystose (GF4) from the fructo-oligosaccharides (FOS), and raffinose and stachyose from the raffinose family oligosaccharides (RFO). Extraction parameters including solvent concentration (35–85% v/v), extraction temperature (25–50 °C) and sonication time (5–15 min) were examined using response surface methodology (RSM). Ethanol concentration of 63% v/v, temperature of 40 °C and extraction time of 10 min gave maximal concentration of the extracted oligosaccharides. The experimental values under optimal conditions were consistent with the predicted values. UAE increased the concentration of extracted oligosaccharides in all fruits and vegetables from 2 to 4-fold compared to conventional extraction. The highest increase of total oligosaccharides extracted by UAE was detected in Jerusalem artichoke, 7.17 ± 0.348 g/100 g FW, compared to 1.62 ± 0.094 g/100 g FW with conventional method. Ó 2014 Elsevier B.V. All rights reserved.
1. Introduction Diet rich in fruits and vegetables has been proven to exert a positive effect on preventing the development of a considerable number of chronic diseases such as cancer and cardiovascular diseases. This protective effect has been attributed to the high concentrations of functional compounds [1]. For the effective utilization of ingredients present in consumed foods, gut microflora plays an important role [2]. In this context, prebiotic oligosaccharides are considered to be key compounds. Since the late 1990s and the birth of the prebiotic concept, many scientists have started studying the health properties of prebiotic compounds which resulted in a number of scientific publications describing them in relation to human health [3,4]. The major prebiotic oligosaccharides in the market are fructo-oligosaccharides and galacto-oligosaccharides whose bioactive properties have been evaluated using a range of in vitro and in vivo methods [5–8]. The oligosaccharides are obtained by extraction from natural sources or by chemical or enzymatic synthesis [9–12]. For extraction of low-molecular weight carbohydrates such as oligosaccharides from plant material, the optimal solvent is water [13]. ⇑ Corresponding author. Tel.: +389 2 3088 256; fax: +389 2 3065 389. E-mail address: [email protected] (E. Winkelhausen). http://dx.doi.org/10.1016/j.ultsonch.2014.07.016 1350-4177/Ó 2014 Elsevier B.V. All rights reserved.
However, water also facilitates interference between carbohydrates and other water-soluble substances such as certain polysaccharides and proteins [14]. Thus, most of the conventional extraction methods for oligosaccharides often use high concentrations of alcohol [15]. The use of ultrasound assisted extraction (UAE) instead of traditional extraction has been increasing and its use has been investigated in the pharmaceutical, chemical and food industries. UAE became a good alternative extraction method when compared to classical extraction methods because of its high efficiency, low energy requirement and low water consumption (no reflux or refrigeration are needed) [16]. The improvement of the extraction process caused by ultrasound is attributed to the disruption of the cell wall, reduction of the particle size and the enhancement of the mass transfer of the cell content to the solvent caused by the collapse of the bubbles produced by cavitation [17]. Therefore, UAE provides increased extraction yield, increased rate of extraction, reduced extraction time and higher processing throughput along with the advantage of usage of reduced temperature and solvent volume which is very advantageous for the extraction of heat labile compounds [18]. The application of UAE in food processing technology is of interest for enhancing extraction of components from plant and animal materials such as phenolic compounds, anthocyanins, aromatic compounds, polysaccharides, oils and functional
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compounds [19–25]. Among all applications, UAE is nowadays considered as the most feasible and economically profitable largescale application of ultrasound in the food field [26]. The aim of this study was to enhance the extraction of oligosaccharides from selected fruits and vegetables by application of ultrasound assisted method. To optimize the extraction conditions, that is the type and the concentration of solvent, extraction time and ultrasound temperature, response surface methodology (RSM) was used. Ultrasound extraction under optimized conditions was performed to look into the individual fractions of fructooligosaccharides (FOS) such as 1-kestose (GF2), nystose (GF3), and 1F-b-fructofuranosylnystose (GF4) as well as raffinose family oligosaccharides (RFO) such as raffinose and stachyose. Furthermore, a comparison between conventional extraction method and ultrasound assisted extraction was conducted. To our knowledge there have been no published data on ultrasound extraction of oligosaccharides and their subsequent analysis for individual fractions.
2. Materials and methods 2.1. Samples and sample preparation The foods selected for analysis were 4 fruits and 6 vegetables, with the highest content of oligosaccharides according to our previous investigation [27]. Fresh food samples were collected from local green markets (nectarine and watermelon) and grocery stores (Jerusalem artichoke) or directly from producers (blueberry, raspberry, garlic, leek, scallion, spring garlic and white onion). The food samples were transferred to the laboratory and analyzed immediately. Approximately 500 g of each sample was chosen at random. The edible part was cut into small pieces (5–15 mm) and dried at 50 °C in a vacuum oven (Heraeus Instruments vacutherm VT 6025, Hanau, Germany) over period of 12 to 24 h until constant dry mass was reached. Dried samples were crushed with a laboratory grinder to a particle size less than 1 mm before extraction. 2.2. Conventional extraction of oligosaccharides The dried and grind samples (200 mg) were extracted with ethanol (85% v/v; 20 mL) as described by Espinosa-Martos et al. [28]. Extractions were performed in screw-capped tubes, at 50 °C in a water bath with constant shaking for 1 h. After cooling at room temperature, the samples were centrifuged at 3000g for 15 min. Ten mL of supernatants were evaporated in a vacuum rotary evaporator at 50 °C until the samples were completely dried. The extracts were redissolved in deionized water (1.5 mL) and passed through 0.45 lm filters (Econofilter, Agilent Technologies, Santa Clara, CA, USA) just before high-performance liquid chromatography (HPLC) analysis. 2.3. Ultrasound assisted extraction of oligosaccharides The dried and grind samples (200 mg) were extracted with 20 mL ethanol, methanol or acetone (20–96% v/v). Extractions were performed in screw-capped tubes, at different temperatures (20–60 °C) in an ultrasound water bath at 40 kHz (Cole-Parmer 8890, Vernon Hills, Illinois, USA) with constant shaking for 5, 10, 20 or 30 min. After cooling at room temperature, the samples were centrifuged at 3000g for 15 min. Ten mL of supernatants were evaporated in a vacuum rotary evaporator at 50 °C until the samples were completely dried. The extracts were redissolved in deionized water (1.5 mL) and passed through 0.45 lm filters (Econofilter, Agilent Technologies) just before high-performance liquid chromatography (HPLC) analysis.
2.4. Determination of oligosaccharides by high-performance liquid chromatography Twenty microliters of prepared samples were injected into Agilent Technologies 1200 HPLC fitted with Zorbax carbohydrate analysis column (4.6 150 mm, 5 lm particle size), Zorbax NH2 guard column (4.6 12.5 mm) (Agilent, USA) and refractive index (RI) detector. The mobile phase was 75:25 (v/v) acetonitrile/water and the flow rate was 1.4 mL/min. The column temperature was kept at 30 °C. Appropriate dilutions of a solution containing each of the carbohydrates, 1-kestose, nystose, 1F-b-fructofuranosylnystose, raffinose and stachyose, all purchased from Sigma–Aldrich (St. Louis, Missouri, USA) HPLC grade were used as calibration standards. 2.5. Experimental design 2.5.1. Single factor experiments 2.5.1.1. Selection of solvent type. By fixing extraction time (10 min) and extraction temperature (50 °C), samples were extracted with 60% (v/v) acetone, 60% (v/v) ethanol, and 60% (v/v) methanol respectively. The extraction procedure was described in Section 2.3. The solvent type was selected according to the value of extracted oligosaccharides (g/100 g FW). 2.5.1.2. Effect of solvent concentration on extraction of oligosaccharides. Using the best solvent type selected in single factor experiments, Section 2.5.1.1, samples were extracted with solvent ranging from 20% to 96% (v/v) by fixing the extraction time and extraction temperature at 10 min and 50 °C, respectively. 2.5.1.3. Effect of extraction time on extraction of oligosaccharides. Samples were extracted using the best solvent type and the best solvent concentration selected in single factor experiments, Sections 2.5.1.1 and 2.5.1.2, respectively. The extraction procedures were repeated as described in section of single factor experiments by varying the extraction time from 5 to 30 min while setting up the extraction temperature constant at 50 °C. 2.5.1.4. Effect of extraction temperature on extraction of oligosaccharides. Using the best solvent type at its corresponding concentration selected in single factor experiments, Sections 2.5.1.1 and 2.5.1.2, the samples were extracted at various extraction temperatures ranged from 20 to 60 °C at the optimum time determined in single factor experiments, Section 2.5.1.3. 2.5.2. Response surface methodology The oligosaccharides content was further optimized through the response surface methodology (RSM) approach. Based on the results of the single factor experiments, ranges of the three factors, solvent concentration (X1), ultrasound time (X2) and ultrasound temperature (X3) were determined. The experiments were designed to evaluate the effect of these factors on the yield of oligosaccharides using ultrasound extraction method (Table 1). Predicted response values for the total oligosaccharide concentration were obtained using Box–Behnken Design (BBD). The mathematical model representing the concentration of oligosaccharides as a function of the independent variables within the range studied was expressed as follows:
Y ¼ b0 þ
3 3 2 X 3 X X X bi X i þ bii X 2i þ bii X i Y j i¼1
i¼1
ð1Þ
i¼1 j¼iþ1
where Y is the estimated response; b0 is a constant; and bi, bii, bij are the linear, quadratic and interactive coefficients of the model,
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Table 1 Independent variables and the response of Box–Behnken RSM model for ultrasound assisted extraction of oligosaccharides in scallion. Assay
X1 solvent concentration (% v/v)
X2 ultrasound time (min)
X3 ultrasound temperature (°C)
Concentration of total OS (g/100 g FW)
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
60 35 85 35 60 35 60 60 85 35 60 85 60 85 60
5 15 10 10 10 10 5 15 15 5 10 5 15 10 10
55 40 55 25 40 55 25 25 40 40 40 40 55 25 40
6.9 6.3 7.0 6.1 7.8 6.6 6.7 7.0 7.1 6.0 7.6 6.6 7.3 6.8 7.9
respectively. X1, X2, and X3 represent the levels of the independent variables, concentration, time and temperature correspondingly. 2.6. Statistical analysis All experiments were performed in triplicates. The results were expressed as g per 100 g fresh weight (FW), and represent mean values ± standard deviation (n = 3). Descriptive statistics and oneway analysis of variance (ANOVA) were performed on the parameters to evaluate the significant differences among the samples at 95% confidence interval (p 6 0.05) according to Tukey’s test using Minitab 15 statistical software. 3. Results and discussion 3.1. Effect of single factors on extraction of oligosaccharides assisted by ultrasound 3.1.1. Solvent type The selection of solvent is a first crucial step for parameters optimization, and critical for the complex food samples as it will determine the amount and type of oligosaccharides being extracted. In this study scallion was chosen as a test sample for optimization of the parameters because of its high content of total oligosaccharides [27]. Fig. 1A showed that aqueous acetone was slightly better than aqueous methanol and aqueous ethanol in ultrasound extraction of oligosaccharides from scallion under same extraction conditions (50% v/v, 50 °C, and 10 min). However, the differences among the extracted concentrations of oligosaccharides by all solvents applied were not significant (p > 0.05). Johansen et al. [14] showed that the aqueous ethanol (50% v/v) was as effective as 50% (v/v) methanol for conventional extraction of raffinose family oligosaccharides. Therefore, ethanol, which is categorized as GRAS (Generally Recognized as Safe) and is preferred for application in food systems, was chosen as the extraction solvent for the next experiments. 3.1.2. Ethanol concentration The effect of ethanol concentration on ultrasound extraction of oligosaccharides from scallion is shown in Fig. 1B. The concentration of oligosaccharides increased with the increment of ethanol concentration up to 60% v/v (7.49 ± 0.82 g/100 g FW). After this point, the concentration of oligosaccharides gradually declined reaching 5.60 ± 0.69 g/100 g FW at ethanol concentration of 96%
v/v. Similarly, Ekvall et al. [29] reported that maximum yield of raffinose family oligosaccharides from immature green peas was obtained at about 50% v/v ethanol followed by a decreased yield with further increase of ethanol concentration. Knudsen and Li [13] also found that increased ethanol concentration beyond 60% v/v noticeably reduced the amount of raffinose oligosaccharides extracted from plant material. A remarkable drop in oligosaccharides content at 96% v/v ethanol revealed that concentrated solvent did not ensure a good recovery of oligosaccharides compared to aqueous ethanol. Thus, ethanol concentrations of 35%, 60% and 85% v/v were selected as the lower, middle and upper level, respectively, to be employed in RSM optimization. 3.1.3. Extraction time The range of extraction time was designed based on the practical and economical aspects. The effect of time on the release of oligosaccharides extracted by ultrasound assisted technique is shown in Fig. 1C. The concentration of oligosaccharides increased with the time and reached 7.33 ± 0.22 g/100 g FW at the 10th minute. After that, the concentration of extracted oligosaccharides was almost constant and further increase in process duration did not significantly (p > 0.05) improve the recovery of oligosaccharides. This observation can be well explained by Fick’s second law of diffusion, which stated that the final equilibrium between the solute concentrations in the solid matrix (plant matrix) and in the bulk solution (solvent) will be achieved after certain time. Hence, an excessive extraction time did not lead to enhanced extraction of oligosaccharides. In contrast, Han and Bail [30] reduced the content of raffinose family oligosaccharides in legumes by applying ultrasound treatment for a pretty long time, 1.5 and 3 h. According to Balachandran et al. [31], sonication leads to an increase in the effective diffusivity of the mass transfer process and this effect is maximal at short sonication times as was verified for oligosaccharides extraction. Taking into account these facts, extraction time of 5, 10 and 15 min was selected for RSM optimization. 3.1.4. Extraction temperature Temperature is the most important factor in the extraction of heat sensitive compounds. Along with the increase of temperature, the solvent diffusion rate and the mass transfer intensification result in the dissolution of components. The concentration of extracted oligosaccharides increased from 5.90 ± 0.23 to 7.55 ± 0.32 g/100 g FW when extraction temperature increased from 20 to 50 °C as reflected in Fig. 1D. Jiang et al. [32], optimizing the parameters of the ultrasound assisted extraction of oligosaccharides from longan fruit pericarp, found the optimal temperature to be 65 °C. However, it should be noted that increasing the temperature beyond certain values might promote possible concurrent decomposition of oligosaccharides which were already mobilized at lower temperatures or even the degradation of oligosaccharides that were still present in the plant matrix. It was reported that significant hydrolysis of FOS took place at T P 60 °C [33]. Additionally, high temperatures may encourage solvent loss through vaporization and increase the cost of the extraction process. Therefore, extraction temperatures of 25, 40 and 55 °C were chosen as the lower, middle and upper levels, respectively, to be applied in RSM optimization. 3.2. Optimization of ultrasound assisted extraction by response surface methodology The extraction conditions not only affect the concentration of extracted oligosaccharides, but might additionally cause structural changes. Multiple regression analysis using the quadratic polynomial model (Eq. (1)) was performed based on the results in Table 1. The values of the independent process variables considered
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449
Fig. 1. Effect of (A) solvent type; (B) ethanol concentration; (C) extraction time; and (D) extraction temperature on total oligosaccharides content in scallion extracted by ultrasound. Values marked by different letters are significantly different (p < 0.05).
(ethanol concentration-X1, time-X2 and temperature-X3), as well as the measured and predicted values of the response (concentration of oligosaccharides), are given in Table 2. By applying multiple regression analysis on the experimental data, the response variable and the test variables were found to be related by the following polynomial equation:
Table 2 Analysis of the variance of the regression coefficients of the fitted polynomial quadratic equation for oligosaccharide concentration. Source
Sum of squares
Degree of freedom
F-value
p-Value
Ethanol concentration (X1) Time (X2) Temperature (X3) X1 X2 X1 X3 X2 X3 X21 X22 X23 Regression Linear Square Interaction Residual error Lack-of-fit Pure error Total
0.32000
1
48.27
0.001
0.12500 0.18000 0.06250 0.02250 0.00250 1.34776 0.13376 0.24665 2.44067 0.62500 1.72817 0.08750 0.11667 0.07000 0.04667 2.55733
1 1 1 1 1 1 1 1 9 3 3 3 5 3 2 14
2.47 14.67 2.68 0.96 0.11 57.76 10.22 14.64 11.62 17.89 24.69 1.25
0.177 0.012 0.163 0.371 0.757 0.001 0.024 0.012 0.007 0.004 0.002 0.385
1.00
0.435
R2 = 0.954
R2adj = 0.892
Y ¼ 3:299 þ 0:009 X 1 þ 0:035 X 2 þ 0:009 X 3 3:776 X 21 4:067 X 22 6:008 X 23 þ 1:250 X 1 X 2 8:333 X 1 X 3 þ 4:444 X 2 X 3
ð2Þ
The adequacy of the model was checked with ANOVA which was tested by Tukey‘s statistical analysis (Table 2). The F-value and p-value of the lack of fit were 1.07 and 0.457 respectively, implying an insignificant difference relative to the pure error and a good fitness of the model. Coefficient of determination (R2) is defined as the ratio of the explained variation to the total variation, and R2 = 0.954 approaching unity suggested a good relevance of the dependent variables in the model. The adjusted determination coefficient of the model (R2adj = 0.892) confirmed that the model was significant, indicating a good degree of correlation between the actual values and the predicted values of total oligosaccharides. The coefficient estimates of the model equation, along with the corresponding F-values and p-values are presented in Table 2. The p-value is used as a tool to check the significance of each coefficient, and also indicates the interaction strength between each independent variable. A small p-value indicates a more significant coefficient [34]. It can be seen that X1, X3, X21, X22, and X23 were significant model terms. The effect of solvent concentration, extraction time and temperature for UAE on the concentration of extracted total oligosaccharides is shown in Fig. 2. The relationship between independent and dependent variables is illustrated by three-dimensional representation of the response surfaces and the two-dimensional contours generated by the model. Two variables within the experimental range are depicted in three-dimensional surface plots when the
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Fig. 2. Response surface plots (A–C) and contour plots (D–F) showing the effect of the variables on the concentration of extracted oligosaccharides by ultrasound assistance.
third variable is kept constant at zero level. From these threedimensional profiles, the interactions between any two factors can be easily observed. The shapes of the contour plots, elliptical or circular, indicate whether the interactions between the corresponding variables are significant or not [19]. An elliptical contour plot means the interactions between the variables are significant while a circular contour plot means otherwise. Ethanol concentration had a high impact on the concentration of extracted oligosaccharides. Higher amount of oligosaccharides was extracted by ethanol concentration ranging from 52% to 66% v/v, temperature range of 35–50 °C (Fig. 2A), and ultrasound time between 9 and 13 min (Fig. 2B). Increase in the oligosaccharide concentration was observed when extraction time and temperature were kept
at their middle values (Fig. 2C). From the Fig. 2A–C, maximal concentration of oligosaccharides could be obtained at optimal value between every two factors. All parameters showed significant quadratic effect; time and temperature at p < 0.05 while ethanol concentration at p < 0.005 (Table 2). Based on these results and the model equation, it was found out that the optimal combination of the independent variables was ethanol concentration of 63% v/v at 40 °C for 10 min, corresponding to the maximal concentration of extracted oligosaccharides in scallion of 7.95 ± 0.135 g/100 g FW. To compare the predicted results with the experimental ones, experimental rechecking was performed using optimal conditions. The good correlation between experimental and predicted values confirmed the adequacy of the
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response model. A chromatographic profile of oligosaccharides extracted by ultrasound assistance from scallion under optimized conditions is shown in Fig. 3. 3.3. Individual fractions of oligosaccharides yielded by ultrasound assisted extraction The concentration of individual fractions of fructo-oligosaccharides, 1-kestose (GF2), nystose (GF3) and 1F-b-fructofuranosylnystose (GF4) as well as raffinose family oligosaccharides, raffinose and stachyose, in 6 vegetables (garlic, Jerusalem artichoke, leek, scallion, spring garlic and white onion) and 4 fruits (blueberry, nectarine, raspberry and watermelon) obtained by ultrasound extraction are shown in Fig. 4. The UAE was performed under optimized conditions (63% v/v ethanol concentration, 40 °C, and
451
10 min) as obtained by response surface methodology. The optimized conditions for UAE developed for scallion were extrapolated and applied for extraction of oligosaccharides in other fruits and vegetables. As shown in Fig. 4, vegetable with statistically significant content of total FOS was scallion (6.22 ± 0.171 g/100 g FW) while fruit with the highest amount of total FOS was nectarine (1.75 ± 0.084 g/100 g FW). Individual fractions of FOS were found in all fruit and vegetable samples. In fruits, GF2 was found to be the highest in watermelon (0.53 ± 0.027 g/100 g FW), whereas in vegetables GF2 was the highest in scallion (2.85 ± 0.159 g/ 100 g FW). On the other hand, GF3 was the highest in nectarine (1.19 ± 0.057 g/100 g FW), while in vegetables, GF3 was the highest in Jerusalem artichoke (3.25 ± 0.173 g/100 g FW). There was a wide range of GF4 content in the samples, from 0.09 ± 0.003 g/100 g FW in raspberry to 1.25 ± 0.063 g/100 g FW in scallion. RFO were not
Fig. 3. HPLC profile of oligosaccharides extracted by ultrasound assistance from scallion under optimized conditions (ethanol concentration 63% v/v, 40 °C, time 10 min); F: fructose, G: glucose, S: sucrose, GF2: 1-kestose, GF3: nystose, GF4: 1F-b-fructofuranosylnystose, R: raffinose.
Fig. 4. Individual fractions of FOS and RFO in selected fruits and vegetables yielded by ultrasound assisted extraction under optimized conditions (ethanol concentration 63% v/v, 40 °C, time 10 min).
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Fig. 5. Conventional (ethanol concentration 85% v/v, 50 °C, 60 min) versus ultrasound assisted (ethanol concentration 63% v/v, 40 °C, 10 min) extraction of total oligosaccharides from selected fruits and vegetables.
detected in fruits. Of the vegetables analyzed, scallion had the highest content of RFO, 1.73 ± 0.061 g/100 g FW, mainly raffinose whilst stachyose was present only in Jerusalem artichoke (1.29 ± 0.053 g/100 g FW). 3.4. Comparison of ultrasound and conventional extraction of oligosaccharides A comparison of total oligosaccharides extracted conventionally [27] and by ultrasound method is presented in Fig. 5. The results showed that ultrasound method can considerably increase oligosaccharides extraction throughput. The increased content of total oligosaccharides ranged from 2 to 4-fold. The highest increase of total oligosaccharide content was spotted in Jerusalem artichoke, from 1.96 g/100 g FW with conventional extraction to 7.17 g/ 100 g FW with UAE. This change could have resulted from the enzymatic hydrolysis of fructans, molecules with high degree of polymerization (DP) present in Jerusalem artichoke. Lingyun et al. [24] reported that some low molecular weight fragments had formed by the action of ultrasound, changing the chemical composition of extracted inulin from Jerusalem artichoke. Degradation of polysaccharides was also reported by Yang et al. [35] during their experiments with ultrasound extraction of Flammulina velutipes polysaccharides. Our results also showed high increase in the amount of total oligosaccharides extracted by UAE in spring garlic (from 1.31 to 5.53 g/100 g FW) onion (from 2.24 to 6.78 g/ 100 g FW) and leek (from 1.07 to 3.05 g/100 g FW) in comparison with conventional extraction. As previously noted by Muir et al. [36], these vegetables have longer DP length (DP 8-11). The selection of an extraction method mainly depends on the advantages and disadvantages of the processes such as extraction yield, complexity, production cost, environmental friendliness and safety [37]. According to the results of this study, beyond increase in extraction efficiency, there was a significant decrease in extraction time. Ultrasound assisted method for oligosaccharide
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