Abstract
An investigation into ultrasound-assisted extraction (UAE) was conducted for the extraction of chlorophyll from Chlorella vulgaris residue after lipid separation. The best possible combination of extraction parameters was obtained with the response surface methodology (RSM), at a three-variable, three-level experiment Box–Behnken design (BBD). The optimum extraction parameters were as follows: extraction temperature, 61.4 °C, extraction time, 78.7 min, ethanol volume, 79.4 %, at a fixed ultrasonic power of 200 W. Under the modified optimal conditions, the model predicted a total chlorophyll content of 30.1 mg/g. Verification of the optimization showed that chlorophyll extraction of 31.1 ± 1.56 mg/g was observed under the optimal conditions, which well matches with the predicted value. Under these conditions, two stage extraction could sufficiently reach the maximal chlorophyll yield (35.2 mg/g), and the extraction rate reached up to 88.9 %. The present paper provides a feasible technology route for comprehensive utilization of bioactive substances from Chlorella and microalgal biomass biorefinery.
Keywords: Chlorophyll, Chlorella vulgaris, Ultrasound-assisted extraction, Response surface methodology, Optimization
Introduction
Chlorophylls are the most common green pigments found in plants. As an integrated part of vegetable foodstuffs, chlorophylls have been a natural component of the human diet throughout history. In vivo, these pigments play a key role in photosynthesis (Schoefs 2002).
Microalgae produce of wide variety of biomaterials, one of them is chlorophyll. Most algae cultured under optimum condition were reported contained about 4 % dry weight of chlorophyll from overall cell weight (Chen and Jiang 1999). Cyanobacteria typically contain chlorophyll-a while species of green algae mostly have chlorophyll-b (Deng et al. 2008). Chlorella is a type of edible algae. It's a single-celled organism that grows in water and has a high nutritional value. Two species are typically grown for human consumption: Chlorella vulgaris and Chlorella pyrenoidosa. Chlorella is over 50 % protein (dry weight) and contains a spectrum of fatty acids, carbohydrates, vitamins, amino acids and trace minerals (Chen and Jiang 1999). It also contains high amounts of chlorophyll. The high chlorophyll content of chlorella is credited with giving the algae many of its beneficial properties (Nakanishi 2001).
Chlorophyll provides a chelating agent activity which can be used in ointment, treatment for pharmaceutical benefits especially liver recovery and ulcer treatment. Besides that, it repairs cells, increases haemoglobin in blood and faster the cell growth (Zheng et al. 2006). Chlorophyll has also been investigated as source of pigments in cosmetics. Furthermore, in food industry, chlorophyll is used as natural pigment ingredient in processed foods (Humphrey 2004). Because of its strong green pigment and consumers demand for natural foods, chlorophyll is gaining importance as a food additive.
However, to the best of our knowledge, there is limited literature on efficient extraction of chlorophyll from microalgae. In order to seek more environmentally friendly methods, decrease the solvent consumption, shorten the extraction time, and increase the extraction yield, various novel extraction techniques have been developed for the extraction of nutraceuticals from plants, including ultrasound-assisted extraction (UAE), supercritical fluid extraction (SFE), and microwave-assisted extraction (MAE) (Wang and Weller 2006). Among these, UAE is an inexpensive, simple and efficient alternative to conventional extraction techniques. UAE has been employed as an efficient technique for plant pigments, phenolics and antioxidants extraction (Tiwari et al. 2009; Annegowda et al. 2011), as well as treatments on texture of chickpea (Yildirim et al. 2011). UAE was also adopted to extract carotenoids, chlorophyll a and lipids from microalgae, such as Dunaliella salina, Botryococcus sp., Chlorella vulgaris and Scenedesmus sp. (Macías-Sánchez et al. 2009; Lee et al. 2010). The enhancement in extraction obtained by using ultrasound is mainly attributed to the effects of acoustic cavitations produced in the solvent by the passage of an ultrasonic wave. Ultrasound also exerts a mechanical effect, allowing greater penetration of solvent into the sample matrix, increasing the contact surface area between solid and liquid phase (Wang et al. 2008).
Response surface methodology (RSM), an experimental strategy for seeking the optimum conditions for a multivariable system, is a much more efficient technique for optimization. This method had been successfully applied in the optimization of fermentation processes (Li et al. 2007; Cui et al. 2006; Gangadharan et al. 2008), enzymatic hydrolysis (Kunamneni and Singh 2005; Nilsang et al. 2005), synthesis parameters for polymers (Shieh and Lai 2000), and food processing operations (Huang et al. 2008; Liu et al. 2009).
The main objective of this study was to apply statistical methods to optimize the UAE parameters of chlorophylls from green algae Chlorella vulgaris residue after lipid separation using solvent extraction for microalgal biomass biorefinery. In this paper, the optimum parameters including UAE temperature, time and ethanol volume, were obtained by RSM in order to determine an optimal set of operational conditions. The Box–Behnken design (BBD) was employed to evaluate the coefficients in a quadratic mathematical model. We hope the investigation provides a feasible way to production of biofuel low costly through biorefinery of active ingredients in microalgae, especially the proteins, carbohydrates, natural pigment and other nutrients.
Materials and methods
Algae material and chemicals
Dried green algae (C. vulgaris) sample was obtained from Qian Xuesen Deserticulture Center Laboratory (Gansu, China). The sample were sealed in polyethylene bags and stored at −20 °C until ready for sampling. All chemicals and solvents were of the analytically pure and obtained from Sinopharm Chemical Reagent Co. Ltd. (Shanghai, China).
Lipid separation and UAE
Dried alga samples were finely mechanical ground 20 min for homogenization and powder process in a laboratory mill (Jiangsu, China) and extracted with n-hexane for lipid separation at darkness, room temperature and agitation until the solvent did not show any colouration. Then the extract was separated from the pellet and recovered by centrifugation at 5000 × g for 10 min (Shanghai, China). The supernatant liquid was evaporated on a rotary evaporator (Tokyo, Japan) and the alga lipid was recovered, and the pellet dried at 50 °C as the chlorophyll extraction samples.
100 mg of homogenized dry sample was put in a sealed vessel, which attached to a reflux condenser, and extracted (extraction conditions varied depending on the particular experiment) in a conventional water bath with magnetic agitation or in an ultrasonic extractor (KQ 250DE, 40.0 kHz, 250 W, Jiangsu, China) at a fixed ultrasonic power of 200 W. An in-water pipe was added to the opposite of out-water pipe in the bath, and the flux ratio between in-water and out-water was regulated to keep solution temperature stable in the test. The mixture was centrifuged after extraction and the supernatant used for chlorophyll determination.
Chlorophyll content determination
Absorption measurements of chlorophyll were made on a Hitachi U-1800 spectrophotometer. The modified equation proposed by Wellburn (1994) was used for the determination of chlorophyll concentration in the samples of C. vulgaris. The absorbance was recorded at 649 and 665 nm simultaneously in order to determine chlorophyll a (Ca) and b (Cb) contents when methanol and ethanol as extraction solvent. For acetone extract, the absorbance was recorded at 645 and 663 nm. The total chlorophyll content equal to sum of Ca and Cb, and the chlorophyll content was expressed as mg/g dry weight.
Experiment design and statistical analysis
Selection of extraction solvent
Different concentrations (anhydrous solvent and 80 % organic solvent +20 % water) of methanol, ethanol and acetone were applied for choice of solvent suitable for C. vulgaris chlorophyll extraction. The experiments were carried out at conventional agitation leaching (50 °C, 30 min, 200 rpm and the solvent: sample ratio of 1:5 (ml:mg) ).
Selection of extraction method
Comparison of conventional and UAE of chlorophyll from C. vulgaris residue was investigated for selection of an efficient extraction method. The conventional agitation extraction was carried out at 50 °C, 30 min, 200 rpm and the solvent: sample ratio of 1:5 (ml:mg). UAE was carried out at 50 °C, 30 min, 200 rpm, solvent: sample ratio of 1:5 (ml:mg), ultrasonic power of 200 W. The selected solvent (ethanol) was used in both extraction methods.
Identifying the significant variables using orthogonal experimental design (OED)
The present study was aimed at screening of the important factors with respect to their main effects by OED. Table 1 illustrated the experimental design with four factors as well as the variables. Table 2 displayed the OED matrix and results for evaluating factors influencing chlorophyll extraction content from C. vulgaris residue.
Table 1.
The variables levels of OED for UAE of total chlorophyll from C. vulgaris residue
| Factor Levels | x 1/Temperature ( °C ) | x 2/Ethanol volume ( % ) | x 3/S-Lr ( mg: ml ) | x 4/Time ( min ) |
|---|---|---|---|---|
| −1 | 50 | 70 | 25 : 10 | 30 |
| 0 | 60 | 80 | 50 : 10 | 60 |
| 1 | 70 | 90 | 100 : 10 | 90 |
OED orthogonal experimental design; UAE ultrasound-assisted extraction; S-Lr Solid–liquid ratio
Table 2.
OED matrix for evaluating factors influencing UAE of total chlorophyll from C. vulgaris residue
| Trials | x 1(Temperature) | x 2(Ethanol volume) | x 3(S-Lr) | x 4(Time) | TCC (mg/g) a |
|---|---|---|---|---|---|
| 1 | 1 (50 °C) | 1 (70 %) | 1 (25:10) | 1 (30 min) | 16.1 ± 0.21 |
| 2 | 1 (50 °C) | 2 (80 %) | 2 (50:10) | 2 (60 min) | 19.6 ± 0.44 |
| 3 | 1 (50 °C) | 3 (90 %) | 3 (100:10) | 3 (90 min) | 17.5 ± 0.31 |
| 4 | 2 (60 °C) | 1 (70 %) | 2 (50:10) | 3 (90 min) | 24.7 ± 0.14 |
| 5 | 2 (60 °C) | 2 (80 %) | 3 (100:10) | 1 (30 min) | 21.5 ± 0.29 |
| 6 | 2 (60 °C) | 3 (90 %) | 1 (25:10) | 2 (60 min) | 20.3 ± 0.34 |
| 7 | 3 (70 °C) | 1 (70 %) | 3 (100:10) | 2 (60 min) | 25.6 ± 0.26 |
| 8 | 3 (70 °C) | 2 (80 %) | 1 (25:10) | 3 (90 min) | 29.1 ± 0.43 |
| 9 | 3 (70 °C) | 3 (90 %) | 2 (50:10) | 1 (30 min) | 21.6 ± 0.27 |
| Mean value 1 | 17.713 | 22.140 | 21.823 | 19.740 | |
| Mean value 2 | 22.167 | 23.387 | 21.980 | 21.817 | |
| Mean value 3 | 25.447 | 19.800 | 21.523 | 23.770 | |
| Range | 7.734 | 3.587 | 0.457 | 4.030 |
OED orthogonal experimental design; UAE: ultrasound-assisted extraction; S-Lr Solid–liquid ratio; TCC Total chlorophyll content.
a n = 4
Box–Behnken design (BBD)
The levels of the significant parameters and the interaction effects between various extraction parameters which influence the chlorophyll content significantly were analysed and optimized by Box–Behnken methodology (Box and Behnkin 1960). In this study, the experiment design contains 17 trials and the values of the responses were the mean of triplications. The experimental design used for the study is shown in Tables 3 and 4. The second-order polynomial coefficients were calculated and analyzed using the “Design Expert” software (Version 7.0, Stat-Ease Inc., Minneapolis, USA) statistical package.
Table 3.
The variables and levels of BBD for UAE of total chlorophyll from C. vulgaris residue
| Factor Levels | X 1 / Temperature ( °C ) | X 2 / Time ( min ) | X 3 / Ethanol volume ( % ) |
|---|---|---|---|
| −1 | 50 | 30 | 70 |
| 0 | 60 | 60 | 80 |
| 1 | 70 | 90 | 90 |
BBD Box–Behnken design; UAE ultrasound-assisted extraction
Table 4.
BBD with three independent variables for UAE of total chlorophyll from C. vulgaris residue
| Run | Factor 1 | Factor 2 | Factor 3 | TCC ( mg/g ) | ||||
|---|---|---|---|---|---|---|---|---|
| X 1(°C) | Code X 1 | X 2(min) | Code X 2 | X 3(%) | Code X 3 | Actual value a | Predicted value | |
| 1 | 50 | −1 | 30 | −1 | 80 | 0 | 24.6 ± 1.86 | 24.7 |
| 2 | 70 | 1 | 30 | −1 | 80 | 0 | 26.4 ± 0.89 | 26.7 |
| 3 | 50 | −1 | 90 | 1 | 80 | 0 | 28.0 ± 1.32 | 27.8 |
| 4 | 70 | 1 | 90 | 1 | 80 | 0 | 28.6 ± 1.10 | 28.5 |
| 5 | 50 | −1 | 60 | 0 | 70 | −1 | 24.6 ± 1.34 | 24.6 |
| 6 | 70 | 1 | 60 | 0 | 70 | −1 | 26.1 ± 1.61 | 25.9 |
| 7 | 50 | −1 | 60 | 0 | 90 | 1 | 23.7 ± 1.35 | 23.9 |
| 8 | 70 | 1 | 60 | 0 | 90 | 1 | 25.4 ± 1.04 | 25.4 |
| 9 | 60 | 0 | 30 | −1 | 70 | −1 | 24.8 ± 1.35 | 24.7 |
| 10 | 60 | 0 | 90 | 1 | 70 | −1 | 27.1 ± 0.70 | 27.3 |
| 11 | 60 | 0 | 30 | −1 | 90 | 1 | 24.6 ± 1.54 | 24.3 |
| 12 | 60 | 0 | 90 | 1 | 90 | 1 | 26.5 ± 1.50 | 26.6 |
| 13 | 60 | 0 | 60 | 0 | 80 | 0 | 30.4 ± 1.02 | 29.6 |
| 14 | 60 | 0 | 60 | 0 | 80 | 0 | 29.5 ± 1.10 | 29.6 |
| 15 | 60 | 0 | 60 | 0 | 80 | 0 | 30.0 ± 1.55 | 29.6 |
| 16 | 60 | 0 | 60 | 0 | 80 | 0 | 28.8 ± 1.08 | 29.6 |
| 17 | 60 | 0 | 60 | 0 | 80 | 0 | 29.4 ± 1.21 | 29.6 |
BBD: Box–Behnken design; UAE: ultrasound-assisted extraction; TCC: Total chlorophyll content.
a n = 4
Statistical analysis
Data were expressed as mean ± standard deviation (SD, n = 4) from two independent parallel experiments for chlorophyll extraction and duplicate tests in each time. Significant differences among the means of samples were analyzed by Tukey’s test and statistical analysis of the model was performed by the analysis of variance (ANOVA).
Results and discussion
Selection of extraction solvent for C. vulgaris chlorophyll
The wavelength scanning spectrum and chlorophyll content of different extraction solvents from C. vulgaris residue were summarized in Figs. 1 and 2. We can conclude from the results that extraction of Chlorella chlorophyll with 80 % organic-aqueous solvents were better than anhydrous organic solvents (Fig. 1). In the tested solvents, the 80 % methanol-aqueous solution was the most efficient solvent for chlorophyll extraction, and obtained the maximum total chlorophyll content (16.8 mg/g). Extraction efficiencies for chlorella total chlorophyll were significantly different (p < 0.05) for all the tests except 100 % ethanol and 100 % acetone. The extraction contents of chlorophyll b were more than chlorophyll a when the methanol, ethanol and acetone as the extracting solvents (Fig. 2a).
Fig. 1.
Wavelength scanning of different chlorophyll extraction solvents from C. vulgaris residue
Fig. 2.
Effects of extraction solvents and ethanol concentrations on chlorophyll contents of C. vulgaris residue (mean ± SD, n = 4). The different letters on same style bars are significantly different (p < 0.05). a extraction solvents; b ethanol concentrations
In Jespersen and Christoffersen (1987) showed that ethanol is as efficient as methanol for extraction of chlorophyll. Kinzie (1993) used methanol: tetrahydrofitran (80: 20, v/v) as the extracting solvent and a modified dichromatic equation to calculate the concentration of chlorophyll a. Wright and Mantoura (1997) recommended methanol rather than acetone for routine marine samples. Schumann et al. (2005) observed that from the various methods tested for chlorophyll a extraction from green microalgal, isolates dimethyl formamide (DMF) gave higher concentrations than did acetone in almost all treatments. While, Wasmund et al. (2006) suggested that the chlorophyll extraction efficiency of the various solvents seems to depend on other factors, such as the taxonomic composition of the algal community. However, taking into account the safety of solvent in food additives and cost control, ethanol was the best green solvent for C. vulgaris chlorophyll extraction as the raw material for further production of sodium salt chlorophyllin, which was then used throughout.
The effects of ethanol volume on C. vulgaris total chlorophyll content are significantly from 70 % to 100 % (Fig. 2b), as well as the chlorophyll a and b. The extraction contents of chlorophyll b were more than the chlorophyll a in the all experimental groups. The maximum total chlorophyll content (14.2 mg/g), chlorophyll a (4.76 mg/g) and b (9.48 mg/g) were obtained at the 80 % ethanol concentration. Meanwhile, anhydrous ethanol reduced the extraction of total chlorophyll (8.61 mg/g). The differences between 80 % and 100 % ethanol volume were significant when examined by single factor ANOVA analysis of total recovery (p < 0.05). This behaviour can be attributed to the fact that chlorophyll is heterogenically bound to other compounds in the chloroplast and at least two or even three fractions of chlorophyll exist in the chloroplast. Therefore, the different polarities of organic solvent and water lead to the extraction of different types of chlorophyll and this gives rise to variations in the extraction yield of this substance (Öquist and Samuelsson 1980; Macías-Sánchez et al. 2009). Besides, the relative polarity and the increase in effective swelling of the algae by water, which helped increase the surface area for solute–solvent contact (Hemwimol et al. 2006). Furthermore, the mixture of water and organic solvent decrease the solution viscosity and the resistance of liquid mass transfer. Therefore, suitable water content in extracting solvent was more conducive to extraction of chlorophyll from the dried algae sample.
Selection of extraction method for C. vulgaris chlorophyll
The extraction results indicated that the total chlorophyll extraction content under UAE (13.2 mg/g) higher than conventional cheating (8.32 mg/g), a remarkable increase (59.0 %) of the chlorophyll yield and highly significant difference (p < 0.01) were observed. UAE significantly improved the extraction yield. Since ultrasound could accelerate swelling and hydration and caused an enlargement in the pores of the plant cell walls, it resulted in a better mass transfer of solute constituents from the plant materials to solvent. The disruption of plant cells by microjet after the cavitation bubble collapsed could increase the rate of solvent penetration into plant tissue (Toma et al. 2001). Therefore, UAE is an efficient technique for the extraction of chlorophyll from algae.
Optimization of C. vulgaris chlorophyll UAE conditions using OED
The UAE conditions for C. vulgaris chlorophyll were optimized by orthogonal experiments (L34) based on our preliminary single factor experiments (temperature, ethanol volume, ratios of the solvent/sample and time). The results from the Table 2 indicated that the chlorophyll yield improved with the increase of extraction temperature from 50 to 70 °C, and time from 30 to 90 min. The effects of ethanol volume and solid–liquid ratio on chlorophyll yield were different with the temperature and time. The highest chlorophyll yields were obtained at 80 % ethanol volume and 50:10 (mg: ml). The ANOVA for orthogonal experimental results for C. vulgaris total chlorophyll are listed in Table 5. We can conclude from the results that the effects of extraction temperature (x1, p < 0.01), ethanol volume (x2, p < 0.05) and time (x4, p < 0.05) on the total chlorophyll content were significant. But the affect of solid–liquid ratio (x3) was not significant. Thus, the effect of solid–liquid ratio (x3) was not considered and optimized in the further RSM experiment.
Table 5.
ANOVA for orthogonal experimental (L34) results for UAE of total chlorophyll from C. vulgaris residue
| Factors | Statistics | ||||
|---|---|---|---|---|---|
| SS | DF | MS | F-Value | Significance | |
| x 1 / Temperature | 90.34 | 2 | 45.17 | 277.41 | ** a |
| x 2 / Ethanol volume | 19.89 | 2 | 9.94 | 61.07 | * b |
| x 3 / S-Lr | 0.33 | 2 | 0.16 | 1.00 | |
| x 4 / Time | 24.34 | 2 | 12.17 | 74.75 | * b |
ANOVA Analysis of variance; UAE ultrasound-assisted extraction; S-Lr Solid–liquid ratio
SS Sum of squares; DF Degree of freedom; MS Mean square
a Significant at p < 0.01, b Significant at p < 0.05
Optimization of C. vulgaris chlorophyll UAE conditions using BBD
Analysis of Box–Behnken experiment
The significant factors obtained from the orthogonal experiments were further optimized by using the RSM in order to establish the mathematical model and equation for UAE of C. vulgaris chlorophyll. The optimal level of the key factors (temperature, time and ethanol volume) and the effect of their interactions on total chlorophyll content were further explored by the BBD. By applying multiple regression analysis on the experimental data, the following second-order polynomial equation (equation in terms of coded factors) was established to explain the UAE of C. vulgaris chlorophyll:
 |
where Y is the predicted total chlorophyll content; X1, X2 and X3 are the coded values of temperature, time and ethanol volume, respectively.
Table 6 shows the ANOVA for response surface quadratic model. The model F-value of 33.56 implies the model is significant. There is only a 0.01 % chance that a "Model F-value" this large could occur due to noise. Values of "Prob > F" less than 0.05 indicate model terms are significant. The p-values are used as a tool to check significance of each variables, which also indicate the interaction strength between each independent variable. The smaller the p-values, the bigger the significance of the corresponding variables. p-values in this study less than 0.05 indicate model terms are significant. In this case X1, X2, X21, X22, X23 are significant model terms. In this case values greater than 0.10 indicate the model terms are not significant. The "Lack of Fit F-value" of 0.36 implies the lack of fit is not significant relative to the pure error. There is a 78.53 % chance that a "Lack of Fit F-value" this large could occur due to noise. Non-significant lack of fit is good.
Table 6.
ANOVA for response surface quadratic model
| Source | SS | DF | MS | F-Value | p-value (Prob > F) | |
|---|---|---|---|---|---|---|
| Model | 74.54 | 9 | 8.28 | 33.56 | < 0.0001 | significant |
| X 1-Temperature | 3.86 | 1 | 3.86 | 15.66 | 0.0055 | |
| X 2-Time | 12.03 | 1 | 12.03 | 48.74 | 0.0002 | |
| X 3-Ethanol volume | 0.60 | 1 | 0.60 | 2.43 | 0.1631 | |
| X 1 X 2 | 0.40 | 1 | 0.40 | 1.63 | 0.2419 | |
| X 1 X 3 | 0.01 | 1 | 0.01 | 0.02 | 0.8843 | |
| X 2 X 3 | 0.04 | 1 | 0.04 | 0.15 | 0.7135 | |
| X 21 | 13.03 | 1 | 13.03 | 52.79 | 0.0002 | |
| X 22 | 3.81 | 1 | 3.81 | 15.45 | 0.0057 | |
| X 23 | 35.94 | 1 | 35.94 | 145.62 | < 0.0001 | |
| Residual | 1.73 | 7 | 0.25 | |||
| Lack of Fit | 0.37 | 3 | 0.12 | 0.36 | 0.7853 | not significant |
| Pure Error | 1.36 | 4 | 0.34 | |||
ANOVA Analysis of variance; SS Sum of squares; DF Degree of freedom; MS Mean square
Effects of temperature, duration and ethanol volume on chlorophyll extraction
The response–surface graphs were obtained using the experimental design shown in Fig. 3. Figure 3a shows the effect of the extraction temperature and time on the total chlorophyll content at a fixed ethanol volume (80 %, v/v). At a definite extraction temperature, the chlorophyll yield increased rapidly with the increase of the extraction time, and nearly reached a peak at the extraction time about 78.7 min. However, the extraction temperature showed a quadratic effect on the response (chlorophyll yield). The maximum chlorophyll yield was obtained at 61.4 °C, followed by a decline with the further increase of the extraction temperature.
Fig. 3.
Response surface plot of the combined effects of UAE temperature, time and ethanol volume on total chlorophyll content of C. vulgaris residue
Figure 3b shows the effect of the extraction temperature and the ethanol volume on the chlorophyll yield at a fixed extraction time of 60 min. The results indicated that the quadratic effect of the ethanol volume was striking, and the highest value at 79.4 %. The quadratic effect of the extraction temperature was significant, and the chlorophyll yield reached the highest value also at 61.4 °C.
The interaction between the extraction time and ethanol volume is shown in Fig. 3c at the fixed extraction temperature of 60 °C. The chlorophyll yield increased with the extraction time and the ethanol volume increasing, and the maximum response value was obtained at 78.7 min and 79.4 %, respectively. Those results may attribute to the oxidation and degradation of chlorophyll under higher temperature and longer duration time (Schumann et al 2005).
Validation of the model
According to the results of the statistical design, the optimized parameters for chlorophyll UAE from C. vulgaris residue after lipid separation were prepared as follows: temperature 61.4 °C, time 78.7 min, and ethanol volume 79.4 % (v/v). Under the above optimized conditions, the maximum chlorophyll yield of C. vulgaris was estimated as 30.1 mg/g.
A repeat UAE of chlorophyll from C. vulgaris residue under modified optimal conditions (temperature 61 °C, time 79 min, ethanol volume 79 %) was carried out for verification of the optimization, and the maximal chlorophyll content was 31.1 ± 1.56 mg/g (n = 4). The measured total amount of chlorophyll from C. vulgaris residue was 39.6 mg/g. The extraction rate of 78.5 % was achieved. This value was found to be 3.43 % more than the predicted value. This discrepancy might be due to the slight variation in experimental conditions. The excellent correlation between predicted and measured values verifies the model validation and existence of an optimal point.
Effect of extraction times on the chlorophyll yield
The effects of extraction times on the yield of chlorophyll were examined under the above modified optimal conditions. The results shown that two stage extraction produced significantly (p < 0.05) higher chlorophyll yield (35.2 ± 1.83 mg/g, n = 4) than one-time extraction (31.1 ± 1.56 mg/g, n = 4). But the chlorophyll yield at three-time extraction (36.8 ± 1.06 mg/g, n = 4) did not had significant difference with two stage extraction. Hence, the optimal extracting times were fixed at two stage extraction. The extraction rate of chlorophyll was 88.9 % under the two stage extraction.
Conclusion
In this paper, RSM (BBD) was adopted to identify UAE parameters which enhanced the chlorophyll extraction from Chlorella sp. residue after lipid separation. The results suggested that UAE method is an efficient technique for the extraction of chlorophyll from microalgae, and statistical design methodology offers an efficient and feasible approach for extraction parameters optimization. The modified optimum extraction parameters from BBD were extraction temperature 61 °C, extraction time 79 min, ethanol volume 79 % at a fixed ultrasonic power of 200 W. Under these conditions, two stages extraction could sufficiently reach the maximal chlorophyll content (35.2 mg/g) and extraction rate (88.9 %). The present paper provides feasible technology route for comprehensive utilization of biologically active components from Chlorella and its biorefinery.
Acknowledgement
Financial support was provided by National Science Found for Distinguished Young Scholars of China (Grant No. 20625308) and Research Fund for Young Teachers of Northwest Normal University (Grant No. NWNU-LKQN-10-30).
Contributor Information
Weibao Kong, Phone: +86-931-7971414, FAX: +86-931-7971207, Email: kwbao@163.com.
Chungu Xia, Phone: +86-931-4968089, FAX: +86-931-4968129, Email: cgxia@lzb.ac.cn.
References
- Annegowda HV, Bhat R, Min-Tze L, Karim AA, Mansor SM (2011) Influence of sonication treatments and extraction solvents on the phenolics and antioxidants in star fruits. J Food Sci Technol. doi:10.1007/s13197-011-0435-8 [DOI] [PMC free article] [PubMed]
- Box GEP, Behnkin EW. Some new three level designs for the study of quantitative variables. Technometrics. 1960;2:455–475. doi: 10.1080/00401706.1960.10489912. [DOI] [Google Scholar]
- Chen F, Jiang Y. Biotechnology of microalgae. Beijing: Light Industry Press of China; 1999. pp. 56–58. [Google Scholar]
- Cui F, Li Y, Xu Z, Xu H, Sun K, Tao W. Optimization of the medium composition for production of mycelial biomass and exo-polymer by Grifola frondosa GF9801 using response surface methodology. Bioresource Technol. 2006;97:1209–1216. doi: 10.1016/j.biortech.2005.05.005. [DOI] [PubMed] [Google Scholar]
- Deng Z, Hu Q, Lu F, Liu G, Hu Z. Colony development and physiological characterization of the edible blue-green alga, Nostoc sphaeroides (Nostocaceae, Cyanophyta) Prog Nat Sci. 2008;18:1475–1484. doi: 10.1016/j.pnsc.2008.03.031. [DOI] [Google Scholar]
- Gangadharan D, Sivaramakrishnan S, Nampoothiri KM, Sukumaran RK, Pandey A. Response surface methodology for the optimization of alpha amylase production by Bacillus amyloliquefaciens. Bioresource Technol. 2008;99:4597–4602. doi: 10.1016/j.biortech.2007.07.028. [DOI] [PubMed] [Google Scholar]
- Hemwimol S, Pavasant P, Shotipruk A. Ultrasound-assisted extraction of anthraquinones from roots of Morinda citrifolia. Ultrason Sonochem. 2006;13:543–548. doi: 10.1016/j.ultsonch.2005.09.009. [DOI] [PubMed] [Google Scholar]
- Huang W, Li Z, Niu H, Li D, Zhang J. Optimization of operating parameters for supercritical carbon dioxide extraction of lycopene by response surface methodology. J Food Eng. 2008;89:298–302. doi: 10.1016/j.jfoodeng.2008.05.006. [DOI] [Google Scholar]
- Humphrey AM. Chlorophyll as a colour and functional ingredient. J Food Sci. 2004;69:422–425. doi: 10.1111/j.1365-2621.2004.tb10710.x. [DOI] [Google Scholar]
- Jespersen AM, Christoffersen K. Measurements of chlorophyll a from phytoplankton using ethanol as an extraction solvent. Arch Hydrobiol. 1987;109:445–454. [Google Scholar]
- Kinzie RA., III Effects of ambient levels of solar ultraviolet radiation on zooxanthellae and photosynthesis of the reef coral Montipora verrucosa. Mar Biol. 1993;116:319–327. doi: 10.1007/BF00350022. [DOI] [Google Scholar]
- Kunamneni A, Singh S. Response surface optimization of enzymatic hydrolysis of maize starch for higher glucose production. Biochem Eng J. 2005;27:179–190. doi: 10.1016/j.bej.2005.08.027. [DOI] [Google Scholar]
- Lee JY, Yoo C, Jun SY, Ahn CY, Oh HM. Comparison of several methods for effective lipid extraction from microalgae. Bioresource Technol. 2010;101:S75–S77. doi: 10.1016/j.biortech.2009.03.058. [DOI] [PubMed] [Google Scholar]
- Li Y, Cui FJ, Liu ZQ, Xu YY, Zhao H. Improvement of xylanase production by Penicillium oxalicum ZH-30 using response surface methodology. Enzyme Microb Technol. 2007;40:1381–1388. doi: 10.1016/j.enzmictec.2006.10.015. [DOI] [Google Scholar]
- Liu S, Yang F, Zhang C, Ji H, Hong P, Deng C. Optimization of process parameters for supercritical carbon dioxide extraction of Passiflora seed oil by response surface methodology. J Supercrit Fluid. 2009;48:9–14. doi: 10.1016/j.supflu.2008.09.013. [DOI] [Google Scholar]
- Macías-Sánchez MD, Mantell C, Rodríguez M, Martínez de la Ossa E, Lubián LM, Montero O. Comparison of supercritical fluid and ultrasound-assisted extraction of carotenoids and chlorophyll a from Dunaliella salina. Talanta. 2009;77:948–952. doi: 10.1016/j.talanta.2008.07.032. [DOI] [PubMed] [Google Scholar]
- Nakanishi K (2001) Chlorophyll-rich and salt-resistant chlorella. European Patent: Publication No. EP 1142985, 10 Oct 2001
- Nilsang S, Lertsiri S, Suphantharika M, Assavanig A. Optimization of enzymatic hydrolysis of fish soluble concentrate by commercial proteases. J Food Eng. 2005;70:571–578. doi: 10.1016/j.jfoodeng.2004.10.011. [DOI] [Google Scholar]
- Öquist G, Samuelsson G. Sequential extraction of chlorophyll from chlorophyll-protein complexes in lyophilized pea thylakoids with solvents of different polarity. Physiol Plantarum. 1980;50:57–62. doi: 10.1111/j.1399-3054.1980.tb02684.x. [DOI] [Google Scholar]
- Schoefs B. Chlorophyll and carotenoid analysis in food products. Properties of the pigments and methods of analysis. Trends Food Sci Tech. 2002;13:361–371. doi: 10.1016/S0924-2244(02)00182-6. [DOI] [Google Scholar]
- Schumann R, Häubner N, Klausch S, Karsten U. Chlorophyll extraction methods for the quantification of green microalgae colonizing building facades. Int Biodeter Biodegr. 2005;55:213–222. doi: 10.1016/j.ibiod.2004.12.002. [DOI] [Google Scholar]
- Shieh CJ, Lai YF. Application of response surface methodology to the study of methyl glucoside polyester synthesis parameters in a solvent-free system. J Agric Food Chem. 2000;48:1124–1128. doi: 10.1021/jf990460f. [DOI] [PubMed] [Google Scholar]
- Tiwari BK, Donnell CP, Cullen PJ. Effect of sonication on retention of anthocyanins in blackberry juice. J Food Eng. 2009;93:166–171. doi: 10.1016/j.jfoodeng.2009.01.027. [DOI] [Google Scholar]
- Toma M, Vinatoru M, Paniwnyk L, Mason TJ. Investigation of the effects of ultrasound on vegetal tissues during solvent extraction. Ultrasoun Sonochem. 2001;8:137–142. doi: 10.1016/S1350-4177(00)00033-X. [DOI] [PubMed] [Google Scholar]
- Wang L, Weller CL. Recent advances in extraction of nutraceuticals from plants. Trends Food Sci Tech. 2006;17:300–312. doi: 10.1016/j.tifs.2005.12.004. [DOI] [Google Scholar]
- Wang J, Sun B, Cao Y, Tian Y, Li X. Optimisation of ultrasound-assisted extraction of phenolic compounds from wheat bran. Food Chem. 2008;106:804–810. doi: 10.1016/j.foodchem.2007.06.062. [DOI] [Google Scholar]
- Wasmund N, Topp I, Schories D. Optimising the storage and extraction of chlorophyll samples. Oceanologia. 2006;48:125–144. [Google Scholar]
- Wellburn AR. The spectral determination of chlorophylls a and b, as well as total carotenoids, using various solvents with spectrophotometers of different resolution. J Plant Physiol. 1994;144:307–313. doi: 10.1016/S0176-1617(11)81192-2. [DOI] [Google Scholar]
- Wright SW, Mantoura RFC. Guidelines for collection and pigment analysis of field samples. In: Jeffrey SW, Mantoura RFC, Wright SW, editors. Phytoplankton pigments in oceanography: guidelines to modern methods. Paris: UNESCO Publ; 1997. pp. 429–445. [Google Scholar]
- Yildirim A, Öner MD, Bayram M (2011) Effect of soaking and ultrasound treatments on texture of chickpea. J Food Sci Technol. doi:10.1007/s13197-011-0362-8 [DOI] [PMC free article] [PubMed]
- Zheng GD, Ouyang W, Yan M, Du FL. The pharmacological research progress of chlorophyll and its derivatives. Central South Phamacy (in Chinese) 2006;4:146–148. [Google Scholar]