Abstract
Chinese jujube is a delicious fruit with high antioxidant nutrients. The fruit peel, however, is always discarded due to its indigestibility. In the current study, the jujube peels were collected for red pigment extraction. Six extraction-related parameters (ethanol concentration, solid-liquid ratio, material granularity, enzyme concentration, enzymolysis time, and pH) were optimized for jujube peel pigment extraction using Plackett–Burman and Box–Behnken designs. When the fruit peels were treated with 1.18% cellulase and 73% ethanol at pH 3.15, optimization enhanced the pigment extraction efficiency by 29.7% compared with the control. Ultra-high performance liquid chromatography (UHPLC) assay revealed that delphinidin 3-O-galactoside and cyanidin 3-O-rutinoside chloride were the major components of the jujube pigment extracts. Additionally, the red pigment extracts exhibited high free radical scavenging capacity and strong Fe3+ reducing power. Finally, it also provides us a simple new method for efficient extraction of natural antioxidants from discarded jujube peels.
1 Introduction
Chinese jujube is the fruit of the Ziziphus jujuba Mill of the Rhamnaceae family. It is a delicious and nutritious fruit with high nutritional compounds and potent medicinal and health benefits [1,2]. Jujube fruits are known as “natural vitamin pills.” According to a recent study, jujube fruit has a high concentration of proteins, sugars, organic acids, fats, 18 types of amino acids required by the human body, as well as iron, zinc, phosphorus, calcium, and selenium. Jujube fruits, peels, seed kernels, leaves, wood hearts, and branches can be used in medicine [3,4] to treat anemia, lung deficiency, cough, neurasthenia, sexual purpura, and other curative effects [5–8], and jujube is a nutritional tonic that has been valued by the medical community both nationally and internationally.
Jujube peel contains red pigment and is an ideal source of natural pigment. It has a high pigment content, excellent water solubility, is a clear and transparent solution, has a bright color, is natural and safe, has good nutritional value, and has pharmacological actions. It also offers significant application potential in cosmetics, food, dyes, and beverages [9]. Although processed jujube products are becoming increasingly abundant, jujube dates are often discarded as processing by-products, causing environmental pollution. The extraction of red pigment from jujube as a raw material not only involves the comprehensive utilization of red dates but also transforms waste into a valuable resource, protects the environment, and has economic benefits [10].
Response surface methodology (RSM) is primarily employed in multi-factor biochemical processes. This methodology quickly identifies the primary components, approximating the maximum response interval, fitting mathematical model equations, identifying the optimal conditions, and evaluating the results. Fewer trials and shorter cycles are the benefits of the RSM [11]. RSM has been effectively employed in various domains of scientific research as computational methods have improved, and microcomputer applications have grown in popularity.
Various parameters in the extraction process of red pigment from jujube peel were analyzed in the current study, and optimal conditions for red pigment extraction were identified. The Plackett–Burman (PB) experimental design screened the main factors affecting the extraction of red pigment from jujube peel. The Box–Behnken center combination experiment and Design–Expert analysis software were then used to optimize the factors that influenced the quantity of red pigment extracted from jujube peel. The optimal combination of extraction parameters and the response equation of red pigment from jujube peel was also established. Ultra-high performance liquid chromatography-mass spectroscopy (UHPLC-MS) identified the chemical constituents of red pigment from jujube peel, and the antioxidant activity of the red pigment was assessed, providing a theoretical basis for the functional study of jujube.
2 Materials and methods
The matured jujube fruits (Ziziphus jujuba Mill, cv. “xinjiangdazao”) were harvested from the jujube garden of the Luoyang Normal University, Henan, China. After harvesting, these jujube fruits were stored at −20°C until use.
2.1 Pigment extraction from the jujube fruit peels
2.1.1 Collection of the jujube fruit peels
The jujube fruits were soaked in cold water for 12 h and then drained. The fruits were then placed in boiling water for 5 min, removed, and immediately placed in cold water. Next the peels were removed and dried at 40°C in an oven for 24 h. The dried peels were crushed using a pulverizer and then sieved through a 40 mesh screen.
2.1.2 Preparation of crude pigment extracts
The jujube powder was added to 70% ethanol and subjected to enzymatic hydrolysis (cellulase: enzyme activity ≥0.3 U/mg from Aspergillus niger; α-amylase: enzyme activity 500–1,500 U/mg from Bacillus; and pectinase: enzyme activity 40 U/mg from Aspergillus niger) (1.0% enzyme, 50°C enzymatic hydrolysis temperature, 1 h enzymatic hydrolysis time, and enzymatic hydrolysis at pH 4.5) in a 80°C water bath for 10 min. The inactivated enzyme was filtered, centrifuged, and the supernatant was evaporated and concentrated to obtain the crude red pigment.
2.1.3 Determination of maximum absorbance in red pigment extracts
Based on our preliminary study findings [12], greater absorbance of the crude extracts indicated a higher concentration of red pigment under certain circumstances. Full wavelength scanning was carried out to determine the wavelength with the maximum absorbance. The scanning wavelength range was between 200 and 800 nm, and the maximum absorbance was obtained at a wavelength of 280 nm (Figure S1). Here the absorbance measured at 280 nm was considered to evaluate the concentration of the red pigment extracts.
2.1.4 Optimization of the extraction factors
The effects of ethanol concentration (60, 65, 70, 75, 80, 85, and 90%), pulverization degree (20, 40, 60, and 80 mesh), material to liquid ratio (1:10, 1:20, 1:30, 1:40, and 1:50), enzyme types (cellulase, pectinase, α-amylase, and enzyme complex), enzyme concentration (0.4, 0.6, 0.8, 1.0, and 1.2%), enzymatic hydrolysis time (1, 2, and 3 h), and pH (3.5, 4.5, 5.5, 6.5, 7.5, and 8.5) on the extraction efficiency of red pigment from jujube peel were evaluated to obtain the optimal extraction conditions.
The PB experimental design was used in further studies as it is a near-saturated 2-level experimental design. Based on the principle of the non-completely balanced block, it estimates the main effect of the factor with the least number of experiments and rapidly and effectively selects the most important factors from several investigation factors for further research [13]. Based on the results of the single-factor test, according to the PB experimental design principle, the important parameters that exhibited a significant influence on the number of jujube extracts were then screened. The type of fermentation culture enzymes, ethanol content, solid–liquid ratio (w/v), pulverization degree, enzymatic hydrolysis pH, and the amount of enzyme added were selected for investigation. Two levels of each factor mentioned earlier were coupled with a parallel experiment. The experiment was performed in triplicate to evaluate the amount of jujube pigment extracts as the response value.
As for the t-test, Design-Expert 8 (Stat-Ease, Inc., Minneapolis, MN, USA) software was used to determine the effect of each factor on the pigment extraction efficiency. According to the confidence level in the factors, significant factors were selected for further investigation. When the important parameters were determined, the Box–Behnken center combination experiment was applied to design the three-factor and three-level experiments. Each factor was designed as the horizontal center point, the lowest and the highest level of the factor, and the number of jujube extracts served as the response value. The quadratic equation was predicted according to the Box–Behnken test design and input variables. The Design-Expert 8 software response surface analysis program was adopted to analyze the response values of 17 groups of experiments. Following the regression equation fitting, variance analysis of the regression equation and the model credibility analysis was performed to verify the model’s validity.
2.2 Pigment component identification
The main components of the jujube pigment extract were assayed with HPLC (HPLC1290, Agilent Technology Co., Ltd) equipped with the Eclipse × DB-C18 column (4.6 mm × 250 mm), with a pore size of 5 μm, and a temperature of 30°C. The injection volume was 20 μL, and the UV detector wavelength was 280 nm. The mobile phase was composed of buffer A (10% formic acid aqueous solution) and buffer B (mixed solution of 100% methanol, 100% acetonitrile, and 0.1% formic acid water [40:40:20]). The ratio of buffer A to buffer B was 67:33. The flow rate was set to 0.8 mL/min. The standard solutions are composed of pelarin-3-5-glucoside (>95% purity), delphinidin-3-O-galactoside (>96% purity), delphinidin-3-O-rutinoside (>96% purity), cyanidin-3-O-galactoside (>97% purity), cyanidin-3-O-glucoside (>92% purity), cyanidin-3-O-rutinoside (>98% purity), petunia, and pelarin-3-O-glucoside (>96% purity) (Sigma-Aldrich, St. Louis, MO, USA). The limits of detection ranged from 0.02 to 0.6 ng/mL, and the lower limits of quantification were set to 0.1–2.0 ng/mL, as described previously in UHPLC 1290 [14].
To analyze the sample extracts, an Orbitrap Mass Spectrometer (Q Exactive, Thermo Fisher Scientific, Waltham, MA, USA) was equipped with a heat electrospray ionization (HESI) source. The data were collected in the Q Exactive software using an orbitrap mass analyzer with a mass resolution of 70,000 at 400 m/z. During each duty cycle, the 20 most energetic precursor ions from a survey scan were picked for MS/MS and identified in an orbitrap analyzer with a mass resolution of 35,000 at 400 m/z. The HESI probe and transfer capillary temperature were kept at 350°C, and the automatic gain control (AGC) was set to 1.0 × 106. The maximum injection time was 100 ms. All tandem mass spectra were generated by the higher energy collision dissociation method with normalized collision energy of 20–80 eV, AGC target of 2.0 × 105, maximum injection time of 100 ms, fill ratio of 1.0%, isotope exclusion “on,” and a dynamic exclusion of 5.0 s. The specific ion peaks were examined using MS/MS using inclusion and exclusion indexes, and the dynamic exclusion was set for 20 s.
2.3 Pigment extracts antioxidant activity assay
Three methods (hydroxyl radical scavenging ability, superoxide anion free-radical scavenging ability, and Fe3+ reducing power) were adopted to evaluate the antioxidant activities of the jujube pigment extracts. These parameters were measured with the UV-visible spectrophotometer (Shanghai Yuan Analysis Instrument Co., Ltd).
The hydroxyl radical-scavenging activity of red pigment from jujube peels was determined by the Fenton method [15], and the absorbance of the sample was measured at 510 nm. The reaction mixture contained 2.0 mL of FeSO4 (6 mM) and 2.0 mL of the sample (0.5–2 mg/mL). Then, 2.0 mL of H2O2 (6 mM) was blended and incubated for 10 min at room temperature. After which, 2.0 mL of salicylic acid (6 mM) was added, and the mixture was incubated for another 30 min. The hydroxyl radical was detected by monitoring the absorbance at 510 nm. Blueberries and ascorbic acid were used as positive control; the sample was substituted with ascorbic acid. The percentage of the scavenging effect was calculated. The extract concentration that provided 50% inhibition (EC 50) was calculated from the hydroxyl radical scavenging activity percentage graph against extract concentration.
The superoxide anion-free radical scavenging activity of the red pigment extracts was determined by the pyrogallol autoxidation method [16], albeit with some modifications. Briefly, 2 mL of the DPPH solution (2 × 10−4 mol/L in dehydrated alcohol) was added to 2 mL of various concentrations of the sample solutions. The mixture was then shaken vigorously and allowed to stand for 30 min in the dark. The absorbance was measured at 325 nm. The extract concentration that provided 50% inhibition (EC50) was calculated from the graph of superoxide anion-free radical scavenging activity percentage against the extract concentration. Blueberries and ascorbic acid served as a positive control.
The Fe3+-reducing power of the red pigment extracted from the jujube peels was determined by the potassium ferricyanide reduction method [17]. The extract concentration that provided 0.5 absorbance (EC50) was calculated from the graph of absorbance at 700 nm against the extract concentration. Blueberries and ascorbic acid served as the positive control.
2.4 Data analysis
The experiments were conducted in a completely randomized design. Three replicates were performed for each treatment. All data were analyzed using Duncan’s multiple range test (P < 0.05) in the SPSS 13.0 software (IBM Corp., Armonk, NY, USA).
3 Results and analysis
3.1 Effect of ethanol concentration on pigment extraction from jujube peel
Five grams of 40 mesh raw materials were weighed, 150 mL of 60, 65, 70, 75, 80, 85, or 90% ethanol was added, absorbance was measured at 280 nm, and the optimal ethanol concentration was determined. Figure 1a depicts the results.
Effects of extraction factors on pigment yield. Effects of ethanol concentration (a), solid-liquid ratio (b), material granularity (particle diameter of material) (c), and enzyme types (d) on the extraction efficiency of red pigment from matured jujube fruits (n = 3; error bar, a standard deviation of the sample, SD; OD value is the optical density value measured at 280 nm; 20 mesh, 1.6 mm; 40 mesh, 0.45 mm; 60 mesh, 0.28 mm; and 80 mesh, 0.18 mm).
As shown in Figure 1a, the absorbance of red pigment from jujube peel rose initially and then decreased as the volume fraction of ethanol increased. When the ethanol volume fraction was 80%, the absorbance reached a maximum value of 0.625 and dropped as the volume fraction increased. This was due to the pigment solution’s concentration reduced as the ethanol volume fraction increased. The higher the solvent dose, the higher the extraction rate [18], but an excessive volume ratio will cause solvent and energy waste. Red jujube peel pigment was readily soluble in polar organic solvents such as water and ethanol. Since the water was cheap, employing water as an extractant or solvent was cost-effective. However, when the pigment was extracted with water, impurities in the fruit such as sugars, organic acids, and pectin were dissolved in the pigment solution [19]. Therefore, the ethanol volume fraction of 80% was chosen as the optimal ethanol concentration.
3.2 Effect of the material–liquid ratio on pigment extraction from jujube peel
Five grams of 40 mesh raw materials were weighed, and 50, 100, 150, 200, or 250 mL of 80% ethanol were added at a ratio of 1:10, 1:20, 1:30, 1:40, or 1:50. The absorbance was measured at a wavelength of 280 nm to determine the optimal material to liquid ratio. Figure 1b depicts the results.
The absorbance of red pigment from jujube peel reached a maximum of 0.726 when the material-liquid ratio was increased from 1:10 to 1:20, as shown in Figure 1b. The absorbance decreased continuously to 0.217 as the material-liquid ratio increased (1:30–1:50). This might be because when the material-liquid ratio increased, the amount of solution increased, increasing the driving force of mass transfer and the diffusion rate [20–22]. In addition, increasing the material-liquid ratio increased the load for evaporation and concentration in subsequent sections, and the solvent recovery increased, resulting in significant solvent consumption, which leads to increase the experimental cost. According to the above conditions, the optimum ratio of material-liquid was 1:20.
3.3 Effect of pulverization degree on pigment extraction from jujube peel
Five grams of raw materials of 20, 40, 60, and 80 mesh were weighed, and 80 mL of 80% ethanol was added. To obtain the optimal degree of pulverization, absorbance was measured at a wavelength of 280 nm. Figure 1c depicts the results.
As shown in Figure 1c, the absorbance of red pigment increased when the particle diameter of the raw material increased when less than 60 mesh was employed, and absorbance was 0.857 when the largest mesh (60) was utilized. This was because as the contact area increased, the rate of diffusion of the pigment from the jujube peel into the solvent increased, as did the rate of penetration of the solvent into the jujube peel; thus, the amount of pigment dissolved in the solvent elevated quickly. Red pigment extraction increased as the particle diameter decreased. However, if the degree of pulverization was too high, the pulverized sample’s surface area was too large, and the adsorption effect was amplified. This, in turn, affected the diffusion rate, which was not conducive to active ingredient dissolution, and the leaching of many insoluble polymers such as proteins, tannin, and sugars increased proportionally. This led to difficulties in separation and purification, and the cost of the process increased [23].
The solvent diffused and penetrated the solid cell wall during the extraction process, dissolving the effective substance. Particle reduction was a process that improved the reaction-specific surface area per unit volume of the jujube peel powder, which was favorable for solvent penetration and diffusion. However, when the particle diameter fell, the specific surface area increased, and the extraction decreased due to enhanced particle adsorption, and the particle diameter was too small to be effectively filtered [24]. Therefore, 40 mesh was selected as the optimal pulverization particle diameter.
3.4 Effect of enzyme types on pigment extraction from jujube peel
Previous studies have shown that cellulase, pectinase, and α-amylase play a very active role in dissolving cell walls and improving cellular content [25]. Various enzymes were introduced to the extraction system to evaluate their effect on the quantity of pigment extracted from jujube peel to increase the amount of red pigment extracted. Five grams of 40 mesh raw materials were weighed, and 100 mL of 80% ethanol was added plus 1.5% of cellulase, pectinase, α-amylase, or cellulose, pectinase, α-amylase, and enzyme complex (cellulose:pectinase:α-amylase = 1:1:1). The enzyme was digested for 1.5 h at 50°C and pH 4.5 before being deactivated in an 80°C water bath for 10 min. To determine the optimal enzyme, absorbance was measured at a wavelength of 280 nm. Figure 1d depicts the results.
As shown in Figure 1d, when cellulase, α-amylase, pectinase, and cellulose, pectinase, and α-amylase were added to the extraction system, the jujube peel hydrolyzed by cellulase exhibited the highest absorbance value of 1.125. The amount of red pigment extracted from jujube peel (0.726) increased by 54.9% compared with nonenzymatic hydrolysis. In contrast, the amount of red pigment extracted by enzyme complex (0.899) was lower than cellulase, indicating that enzyme hydrolysis had a good effect on the extraction of red pigment from jujube peel and that cellulase had the best extraction effect.
Cellulase refers to a group of enzymes that degrades cellulose to produce glucose. It is a synergistic multi-component enzyme system, not a monomeric enzyme. It is a complex enzyme consisting mainly of exo-β-glucanase, endo-β-glucanase, and β-glucosidase, as well as highly active xylanase acting on cellulose and cellulose-derived compounds [26–28]. It was speculated that when plant cells were treated with cellulase and cellular red pigment was released, the breakdown of the cell was increased. Cellulase was selected to be the best enzyme based on the findings of this extensive investigation.
3.5 Effect of enzyme concentration on pigment extraction
Five grams of 40 mesh raw materials were weighed, 100 mL of 80% ethanol plus 0.8, 1.0, 1.2, 1.4, or 1.6% of cellulase were added and digested for 1 h at 50°C and pH 4.5. For 10 min, the enzyme was deactivated in an 80°C water bath. The absorbance was measured at a wavelength of 280 nm. The results are shown in Figure 2a.
Effect of cellulase treatment on the pigment extraction. Effects of enzyme concentration (a), enzymolysis time (b), and enzymolysis pH (c) on the extraction of red pigment from matured jujube fruits (n = 3; error bar, a standard deviation of the sample, SD; OD value is the optical density value measured at 280 nm).
As shown in Figure 2a, the amount of red pigment extracted from jujube peel increased as the dose of cellulase increased. The absorbance of red pigment from the jujube peel reached a maximum value of 1.247 when the cellulase dose was 1.2%. The absorbance of red pigment from jujube peel gradually declined as the cellulase mass fraction rose. This might be because the reaction substrate concentration was relatively large when cellulase mass fraction was low. The combination of the two did not approach saturation at this time, and the enzymatic hydrolysis reaction rate was proportional to the enzyme mass fraction. The enzymatic hydrolysis reaction rate rose as the cellulase mass fraction increased. The enzymatic reaction efficiency was highest when the cellulase mass fraction increased, and the reaction substrate was entirely saturated by the enzyme. When it continued to increase, the rate of enzymatic hydrolysis no longer increased but did not decrease as well, probably due to the inhibition of the intermediate complex of the enzyme reaction [29,30]. Therefore, the most suitable cellulase mass fraction was 1.2%.
3.6 Effect of enzymatic hydrolysis time on pigment extraction
Five grams of 40 mesh raw materials were weighed, 80 mL of 80% ethanol and 1.2% cellulase were added and then digested for 0.5–2.5 h at 50°C and pH 4.5. For 10 min, the enzyme was deactivated in an 80°C water bath. The absorbance at 280 nm was measured to determine the optimal enzymatic hydrolysis time. Figure 2b depicts the results.
As shown in Figure 2b, the absorbance of red pigment from jujube peel gradually increased with increasing enzymatic hydrolysis time, reaching a maximum value of 1.358 at 1 h. The absorbance then decreased due to the prolongation of enzymatic hydrolysis time. When the enzymatic hydrolysis time was short, the enzyme activity was not fully utilized, and excessive time led to the loss of activity of some enzymes, which reduced the amount extracted. The absorbance value decreased because the quantity of the enzymatic hydrolysis product impeded the hydrolysis process when the duration was too long [31].
Taking the above factors into consideration, the enzymatic hydrolysis time was 1 h, and the enzyme activity was optimal at this time. Therefore, the enzymatic hydrolysis time of 1 h was considered optimal.
3.7 Effect of enzymatic hydrolysis pH on pigment extraction
Five grams of 40 mesh raw materials were weighed, 100 mL of 80% ethanol and 1.2% cellulase were added and then digested for 1 h at 50°C and pH 3.5, 4.5, 5.5, 6.5, 7.5, or 8.5. For 10 min, the enzyme was deactivated in an 80°C water bath. The absorbance at 280 nm was measured to determine the optimal enzymatic hydrolysis pH. The results are shown in Figure 2c.
Cellulase exhibited maximal viability at pH 3.5, as shown in Figure 2c, and the absorbance of the jujube extract was 1.389. The absorbance gradually decreased as the pH increased, and the enzyme was severely inhibited at pH 5.5–6.5. The main reason for the red pigment extraction rate variation from jujube peel with pH was that cellulase was most stable at pH 3.5. The enzyme was gradually denatured as the pH increased [32]. Therefore, pH 3.5 was selected as the optimal enzymatic hydrolysis pH. Based on the data mentioned above, the extraction efficiency of anthocyanin from fruit is determined by many factors such as the extracting reagent, enzyme kinds, and treatment conditions [33].
3.8 Parameter optimization of the jujube extraction process
3.8.1 PB experimental design screening of the main influencing factors
Six experimental factors (A. pulverization degree, B. enzymatic hydrolysis time, C. enzymatic hydrolysis pH, D. solid-liquid ratio, E. ethanol concentration, and F. enzyme amount) and 5 blank factors (G, H, I, J, and K) were selected using the PB experimental design principle, for a total of 11 factors and 12 experiments. Each factor’s high and low levels were determined using the design experiments and data processing with Design-Expert 8.0 software based on the single factor results. Table 1 displays the PB experimental design factors and levels.
Parameters in the Plackett–Burman experimental design
| Level | A | B | C | D | E | F | G | H | I | J | K |
|---|---|---|---|---|---|---|---|---|---|---|---|
| −1 | 40 | 0.5 | 3 | 70 | 1:20 | 1 | — | — | — | — | — |
| 1 | 80 | 1.5 | 4 | 90 | 2:10 | 1.5 | — | — | — | — | — |
Six factors and 5 blank factors were used in a total of 12 experiments. The experiment was performed in triplicates under the PB design table to calculate the average amount of red pigment extracted from the jujube peel. Table 2 displays the PB experimental design and response values. Design-Expert 8.0 software was used to assess significant differences. The most influential factors were those with P < 0.05. Table 3 displays the results of the analysis of various significant factors.
Plackett–Burman experimental design and response value
| Number | A | B | C | D | E | F | G | H | I | J | K | Response value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | 1 | −1 | 1 | 1 | 1 | −1 | −1 | −1 | 1 | −1 | 1 | 1.26 |
| 2 | 1 | −1 | −1 | −1 | 1 | −1 | 1 | 1 | −1 | 1 | 1 | 1.358 |
| 3 | 1 | −1 | 1 | 1 | −1 | 1 | 1 | 1 | −1 | −1 | −1 | 0.49 |
| 4 | −1 | 1 | 1 | 1 | −1 | −1 | −1 | 1 | −1 | 1 | 1 | 0.868 |
| 5 | 1 | 1 | −1 | 1 | 1 | 1 | −1 | −1 | −1 | 1 | −1 | 1.176 |
| 6 | −1 | −1 | −1 | −1 | -1 | −1 | −1 | −1 | −1 | −1 | -1 | 1.232 |
| 7 | −1 | 1 | 1 | −1 | 1 | 1 | 1 | −1 | −1 | −1 | 1 | 1.092 |
| 8 | 1 | 1 | 1 | −1 | −1 | −1 | 1 | −1 | 1 | 1 | −1 | 1.078 |
| 9 | −1 | 1 | −1 | 1 | 1 | −1 | 1 | 1 | 1 | −1 | −1 | 1.512 |
| 10 | 1 | 1 | −1 | −1 | −1 | 1 | −1 | 1 | 1 | −1 | 1 | 1.176 |
| 11 | −1 | −1 | 1 | −1 | 1 | 1 | −1 | 1 | 1 | 1 | −1 | 0.756 |
| 12 | −1 | −1 | −1 | 1 | −1 | 1 | 1 | −1 | 1 | 1 | 1 | 0.966 |
Estimated regression coefficients of the Plackett–Burman experiment
| Source | Effect | F-value | P-value | Order |
|---|---|---|---|---|
| A | 0.770 | 6.02 | 0.8309 | 6 |
| B | 0.007 | 0.051 | 0.1523 | 4 |
| C | 0.050 | 2.85 | 0.0130 | 1 |
| D | –0.025 | 14.21 | 0.4373 | 5 |
| E | –0.080 | 0.71 | 0.0428 | 3 |
| F | –0.098 | 11.02 | 0.0210 | 2 |
It can be concluded from Table 3 that the order of influence of these six factors on the improvement of glucoamylase activity was: C > F > E > B > D > A. The variables with significant influence were screened using the t-test, and P < 0.05 indicated that the factor had a significant effect on the response. Therefore, the most significant influences on the outcomes were enzymatic pH (P = 0.013), ethanol concentration (P = 0.0428), and enzyme amount (P = 0.0210). These three factors were selected as significant factors for subsequent optimization studies.
3.8.2 Box–Behnken design experiment
The Box–Behnken experiment optimized the three factors that significantly influenced the extraction rate of red pigment from jujube peel. Using ethanol concentration (X 1), enzyme amount (X 2), and enzymatic pH (X 3) as variables, each variable’s three levels were encoded by −1, 0, and 1, respectively. The experimental factors and levels are shown in Table 4.
Actual factor levels corresponding to coded factor levels in the Box–Behnken design
| Code | Factor | Level | ||
|---|---|---|---|---|
| −1 | 0 | +1 | ||
| X 1 | Ethanol content (%) | 70 | 80 | 90 |
| X 2 | Enzyme amount (%) | 0.4 | 1.2 | 2 |
| X 3 | Enzymolysis pH | 2.5 | 3.5 | 4.5 |
This experiment design included 17 groups of experiments. The experiment was performed in triplicates, and the response value was the average of three measurements. Tables 5 and 6 illustrate experimental data analysis using Design-Expert version 8.0.6, the Box–Behnken test design, experimental results, and variance analysis.
Box–Behknen design matrix and experimental results
| Run | X 1 | X 2 | X 3 | OD value |
|---|---|---|---|---|
| 1 | −1 | 1 | 0 | 1.18 |
| 2 | 0 | 0 | 0 | 1.7 |
| 3 | 1 | 0 | −1 | 0.88 |
| 4 | 0 | 0 | 0 | 1.74 |
| 5 | 0 | −1 | −1 | 1.51 |
| 6 | 1 | −1 | 0 | 1.05 |
| 7 | −1 | 0 | 1 | 0.75 |
| 8 | 0 | 0 | 0 | 1.78 |
| 9 | 0 | 1 | −1 | 1.4 |
| 10 | 0 | 1 | 1 | 0.8 |
| 11 | 1 | 1 | 0 | 0.8 |
| 12 | 0 | 0 | 0 | 1.76 |
| 13 | −1 | 0 | −1 | 1.56 |
| 14 | 0 | −1 | 1 | 1.24 |
| 15 | 0 | 0 | 0 | 1.72 |
| 16 | −1 | −1 | 0 | 1.14 |
| 17 | 1 | 0 | 1 | 1.12 |
Standard analysis of variance for the Box–Behknen experimental results
| Source | df | Sum of squares | Mean square | F-Value | P-Value (Prob >F) | Significance |
|---|---|---|---|---|---|---|
| X 1 | 1 | 0.076 | 0.076 | 16.18 | 0.0050 | * |
| X 2 | 1 | 0.072 | 0.072 | 15.36 | 0.0058 | * |
| X 3 | 1 | 0.26 | 0.26 | 55.15 | 0.0001 | * |
| X 1 × X 1 | 1 | 0.77 | 0.77 | 164.68 | <0.0001 | ** |
| X 1 × X 2 | 1 | 0.021 | 0.021 | 4.47 | 0.0722 | |
| X 1 × X 3 | 1 | 0.28 | 0.28 | 58.64 | 0.0001 | * |
| X 2 × X 2 | 1 | 0.030 | 0.030 | 64.70 | <0.0001 | ** |
| X 2 × X 3 | 1 | 0.027 | 0.027 | 5.79 | 0.0470 | * |
| X 3 × X 3 | 1 | 0.23 | 0.23 | 48.95 | 0.0002 | * |
| Model | 9 | 2.18 | 0.24 | 51.49 | <0.0001 | ** |
| Pure error | 4 | 0.016 | 0.004 | |||
| Lack of fit | 3 | 0.12 | 0.041 | 9.63 | 0.0266 | |
| Cor total | 16 | 8.82 | ||||
| R 2 | 0.9851 | |||||
| Adjusted R 2 | 0.9660 | |||||
| CV% | 5.27 |
* Significant; ** very significant.
Recombining the various components resulted in the regression equation. The quadratic multiple regression equation of the amount of red pigment extracted from jujube peel to ethanol concentration (X 1), enzyme amount (X 2), and enzymatic hydrolysis pH (X 3) was obtained after regression of the response values in Table 5, and various factors using the Design-Expert software, which was R1 = 1.74 − 0.0975X 1 − 0.095X 2 − 0.18 X 3 − 0.072500X 1 X 2 + 0.26250X 1 X 3 − 0.0825X 2 X 3 − 0.42875 X 12 − 0.2687 X 22 − 0.23375X 32.
Table 6 displays the analysis of variance and the reliability analysis of the regression equation. From the results, the model had a P-value of <0.0001, which was highly significant. The F test evaluated the significance of each variable’s response in the regression equation. The higher the degree of significance of the corresponding variable, the smaller the probability P-value. The missing items reflected that the experimental data were inconsistent with the model. The missing items had a P-value > 0.01, and the miscalculation was insignificant; thus, the model selection was correct. In the model credibility analysis, the square of the complex correlation coefficient was R 2 = 0.9660, indicating that the model can explain a change of 96.60% in experimentally obtained red pigment from jujube peel, indicating that the equation fitted well. The experiment’s accuracy was assessed by CV (the coefficient of variation in Y). The higher the CV value, the lower the reliability of the experiment. The design experiment’s CV was 5.27%, indicating that the experimental method was credible. The regression equation provided a suitable model for jujube peel extraction parameters.
The contour map that corresponds to the three-dimensional response surface map produced by the model equation (Figure 3) may be used to explain the influence of each variable on the response value. The central level value of one of the three variables was fixed in this graph, and the amount of red pigment extracted was analyzed and evaluated using the other two variables. The shape of the contour line visually analyzed the strength of the interaction. An ellipse indicated that the interaction between the two factors was significant, while a circle illustrated the opposite [34]. Figure 3 shows that for the extraction of red pigment, the interaction between enzymatic hydrolysis pH and the amount of enzyme added was the strongest, followed by the amount of enzyme added and ethanol concentration, and the interaction between ethanol concentration and enzymatic hydrolysis pH was the weakest.
The contour map and response surface graph between various factors. Combinative effects of enzyme dosage × ethanol concentration (a), enzymolysis pH × enzyme dosage (b), and enzymolysis pH × ethanol concentration (c) on pigment extraction from jujube fruits were monitored (n = 3; error bar, a standard deviation of the sample, SD; OD value is the optical density value measured at 280 nm).
The model prediction value was 1.79 when Design-Expert was used to solve the regression equation using enzymatic pH (3.15), enzyme amount (1.18%), and ethanol concentration (73.62%). Under optimum circumstances, three reproducibility tests were carried out, and the experimental value was 1.79 ± 0.107. The results were very close to the theoretical predictions, and the model’s stability was verified.
3.9 Identification of the main pigment component of peel extracts
To test the chemical composition of the red pigment from jujube peel, eight standard products were selected for HPLC detection, as shown in Figure 4a (pelarin-3-5-glucoside, delphinidin-3-O-galactoside, delphinidin-3-O-rutinoside, cyanidin-3-O-galactoside, cyanidin-3-O-glucoside, cyanidin-3-O-rutinoside, petunia, pelarin-3-O-glucoside), and eight standard solutions at a concentration of 100 μg/mL were included. The injection volume was 20 μL. The results were as follows:
HPLC analysis of the main pigment components of peel extracts. HPLC chromatograms of standard solutions (a) and pigment extract samples (b). Retention time of peak 2 and peak 6 were 4.43 and 6.61 min, respectively, for standards and pigment extract samples. The 2–8 peak presented in (a) (1, pelarin-3-5-glucoside; 2, delphinidin-3-O-galactoside; 3, delphinidin-3-O-rutinoside; 4, cyanidin-3-O-galactoside; 5, cyanidin-3-O-glucoside; 6, cyanidin-3-O-rutinoside; 7, petunia; and 8, pelarin-3-O-glucoside). Mass spectrogram of delphinidin-3-O-galactoside (c) and cyanidin-3-O-rutinoside (d)
Figure 4b shows that two substances were identified in the extracted sample of red pigment from jujube peel, namely, the second peak delphinidin-3-O-galactoside with a retention time of 4.438 min and the sixth peak chrysin-3-O-rutinoside with a retention time of 6.61 min. These 2 components have the same peak times as peaks 2 and 6 in the standard. Figure 4c and d demonstrate that delphinidin-3-O-galactoside represented 466.11058 (M–H)+ ion at m/z, the elemental composition was C21H21O12, and chrysin-3-O-rutinoside represented 630.9790 (M–H)+ ion at m/z, the elemental composition was C27H31O15Cl, both of which were detected in their MS spectra [35,36]. It was consistent with the previous report, illustrating that the anthocyanins are the predominant pigment of jujube fruit peel [37].
Figure 4b shows that the red pigment from the jujube peel includes at least 10 substances, indicating that further investigation is required.
3.10 Antioxidant activity of pigment extracts from jujube peel
Hydroxyl radicals are highly toxic and produced during the metabolism of organisms. They can react biologically with living cells, causing oxidative damage or cell necrosis, and are closely related to aging and diseases such as cancer. Therefore, screening safe and effective hydroxyl radical scavengers have been a research hotspot [38]. Figure 5a depicts the hydroxyl radical scavenging activity of red pigment from the jujube peel. It can be seen that red pigment from jujube peel and ascorbic acid were able to scavenge hydroxyl radicals. The hydroxyl radical scavenging rate increased from 44.6 to 91.2% when the concentration of red pigment from jujube peel was increased from 0.1 to 0.5 g/L. When the hydroxyl radical scavenging rate was 50%, the concentration of jujube red pigment, ascorbic acid, and blueberries was 0.18, 0.24, and 0.31 g/L, respectively. This demonstrates that the scavenging rate of red pigment was greater than that of ascorbic acid blueberries. This indicated that the red pigment in the jujube peel exhibited strong hydroxyl radical scavenging activity.
Antioxidant activity of pigment extracts. Effects of pigment extracts on hydroxyl radical scavenging capacity (a), superoxide scavenging capacity (b), and Fe3 + reducing power (c) during in vitro experiment. Means associated with the same letter are not significantly different (n = 3; error bar, a standard deviation of the sample, SD).
Superoxide anions have strong activity as a precursor to numerous active free radicals and can directly cause DNA damage in cells. In addition, they can be converted into hydroxyl radicals with stronger oxidation activity [39]. Therefore, the superoxide anions scavenging activity of red pigment from the jujube peel was determined. Figure 5b depicts the results. When the concentration of red pigment from the jujube peel increased from 0.1 to 0.5 g/L, the superoxide anion scavenging rate increased from 16.5 to 54.4. When the concentration of superoxide anion scavenging activity was 50%, the concentration of jujube red pigment was 0.45 g/L, which was lower than the concentration of ascorbic acid and blueberries. Red pigment also had a high scavenging rate than ascorbic acid and blueberries. This indicated that the purified red pigment from the jujube peel was capable of scavenging the superoxide anion.
A good antioxidant generally has a good reducing ability, and the reducing power can be used to evaluate antioxidant activity indirectly. When the mass concentration of purified red pigment from jujube peel was in the range of 0.1–0.5 g/L in this experiment, the absorbance increased rapidly as the mass concentration increased, reaching 1.145 at 0.5 g/L. The concentrations of jujube red pigment, ascorbic acid, and blueberries were 0.20, 0.27, and 0.24 g/L, respectively, when absorbance was 50%. This demonstrates that red pigment has a stronger reducing power than ascorbic acid and blueberries.
The reducing power of red pigment was slightly greater than that of ascorbic acid (Figure 5c), indicating that red pigment from jujube peel had strong dose-dependent reducing power. Based on the data mentioned above, the red pigment from the red peel provided the fruit with enhanced antioxidant activity [40].
4 Conclusion
Parameters were optimized in this study in response to alcohol extraction and enzymatic hydrolysis of red pigment from jujube peel. Using the PB experimental design, it was discovered that the amount of red pigment extracted from jujube peel was significantly affected by enzymatic hydrolysis pH, ethanol concentration, and enzyme amount. The optimal conditions for enzymatic hydrolysis were identified via the Box–Behnken experiment and Design-Expert analysis software to be pH 3.15, enzyme quantity of 1.18%, and ethanol concentration of 73%. The absorbance of red pigment from jujube peel under optimal conditions was 1.802, 29.7% higher than the absorbance before optimization. The red pigment in the jujube peel was identified using UHPLC and found to include delphinidin-3-O-galactoside and cyanidin-3-O-rutinoside. For the first time, the chemical composition of red pigment from jujube peel was qualitatively identified. In vitro experiments demonstrated that the red pigment from jujube peel could scavenge hydroxyl radicals and superoxide anion radicals and had strong reducing power. The red pigment found in jujube peel has the potential to be employed as a potential natural antioxidant.
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Funding information: This work was supported by the National Natural Science Foundation of China (Grant Nos.: 32001669 and 32101565) and Key Scientific Research Projects in Colleges and Universities of Henan Province (Grant No.: 20B180005)
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Author contributions: Hongxia Liu: conceptualization, investigation, funding acquisition, and writing and reviewing; Jingjie Wu: full text proofreading, Benliang Deng and Zhien Cai: investigation, project administration, visualization, and resources; Hui Liu: validation, formal analysis, writing and reviewing, and editing; Xusheng Zhao: supervision
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Conflict of interest: The authors declare that no conflicts of interest exist in the work reported in this manuscript.
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Ethical approval: The conducted research is not related to either human or animal use.
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Data availability statement: All data analyzed during this study are included in this published article. The detailed data are available on reasonable request.
References
[1] Chi A, Kang C, Zhang Y, Tang L, Guo H, Li H, et al. Immunomodulating and antioxidant effects of polysaccharide conjugates from the fruits of Ziziphus Jujube on Chronic Fatigue Syndrome rats. Carbohyd Polym. 2015;122:189–96.10.1016/j.carbpol.2014.12.082Search in Google Scholar PubMed
[2] Kou X, Chen Q, Li X, Li M, Kan C, Chen B, et al. Quantitative assessment of bioactive compounds and the antioxidant activity of 15 jujube cultivars. Food Chem. 2015;173:1037–44.10.1016/j.foodchem.2014.10.110Search in Google Scholar PubMed
[3] Wang AR. The nutritive and medicinal values of the red data. Sci/Tech Inf Dev Econ. 2005;15:143–4 (in Chinese).Search in Google Scholar
[4] Sun LX, Zhang QH, Chen JP. Nutrition and health of jujube and its comprehensive utilization. Farm Prod Pro. 2008;4:54–61 (in Chinese).Search in Google Scholar
[5] Zhang H, Jiang L, Ye S, Ye Y, Ren F. Systematic evaluation of antioxidant capacities of the ethanolic extract of different tissues of jujube (Ziziphus jujuba Mill.) from China. Food Chem Toxicol. 2010;48:1461–5.10.1016/j.fct.2010.03.011Search in Google Scholar PubMed
[6] Rabiei Z, Rafieian-Kopaei M, Heidarian E, Saghaei E, Mokhtari S. Effects of Ziziphus jujube extract on memory and learning impairment induced by bilateral electric lesions of the nucleus basalis of Meynet in rat. Neurochem Res. 2014;39:353–60.10.1007/s11064-013-1232-8Search in Google Scholar PubMed
[7] Jung HY, Sawayanagi T, Kakizawa S, Nishigawa H, Wei W, Oshima K, et al. ‘Candidatus Phytoplasma Ziziphi’, a novel phytoplasma taxon associated with jujube witches’-broom disease. Int J Syst Evol Micr. 2003;53:1037–41.10.1099/ijs.0.02393-0Search in Google Scholar PubMed
[8] Jian GJ, Xiao JH, Jian C. Comparison of the sedative and hypnotic effects of flavonoids, saponins, and polysaccharides extracted from Semen Ziziphus jujube. Nat Prod Res. 2007;21:310–20.10.1080/14786410701192827Search in Google Scholar PubMed
[9] Shi H, Tian YL. Study of jujube pigment extracted and its stability. Food Res Dev. 2011;5:186–9 (in Chinese).Search in Google Scholar
[10] Li WF, Feng W, Lv J, Liu JH. Research Progress on extraction process of red jujube red pigment. Tesenon. 2010;7:10–1 (in Chinese).Search in Google Scholar
[11] Ahuja SK, Ferreira GM, Moreira AR. Application of Plackett–Burman design and response surface methodology to achieve exponential growth for aggregated shipworm bacterium. Biotechnol Bioeng. 2004;85:666–75.10.1002/bit.10880Search in Google Scholar PubMed
[12] An-Ran Z, Pei-Lan S, Xiao-Dan G, Li-Fen Z, Hui X. Structure preliminary identification and antioxidant activity of red pigment from jujube peel. Food Sci Technol. 2016;41(11):230–5.Search in Google Scholar
[13] Liu Z, Zhao L. The optimum of L-valine fermentation culture based on response surface analysis. Acta Sci Nat Uni Nankai. 2009;42:24–8.Search in Google Scholar
[14] Eckart K, Röhrich J, Breitmeier D, Ferner M, Laufenberg-Feldmann R, Urban R. Development of a new multi-analyte assay for the simultaneous detection of opioids in serum and other body fluids using liquid chromatography–tandem mass spectrometry. J Chromatogr B. 2015;1001:1–8.10.1016/j.jchromb.2015.06.028Search in Google Scholar PubMed
[15] Yang L, Zhao T, Wei H, Zhang M, Zou Y, Mao G, et al. Carboxymethylation of polysaccharides from Auricularia auricula and their antioxidant activities in vitro. Int J Biol Macromol. 2011;49:1124–30.10.1016/j.ijbiomac.2011.09.011Search in Google Scholar PubMed
[16] Wang J, Chao DU, Liang C, Lizhi MA, Zeng J. Extraction and antioxidant activity of polysaccharides from Guichang Kiwifruit. Food Sci. 2016;37:19–23.Search in Google Scholar
[17] Tsai SY, Huang SJ, Mau JL. Antioxidant properties of hot water extracts from Agrocybe cylindtracea. Food Chem. 2006;98:670–7.10.1016/j.foodchem.2005.07.003Search in Google Scholar
[18] Yang J, Yuan CL, Ren YM, Fang YF, Yang XY, Zhang SJ, et al. Extraction and anti-ultraviolet activity of proanthocyanidins from grape seed. Food Sci. 2014;18:69–73.Search in Google Scholar
[19] Wu JD, Gan GS, Chen HM, Li HM. Studies on the enzyme hydrolysis of soluble polysaccharide from Momordica charantia. J Anhui Agri Sci. 2005;33:73–4.Search in Google Scholar
[20] Boesten JJTI. Influence of solid/liquid ratio on the experimental error of sorption coefficients in pesticide/soil systems. Pest Manag Sci. 1990;30:31–41.10.1002/ps.2780300105Search in Google Scholar
[21] Bucić-Kojić A, Planinić M, Tomas S, Bilić M, Velić D. Study of solid–liquid extraction kinetics of total polyphenols from grape seeds. J Food Eng. 2007;81:236–42.10.1016/j.jfoodeng.2006.10.027Search in Google Scholar
[22] Zou T, Wang D, Guo H, Zhu Y, Luo X, Liu F, et al. Optimization of microwave-assisted extraction of anthocyanins from mulberry and identification of anthocyanins in extract using HPLC-ESI-MS. J Food Sci. 2012;77:C46–50.10.1111/j.1750-3841.2011.02447.xSearch in Google Scholar PubMed
[23] Du FY, Deng BW. Studies on the extraction technique and physico-chemical properties of the pigment from jujube. J North Fore Univer. 2005;1:181–5.Search in Google Scholar
[24] Sun LX, Chen JP, Liu FY. Study on extraction technology of jujube pigment. Sci Tech Food Ind. 2005;1:153–5.Search in Google Scholar
[25] Xia J, Shu J, Yao K, Xu J, Yu X, Xue X, et al. Synergism of cellulase, pectinase and xylanase on hydrolyzing differently pretreated sweet potato residues. Prep Biochem Biotech. 2020;50:181–90.10.1080/10826068.2019.1680390Search in Google Scholar PubMed
[26] Mary M, James W, Richard P. Enhanced cellulase production by a mutant of Trichoderma viride. Appl Microbiol. 1971;21:152–4.10.1128/am.21.1.152-154.1971Search in Google Scholar PubMed PubMed Central
[27] Yi-Heng PZ, Lee RL. Toward an aggregated understanding of enzymatic hydrolysis of cellulose: noncomplexed cellulase systems. Biotechnol Bioeng. 2004;88:797–824.10.1002/bit.20282Search in Google Scholar PubMed
[28] Yi-Heng PZ, Michael EH, Jonathan RM. Outlook for cellulase improvement: screening and selection strategies. Biotechnol Adv. 2006;24:452–81.10.1016/j.biotechadv.2006.03.003Search in Google Scholar PubMed
[29] Rasmus D, Sven P, Lisbeth O. Characterization of very high gravity ethanol fermentation of corn mash. Effect of glucoamylase dosage, pre-saccharification and yeast strain. Appl Microbiol Biot. 2005;68:622–9.10.1007/s00253-005-1902-9Search in Google Scholar PubMed
[30] Modi MK, Reddy JRC, Rao BVSK, Prasad RBN. Lipase-mediated conversion of vegetable oils into biodiesel using ethyl acetate as acyl acceptor. Bioresour Techn. 2007;98:1260–4.10.1016/j.biortech.2006.05.006Search in Google Scholar PubMed
[31] Chen XH, Xu YQ. Study on the extraction of total flavonoids from raspberry leaves by enzymatic treatment. Food Res Dev. 2007;34:37–9.Search in Google Scholar
[32] Wang ZY, Yang Q. The study on anthocyanin preparation by enzyme. China Beet Sugar. 2004;4:26–9.Search in Google Scholar
[33] Silva S, Costa EM, Calhau C, Morais RM, Pintado ME. Anthocyanin extraction from plant tissues: a review. Crit Rev Food Sci. 2017;57:3072–83.10.1080/10408398.2015.1087963Search in Google Scholar PubMed
[34] Khuri AI, Mukhopadhyay S. Response surface methodology. Adv Rev. 2010;2:128–49.10.1007/978-3-642-04898-2_492Search in Google Scholar
[35] Sankara Subramanian S, Nagarajan S, Sulochana N. Chrysin-7-rutinoside from the leaves of Dolichandrone falcate. Phytochem. 1972;11:438–9.10.1016/S0031-9422(00)90041-4Search in Google Scholar
[36] Rongda C, Yurui S, Guiming L, Yanzhou T, Yangyang F, et al. Spectroscopic studies and molecular docking on the interaction of delphinidin-3-O-galactoside with tyrosinase. Biotechnol Appl Biochem. 2021;35:1–12.Search in Google Scholar
[37] Zhang Q, Wang L, Liu Z, Zhao Z, Zhao J, Wang Z, et al. Transcriptome and metabolome profiling unveil the mechanisms of Ziziphus jujuba Mill. peel coloration. Food Chem. 2020;312:125903.10.1016/j.foodchem.2019.125903Search in Google Scholar
[38] Wang ZY, Xiao HQ. Progress indetermination of hydroxyl radical. Food Nutr. 2009;25:23–4 (in China).Search in Google Scholar
[39] Wickens AP. Ageing and the free radical theory. Respir Physiol. 2001;128:379–91.10.1016/S0034-5687(01)00313-9Search in Google Scholar
[40] Shi Q, Zhang Z, Su J, Zhou J, Li X. Comparative analysis of pigments, phenolics, and antioxidant activity of Chinese jujube (Ziziphus jujuba Mill.) during fruit development. Molecules. 2018;23:1917.10.3390/molecules23081917Search in Google Scholar PubMed PubMed Central
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