Efficient Ultrasound-Assisted Extraction of Bioactive Molecules from Brown Macroalga Sargassum horneri: Optimal Extraction, Antioxidant and Cytotoxicity Evaluation

Abstract

Sargassum horneri (SH) is a promising marine bioresource for producing bioactive compounds. Recently, the biological functions (including anti-inflammatory, antioxidant, and anticancer activities) of SH extracts have been revealed; however, efficient extraction processes to produce bioactive molecules (such as tannin and phenol) have not been carefully designed. In this study, the ultrasound-assisted extraction process was optimized based on the response surface methodology (RSM) to efficiently produce tannin and phenol from SH. Significant RSM models (p < 0.05) for predicting tannin and phenol yields were developed, and prethanol A concentration, temperature, and solid loading were significantly affected by tannin or phenol yield (p < 0.05). Following numerical optimization, the tannin and phenol yields achieved 14.59 and 13.83 mg/g biomass, respectively, under optimal conditions (39.1% solvent, 61.9 °C, 52.0 g/L solid loading, and 49.0% amplitude), similar to the model-predicted values (12.95 and 13.37 mg/g, respectively). Then, time profiling under optimal conditions determined the optimal time as 10.0 min, resulting in the highest yield (15.88 mg tannin and 14.55 mg phenol/g). The extracts showed antioxidant activity (IC₅₀: 79.86 μg/mL) comparable to that of ascorbic acid (vitamin C). It was found to be particularly non-toxic, raising its potential as a functional ingredient in food or cosmetics.

1. Introduction

Brown macroalgae are attracting attention as a promising source of bioactive molecules such as phenolics, polysaccharides, and vitamins [1,2,3]. In particular, tannins and phenols have been reported as natural molecules of brown macroalgae, with various biological activities such as antioxidant, anticancer, antidiabetic, and antiviral activities [4]. Bioactive substances extracted from brown macroalgae have been applied to develop various products such as food and cosmetics, thereby promoting the discovery of next-generation bioactive molecules [5,6,7]. In recent years, research has been actively conducted on feedstock exploration, extraction process design, formulation, and application [1,8,9].

Since 2015, Sargassum horneri (SH) has been entering Jeju Island and the coast of the Korean Peninsula between February and May each year, causing significant damage to aqua-farming sites and navigation [10]. In particular, it causes damage to aquaculture facilities, reduces the quality of farmed organisms, and creates odors due to spoilage, all of which are costly [11]. While some of the large amounts of SH are used as agricultural fertilizer or livestock feed, most of them are landfilled or incinerated, which requires diversified sustainable use [12]. The following applications were reported for the sustainable use of SH: bioactive ingredients [13], biodegradable packaging films [14], and a potential therapeutic drug for treating particulate matter-exacerbated allergic asthma [15].

SH extracts contain various bioactive compounds such as phenol, tannin, fucoxanthin, and polysaccharides, and various bioactivities of SH extracts (including anti-inflammatory, antioxidant, and anticancer activities) have been identified [16,17,18,19,20]. Although optimization of the extraction process for some bioactive compounds (fucoxanthin and polysaccharide) has been conducted [20,21], the process design and optimization for efficient tannin and phenol production from SH have not been carefully performed. Therefore, it is necessary to design a process for efficiently extracting bioactive molecules from SH.

Bioactive molecules including phenols and tannins can be recovered from biomass by conventional methods including maceration and decoction [22,23]. Maceration is a simple method that is easy to scale up, but it must be operated for a long time to obtain a high extraction yield [24,25,26]. Since the decoction requires thermal interference, it is only suitable for extracting thermally stable compounds. [25]. Accordingly, non-conventional extraction methods such as ultrasound-assisted extraction have been developed to address high energy consumption and long extraction time [27]. By applying ultrasound-assisted extraction, bioactive compounds can be efficiently extracted from biomass under mild conditions because of the cavitation phenomenon [28,29]. In addition, recent studies successfully performed the scale-up of the ultrasound-assisted extraction process after optimization at the laboratory scale, with satisfactory extraction yields [30,31].

This study aimed to design and optimize an ultrasound-assisted extraction process to efficiently recover bioactive molecules such as tannins and phenols from SH. In the extraction process, considering applications such as food and cosmetics, prethanol A (ethanol) was utilized as a solvent. Major process parameters such as solvent concentration, extraction temperature, solid loading, and amplitude were selected and investigated for response surface modeling and optimization. Furthermore, antioxidant activity and cytotoxicity properties were investigated to evaluate the practical applications of SH.

2. Results and Discussion

2.1. Development of Regression Models for Predicting Tannin and Phenol Yields from Sargassum horneri

The objective was to optimize ultrasound-assisted extraction process parameters in order to maximize the extraction yield of tannins and phenols from SH. To optimize extraction process parameters, a model must be developed that can predict tannin and phenol extraction yields within designed extraction conditions. A regression model was developed to predict the extraction yield of tannin and phenol through extraction experiments designed by Design Expert (

Table 1. Design of experiments and their response values (tannin and phenol extraction yield).

Std #	Parameter Symbol (Coded Level)				Responses (mg/g Biomass)
	A	B	C	D	Tannin Yield	Phenol Yield
1	−1	−1	−1	−1	9.15	7.15
2	1	−1	−1	−1	8.10	5.84
3	−1	1	−1	−1	11.41	9.09
4	1	1	−1	−1	10.74	13.16
5	−1	−1	1	−1	8.54	6.58
6	1	−1	1	−1	7.88	4.50
7	−1	1	1	−1	9.72	4.10
8	1	1	1	−1	8.62	5.29
9	−1	−1	−1	1	10.09	7.54
10	1	−1	−1	1	8.75	11.12
11	−1	1	−1	1	11.49	9.31
12	1	1	−1	1	9.48	12.71
13	−1	−1	1	1	9.18	7.10
14	1	−1	1	1	7.26	5.23
15	−1	1	1	1	9.55	3.43
16	1	1	1	1	8.92	7.69
17	−2	0	0	0	8.95	7.09
18	2	0	0	0	5.59	4.61
19	0	−2	0	0	9.14	6.74
20	0	2	0	0	12.63	9.80
21	0	0	−2	0	12.20	9.02
22	0	0	2	0	8.84	6.81
23	0	0	0	−2	12.17	7.38
24	0	0	0	2	11.63	8.40
25	0	0	0	0	11.24	8.65
26	0	0	0	0	11.73	8.77
27	0	0	0	0	10.14	7.75
28	0	0	0	0	9.92	7.56
29	0	0	0	0	11.58	7.97
30	0	0	0	0	12.04	8.61

Symbols: A, solvent concentration (wt%); B, extraction temperature (°C); C, solid loading (g/L); D, amplitude (%). The extraction conditions are represented as coded levels (see Section 3.2).

). Among the results of the extraction experiments, the highest tannin extraction yield (12.63 mg/g biomass) was observed under Std #20 (40% solvent, 70 °C, 100 g/L, and 60% amplitude). These results suggest that high temperatures are required for efficient tannin recovery from SH, but high concentrations of the solvent are not essential. The highest extraction yield of phenol (13.16 mg/g biomass) was observed under Std #4 (60% solvent, 60 °C, 75 g/L, and 40% amplitude). These results suggest that there is a partial difference, especially solvent concentration, between tannin and phenol recovery, requiring multi-objective optimization to produce bioactive extracts from SH.

Based on the results in

Table 2. ANOVA results for the initial model for predicting tannin yield from Sargassum horneri.

Source	Sum of Squares	DF	Mean Square	F-Value	p-Value
Model	71.98	14	5.14	7.9	0.0001
A	10.79	1	10.79	16.59	0.001
B	13.43	1	13.43	20.64	0.0004
C	11.04	1	11.04	16.97	0.0009
D	0.0118	1	0.0118	0.0181	0.8949
AB	0.019	1	0.019	0.0291	0.8668
AC	0.0356	1	0.0356	0.0548	0.8181
AD	0.3673	1	0.3673	0.5646	0.464
BC	0.5944	1	0.5944	0.9136	0.3543
BD	0.4459	1	0.4459	0.6853	0.4207
CD	0.0044	1	0.0044	0.0067	0.9357
A2	33.17	1	33.17	50.98	<0.0001
B2	1.04	1	1.04	1.59	0.2262
C2	2.25	1	2.25	3.47	0.0824
D2	0.0958	1	0.0958	0.1473	0.7065
Residual	9.76	15	0.6506
Lack of Fit	5.91	10	0.5911	0.7682	0.663
Pure Error	3.85	5	0.7695
Cor Total	81.74	29

DF, degree of freedom; R²: 0.8806, adjusted R²: 0.7692, adequate precision: 11.4701. Symbols: A, solvent concentration (wt%); B, extraction temperature (°C); C, solid loading (g/L); D, amplitude (%).

, a regression analysis was performed to predict tannin and phenol extraction yields, and the following Equations (1) and (2) were derived, respectively.

Tannin yield (mg/g biomass) = 11.11 − 0.6707A + 0.7481B − 0.6783C − 0.0221D + 0.0344AB + 0.0472AC − 0.1515AD − 0.1927BC − 0.1669BD − 0.0165CD − 1.1A² − 0.1944B² − 0.2867C² + 0.0591D²

(1)

Phenol yield (mg/g biomass) = 8.22 + 0.2611A + 0.6596B − 1.52C + 0.435D + 0.9136AB − 0.5149AC + 0.47AD − 0.9713BC − 0.3394BD − 0.1543CD − 0.5895A² + 0.0149B² − 0.0746C² − 0.0805D²

(2)

An analysis of variance (ANOVA) was performed to assess the statistical significance of regression model Equations (1) and (2) (Table 2 and

Table 3. ANOVA results of the initial model for predicting phenol yield from Sargassum horneri.

Source	Sum of Squares	DF	Mean Square	F-Value	p-Value
Model	120.18	14	8.58	4.16	0.0048
A	1.64	1	1.64	0.7929	0.3873
B	10.44	1	10.44	5.06	0.0399
C	55.3	1	55.3	26.8	0.0001
D	4.54	1	4.54	2.2	0.1587
AB	13.35	1	13.35	6.47	0.0225
AC	4.24	1	4.24	2.06	0.1722
AD	3.53	1	3.53	1.71	0.2103
BC	15.09	1	15.09	7.31	0.0163
BD	1.84	1	1.84	0.8929	0.3597
CD	0.3811	1	0.3811	0.1847	0.6735
A2	9.53	1	9.53	4.62	0.0483
B2	0.0061	1	0.0061	0.003	0.9574
C2	0.1526	1	0.1526	0.074	0.7894
D2	0.1779	1	0.1779	0.0862	0.7731
Residual	30.96	15	2.06
Lack of Fit	29.6	10	2.96	10.93	0.0083
Pure Error	1.35	5	0.2709
Cor Total	151.14	29

DF, degree of freedom; R²: 0.7952, adjusted R²: 0.6040, adequate precision: 8.8818. Symbols: A, solvent concentration (wt%); B, extraction temperature (°C); C, solid loading (g/L); D, amplitude (%).

). In general, p-values less than 0.05 indicate that the prediction model and model terms are statistically significant. In the case of Equation (1), solvent conc. (A, p-value = 0.001), extraction temp. (B, p-value = 0.0004), and solid loading (C, p-value = 0.0009) were significant parameters for tannin yield. On the contrary, it was confirmed that amplitude (D, p-value = 0.8949) and all interaction effects did not have a significant effect (p-value > 0.05) on tannin yield. Among the square terms, an indicator that evaluates the effect on tannin extraction yield when the value of each parameter increases to the limit, only A² (p-value < 0.0001) was found to have a statistically significant effect. In the case of Equation (2), the single parameters extraction temp. (p-value = 0.0399) and solid loading (p-value = 0.0001), and the interaction effects AB (p-value = 0.0225) and BC (p-value = 0.0163) were confirmed as significant parameters for phenol yield. Single parameter A was confirmed to be not statistically significant, but the square term A² (p-value = 0.0483) was found to have a significant impact, requiring reflection of parameter A into the model equation for numerical optimization [4].

In the results of the ANOVA, the R² value is an indicator of the degree of agreement between predicted and observed values [32]. As the R² value approaches 1, it can be judged that the prediction accuracy of the regression model is high. However, as the number of independent parameters increases, the R² value tends to increase regardless of the prediction accuracy. To prevent such overfitting errors, the adjusted R² value can be used as an indicator and was found to be 0.7692 for the tannin yield prediction model and 0.6040 for the phenol yield prediction model. To improve the prediction accuracy of the model, a model reduction was performed to remove model terms that did not have a statistically significant impact. As a result, the following reduced model Equations (3) and (4) were derived.

Tannin yield (mg/g biomass) = 10.73 − 0.6707A + 0.7481B − 0.6783C − 1.05A²

(3)

Phenol yield (mg/g biomass) = 7.63 + 0.2611A + 0.6596B − 1.52C + 0.9136AB − 0.9713BC

(4)

The results of the ANOVA on the improved model Equations (3) and (4) are summarized in

Table 4. ANOVA results of the reduced model for predicting tannin yield from Sargassum horneri.

Source	Sum of Squares	DF	Mean Square	F-Value	p-Value
Model	67.19	4	16.80	28.85	<0.0001
A	10.79	1	10.79	18.54	0.0002
B	13.43	1	13.43	23.07	<0.0001
C	11.04	1	11.04	18.97	0.0002
A2	31.92	1	31.92	54.83	<0.0001
Residual	14.56	25	0.5822
Lack of Fit	10.71	20	0.5354	0.6958	0.7458
Pure Error	3.85	5	0.7695
Cor Total	81.74	29

DF, degree of freedom; R²: 0.8219, adjusted R²: 0.7934, adequate precision: 22.6275. Symbols: A, solvent concentration (wt%); B, extraction temperature (°C); C, solid loading (g/L); D, amplitude (%).

and

Table 5. ANOVA results of the reduced model for predicting phenol yield from Sargassum horneri.

Source	Sum of Squares	DF	Mean Square	F-Value	p-Value
Model	95.83	5	19.17	8.32	0.0001
A	1.64	1	1.64	0.7101	0.4077
B	10.44	1	10.44	4.53	0.0437
C	55.30	1	55.30	24.00	<0.0001
AB	13.35	1	13.35	5.80	0.0241
BC	15.09	1	15.09	6.55	0.0172
Residual	55.31	24	2.30
Lack of Fit	53.95	19	2.84	10.48	0.0081
Pure Error	1.35	5	0.2709
Cor Total	151.14	29

DF, degree of freedom; R²: 0.6341, adjusted R²: 0.5578, adequate precision: 10.8407. Symbols: A, solvent concentration (wt%); B, extraction temperature (°C); C, solid loading (g/L); D, amplitude (%).

. By removing statistically insignificant parameters (D, AB, AC, AD, BC, BD, CD, B², C², and D²) from the initial model (1), the reduced model (3) was derived, and this model was selected as the final model to predict the tannin yield. An improved model (4) without the insignificant parameters (D, AC, AD, BD, CD, A², B², C², and D²) of the initial model (2) was selected as the final model to predict the phenol yield.

2.2. Effects of Extraction Parameters on Tannin and Phenol Extraction Yields from Sargassum horneri

The effects of ultrasound-assisted extraction process parameters on the extraction yield of tannin and phenol from SH were investigated. Figure 1 shows the one-factor effects on tannin extraction yield. A solvent concentration higher than about 40% decreased tannin yield from SH. Gam et al. [33] reported that as the solvent concentration increases, the total phenol content tends to increase and then rapidly decrease. The higher temperature resulted in a higher tannin and phenol yield from SH (Figure 1 and Figure 2). Kong et al. [34] showed that a high temperature leads to a higher yield extraction of phenolic compounds than a low temperature. The extraction process for high-solid loading resulted in decreased tannin and phenol yield (Figure 1 and Figure 2). In ultrasound-assisted extraction processes with low solid loading, the interaction between solids and liquids is more active, and the diffusion of the bioactive compounds from solid to liquid is more efficient [35].

2.3. Optimization of Extraction Parameters for Efficient Tannin and Phenol Recovery from Sargassum horneri

The developed models (3) and (4) can predict response values (i.e., tannin yield and phenol yield) within the designed range; thus, these were used in the numerical optimization. The targets were both maximizations of tannin yield and phenol yield from SH, and the results are shown in

Table 6. Optimization results for the efficient extraction of tannin and phenol from Sargassum horneri.

A	B	C	D	Tannin Yield (mg/g Biomass)		Phenol Yield (mg/g Biomass)
				Predicted	Experimental	Predicted	Experimental
39.1	61.9	52.0	49.0	12.95	14.59 ± 1.76	13.37	13.83 ± 0.09

. The optimal extraction conditions were derived as follows: solvent concentration, 39.1%; extraction temperature, 61.9 °C; solid loading, 52.0 g/L; and amplitude, 49.0%. Under these conditions, the tannin and phenol yields were predicted to be 12.95 and 13.37 mg/g biomass, respectively. To verify the prediction accuracy of the model, a verification experiment was conducted. As a result, the extraction yield of tannin and phenol was determined to be about 14.59 and 13.83 mg/g biomass, similar to the model-predicted values (p-value > 0.05). Therefore, the prediction model is suitable for predicting tannin and phenol yields. This study is significant in that an optimization model was developed for the first time.

To further increase the tannin and phenol yields from SH, it is necessary to optimize the extraction time; thus, extraction profiling was performed for 20.0 min under the RSM-determined optimal conditions (Figure 3). As a result, the extraction yields of tannin and phenol showed an increasing trend up to 10.0 min but did not significantly increase thereafter (p < 0.05). Therefore, the optimal extraction time was determined to be 10.0 min. The extraction yield was determined to be about 15.88 ± 0.38 mg tannin and 14.55 ± 0.30 mg phenol per g biomass under the final conditions: solvent concentration, 39.1%; extraction temperature, 61.9 °C; solid loading, 52.0 g/L; amplitude, 49.0%; and extraction time, 10.0 min. Overall, this study designed an optimal ultrasound-assisted extraction process for producing bioactive compounds from SH with a high yield. The produced tannin and phenol contained in the SH extracts at 42.15 and 39.95 mg/g, respectively. Kim et al. [17] produced SH extracts by immersing 10 g of dried SH in 500 mL of ethanol (70%) while stirring at room temperature for 12 h, and the total phenol content of the extracts was 8.52 ± 2.64 mg GAE/g. Therefore, the ultrasound-assisted extraction process is efficient for preparing phenol-rich SH extracts.

2.4. Antioxidant of Sargassum horneri Extracts

ABTS radical scavenging activity was determined to evaluate the antioxidant activity of the SH extracts (

Table 7. Antioxidant activity of the Sargassum horneri extracts produced under the optimal extraction conditions.

Sample	ABTS IC50 (μg/mL)
Sargassum horneri extracts	79.86 ± 0.42
Ascorbic acid (reference antioxidant)	54.37 ± 2.18

). The results of the radical scavenging activity (%) of the extracts were represented as IC₅₀ values (μg/mL). The ABTS IC₅₀ value of the SH extracts was determined to be about 79.86 μg/mL, which was about 68% activity compared to that of ascorbic acid (ABTS IC₅₀: 54.37 μg/mL). This antioxidant activity may be attributed to compounds such as tannins and phenols. Dang et al. [36] evaluated the ABTS radical scavenging activities of Sargassum extracts such as S. vestitum, S. linearifolium, and S. podocanthum extracts (at 0.06 mg/mL), and the activities were determined to be 31.71, 2.02, and 13.30 mg Trolox equivalent (TE)/g extract, respectively. These were 30.41%, 1.94%, and 12.76% activity compared to that of ascorbic acid (104.27 mg TE/g at 0.06 mg/mL) [36]. In the case of S. coriifolium extracts, the ABTS IC₅₀ value was determined to be 2.19 mg/mL, which was 7.31% activity of that of ascorbic acid (0.16 mg/mL) [37]. Meanwhile, in addition to tannins and phenols, compounds that contribute to antioxidant activity may exist in SH extracts [38,39], requiring the further identification of bioactive molecules before practical applications. This study confirmed that the SH extracts are expected to have a high potential as a natural antioxidant among various Sargassum extracts. The produced SH extracts with antioxidant activity can be applied to the development of antioxidant foods and antioxidant cosmetics. For instance, Park et al. [40] developed a functional ingredient containing SH extracts for food applications, with antioxidant and anti-obesity effects. Choung et al. [41] used SH extracts to develop a cosmetic with antioxidant and skin-whitening effects.

2.5. Effect of Sargassum horneri Extracts on the L929 Cell Viability

Figure 4 shows the cell viability of the SH extract-treated normal L929 fibroblast cells. Cell viability increased at all tested concentrations (0.25–1.5 mg/mL), with a maximum of 161.3% (at 0.75 mg/mL). In particular, cell viability in the extracts treatment group at concentrations of 0.5–1.25 mg/mL was significantly increased compared to that in the 0.25 mg/mL group (p < 0.05). The improved cell viability due to the addition of SH extracts can be related to the antioxidant activity of SH extracts. According to Li et al. [42], proteins secreted by the L929 cell lines are responsible for reactive oxygen species (ROS) production, and increased ROS levels have been reported to decrease cell viability. Turan et al. [43] evaluated the cytotoxicity of curcumin-loaded nano-fibrous membranes, showing an increased L929 cell viability (at 24 h measurement), and they presumed that this increase could be related to the ability of curcumin to prevent the formation of ROS. Therefore, the increased cell viability in this study can be attributed to the antioxidant activity of the SH extracts, but the related mechanisms should be investigated in detail, considering the presence of other substances besides antioxidants such as tannins and phenols. The present study highlights the non-toxicity of the SH extracts, which indicates their potential safety for applications.

3. Materials and Methods

3.1. Materials

SH was purchased from Parajeju (Jeju, Republic of Korea), washed with fresh water, naturally dried for two days, and ground. Na₂CO₃ (CAS No. 144-55-8) was purchased from DaeJung Chemicals & Metals (Siheung, Republic of Korea). Prethanol A (CAS No. 64–17-5) and tannin acid (CAS No. 1401-55-4) were purchased from Duksan Chemical (Ansan, Republic of Korea). Folin-Ciocalteu reagent, NaNO₂ (CAS No. 7632-00-0), K₂S₂O₈ (CAS No. 7727-21-1), gallic acid (CAS No. 149-91-7), ascorbic acid (CAS No. 50-81-7), 2,2’-Azino-bis (3-ethyl-benzothiozoline)-6-sulfonic acid (ABTS) (CAS NO. 28752-68-3), and potassium persulfate (CAS No. 7727-21-1) were purchased from Sigma-Aldrich (St. Louis, MO, USA).

3.2. Experimental Design and Statistical Optimization for Maximizing Tannin and Phenol Extraction Yields

RSM modeling and optimization were performed to maximize tannin and phenol yield from SH. Ultrasound-assisted extraction was performed by an Ultrasonic processor VCX–130 (Sonics and Materials Inc., Newton, CT, USA) with a 6 mm diameter probe (amplitude: 120 μm). The temperature was controlled using a water bath during the extraction process to prevent undesired thermal effects. For the process optimization, prediction model development, statistical model evaluation, and numerical optimization were performed based on the response surface methodology and central composite design using Design-Expert software version 7 (Stat-Ease Inc., Minneapolis, MN, USA) [26,44]. The following

Table 8. Parameters and their levels in the central composite rotatable design of the response surface methodology.

Parameter	Unit	Symbol	Coded Level
			−2	−1	0	1	2
Solvent conc.	wt%	A	0	20	40	60	80
Extraction temp.	°C	B	30	40	50	60	70
Solid loading	g/L	C	50	75	100	125	150
Amplitude	%	D	20	40	60	80	100

lists the extraction parameters selected as a major factor of the process.

The designed 30 conditions for RSM modeling are listed in Table 1. The volume of extraction solvent was fixed at 10 mL, and extraction was performed in a 50 mL plastic tube. All extractions were performed for 5.0 min. After the extraction, the concentrations of tannin and phenol in the extracts were quantified. These values were represented as tannin and phenol yields (mg/g biomass). The prediction models for tannin yield and phenol yield were developed using the following Equation (5). The meaning of each symbol in Equation (5) is as follows: Y is the response value (tannin yield or phenol yield); X_i and X_j are independent parameters; β₀ is the intercept; β_i, β_ij and β_ii are regression coefficients; ϵ is the error term; and k is the number of independent parameters [45]. The statistical significance of the developed prediction model was tested by ANOVA.

$$Y={\beta }_0+\sum _{i=1}^k{\beta }_i{X}_i+\sum _{i=1}^{k-1}\sum _{i=i+1}^k{\beta }_{ij}{X}_i{X}_j+\sum _{i=1}^k{\beta }_{ii}{X}_i^2+ϵ$$

(5)

3.3. Measurement of Tannin Concentration

The tannin concentration in the extracts was quantified by the Folin–Ciocalteu colorimetric Method. For tannin quantification, 20 μL of the extracts, 900 μL of distilled water, and 25 μL of the Folin–Ciocalteu reagent were mixed. After vertexing, 50 μL of the Na₂CO₃ solution (20%) was added and reacted at 24 °C for 30.0 min. After the reaction, the optical density (OD) of the mixture was measured at 700 nm. The results are expressed as mg tannic acid equivalent per g biomass.

3.4. Measurement of Phenol Concentration

The phenol concentration in the extracts was quantified by the Folin–Ciocalteu colorimetric method. For phenol quantification, 10 μL of the extracts, 790 μL of distilled water, and 50 μL of the Folin–Ciocalteu reagent were mixed and reacted at 30 °C for 8.0 min. After the reaction, 150 μL of 20% Na₂CO₃ (20%) was added and reacted at 25 °C for 1 h. The OD at 765 nm was measured [46]. The results are expressed as mg gallic acid equivalent per g biomass.

3.5. Evaluation of ABTS Cation Radical Scavenging Activity

The ABTS cation radical scavenging activity of the SH extracts was evaluated. The ABTS^•+ solution was prepared by mixing the ABTS solution and 2.45 mM potassium persulfate in a 1:1 ratio and then diluted with methanol to prepare the solution with 1.0 of absorbance at 734 nm. An amount of 50 μL of the sample was added to 950 μL of the ABTS^•+ solution, and the mixture was incubated at 25 °C for 30.0 min. The OD_{734 nm} was measured, and the ABTS radical scavenging activity (%) was calculated using the following Equation (6). The results were expressed as IC₅₀ (μg/mL), which is the concentration required to scavenge 50% of the ABTS cation radicals.

$$\mathrm{ABTS}\mathrm{cation}\mathrm{radical}\mathrm{scavenging}\mathrm{activity}(\%)=1-{\displaystyle \frac{\mathrm{O}\mathrm{D}734\mathrm{n}\mathrm{m}\mathrm{o}\mathrm{f}\mathrm{s}\mathrm{a}\mathrm{m}\mathrm{p}\mathrm{l}\mathrm{e}}{\mathrm{O}\mathrm{D}734\mathrm{n}\mathrm{m}\mathrm{o}\mathrm{f}\mathrm{c}\mathrm{o}\mathrm{n}\mathrm{t}\mathrm{r}\mathrm{o}\mathrm{l}}}$$

(6)

3.6. Culturing of L929 Fibroblast Cells

The mouse lung fibroblast cell L929 was procured for European Collection of Cell Cultures (ECACC 85011425). The cells were cultured with Dulbecco’s modified Eagle medium (DMEM) containing 10% (v/v) fetal bovine serum, 100 U/mL of penicillin, 100 μg/mL of streptomycin, and 250 ng/mL of amphotericin B in a 5% CO₂ incubator at 37 °C.

3.7. WST-1 Assay for Cytotoxicity Evaluation

The effect of the extracts on cell viability was determined by a WST-1 assay using a Viability Assay Kit (CELLO MAX TM, Anyang-si, Gyeonggi-do, Republic of Korea). For the assay, 100 μL of DMEM containing 1 × 10⁴ cells/well was dispensed into a 96-well plate and incubated in a 5% CO₂ incubator for 24 h. After incubation, 1% of deionized water (as a control group) or the extracts diluted with deionized water was added to each well at 1% of the medium volume to reach 0.25–1.5 mg/mL and incubated in a 5% CO₂ incubator for 48 h. Then, 10 μL of the WST-1 reagent was added to each well and incubated for 4 h, and the absorbance (A) was measured at 450 nm using a microplate reader (BIO-TEK, Los Angeles, CA, USA). Cell viability was determined using Equation (7).

Cell viability (%) = A₁/A₀ × 100

(7)

where A₀ and A₁ are the absorbance of the control and experimental groups, respectively.

3.8. Statistical Analysis

All experiments were performed in triplicate, and all data are presented as mean ± standard deviation. The data related to the time profiling experiment and cytotoxicity evaluation were subjected to an analysis of variance (ANOVA) using SPSS Statistics 27 software (IBM-SPSS Inc., Chicago, IL, USA). The significant difference between each group was tested using Tukey’s test at 95% significance.

4. Conclusions

In this study, highly antioxidant and non-toxic bioactive extracts were successfully produced from SH in a high yield through response surface modeling and optimization of the ultrasound-assisted extraction process. In the RSM study, prethanol A concentration, extraction temperature, and solid loading were determined to be parameters that had a statistically significant effect (p < 0.05) on tannin yield or phenol yield. The RSM model-based optimization and time profiling studies maximized tannin yield and phenol yield from SH (15.88 mg and 14.55 mg per g biomass, respectively). The SH extracts, rich in tannins and phenols, showed a high antioxidant capacity (IC₅₀: 79.86 μg/mL, 68% compared to ascorbic acid), demonstrating its high potential as a natural antioxidant. Moreover, the SH extracts were non-toxic to normal L929 fibroblast cells up to high concentrations (1.5 mg/mL), making it a suitable material for applications such as food and cosmetics. The ultrasound-assisted extraction process developed in this study can be used as basic data for future scale-up and is expected to be one of the ways to sustainably utilize SH. For various industrial applications of SH extracts, biological activities other than antioxidant properties will be evaluated and formulation studies of the extracts will be conducted.