Antioxidant Activity of Zingiber officinale R. Extract Using Pressurized Liquid Extraction Method

Abstract

Global food demand is rising, leading to increased food waste, which contains underutilized bioactive compounds. The Pressurized Liquid Extraction (PLE) method employs high temperature and pressure to maintain the solvent in a liquid state above its boiling point, thereby minimizing extraction time and solvent usage. Ginger waste is known to contain bioactive compounds with significant antioxidant activity. We aimed to assess the effect of temperature, time, and particle size on the total phenolic content (TPC) and antioxidant activity (AA) of ginger (Zingiber officinale R.) waste aqueous extract using the PLE method. A Box–Behnken design with 16 runs was employed. Each extraction utilized 40 g of the sample and was conducted at a constant pressure of 20 bar with a solvent ratio of 27:1 mL/g. Data analysis was performed with Minitab^® 19.1 (64-bit). TPC ranged from 10.42 to 14.1 mg GAE/g, and AA ranged from 72.9 to 111.9 μmol TE/g. The model explained 81.07% of AA’s total variability. Positive correlation was found between TPC and AA (Pearson’s ρ = 0.58, p < 0.05). The optimized extraction conditions were a temperature of 126 °C, an extraction time of 38 min, and a particle size between 355 and 500 μm. Temperature significantly influenced AA (p < 0.05), while time and particle size were not significant factors. To enhance future research, conducting nutritional and functional studies on the extracted compounds would provide valuable insights. Lastly, evaluating the economic feasibility of using PLE for ginger waste valorization should be considered to support its commercial application.

1. Introduction

Global food industry generates approximately 1.6 billion tons of food waste annually, creating significant economic, environmental, and social impacts [1,2]. Despite the food system’s success in increasing per-capita food supply by over 30% since 1961, this growth has led to substantial waste and by-products, posing ethical, social, economic, and environmental challenges. Addressing food waste is crucial, as it can be repurposed as natural sources of bioactive compounds, organic fertilizers, animal feed, biopesticides or bioplastics [3]. Therefore, due to the significant global impact of the increasing demand for food, a larger volume of food waste is generated; however, these wastes are not properly utilized.

Ginger (Zingiber officinale Roscoe), a member of the Zingiberaceae family, has many biologically active compounds with antioxidant properties. Gingerols, shogaols, and zingerone were found in ginger waste [4]. In 2016, the global ginger production reached 3.3 million tons, resulting in a substantial volume of ginger waste generated by industry [5]. Ginger waste is typically either burned, discarded in landfills, or processed into ginger waste meal, which serves as a low-quality feed for animals [4].

Ginger is renowned for its bioactive compounds, including phenolic compounds, which exhibit potent antioxidant activity [6]. Antioxidants present in ginger waste can help shield the body from oxidative stress and reduce the risk of chronic diseases such as cancer, diabetes, and heart conditions. Notably, ginger peels demonstrate higher antioxidant activity compared to the root, leaf, and stem of the ginger plant [4]. Oxidative stress, primarily caused by reactive oxygen species (ROS), can damage nucleic acids, proteins, and lipids, leading to diseases such as cancer and aging [7]. Phenolic compounds play a crucial role in plant defense and human health owing to their antioxidant properties [8,9]. They help prevent lipid and protein oxidation and protect against microbial activity, thereby extending the shelf life of food and beverages [2,10]. Given the increasing preference for natural antioxidants over synthetic ones due to carcinogenic concerns [11], exploring effective extraction methods for these bioactive compounds is of great interest. Polyphenols are traditionally extracted using solvents like water, methanol, ethanol, or their mixtures [8,9].

A particular extraction method from PLE is Subcritical Water Extraction (SWE) method. SWE emerges as an extraction method that employs liquid water under temperatures between 100 °C and 374 °C and high-pressure conditions, enhancing mass transfer rates, absorption into the particle matrix, and selectivity [12]. Under these conditions, water’s properties shift, resembling non-polar solvents like acetone, ethanol, or DMSO, significantly reducing its dielectric constant and increasing its diffusivity [6]. This distinct property of subcritical water enables it to be used as the sole extraction fluid, eliminating the need for any co-solvents like acids, alkalis, catalysts, or organic solvents [8]. These changes promote faster and higher-yield extractions [13]. SWE has been widely recognized for its effectiveness in extracting various bioactive compounds from plant-based raw materials [14]. SWE’s advantages include short extraction times, minimal downstream processing, solvent recyclability, the non-requirement of catalysts, and the preservation of functional groups [15]. Thus, SWE offers high selectivity, high extraction efficiency, low economic costs, sustainability and a reduced environmental footprint compared to traditional extraction methods [16,17,18,19]. Furthermore, response surface methodology (RSM) can optimize the extraction process, reducing the number of experiments, solvent usage, and saving time, while also revealing the relationships between experimental factors and responses [20].

Thus, the study aimed to evaluate the effect of temperature, time, and particle size on the antioxidant activity of ginger (Zingiber officinale R.) waste extract through the PLE method. This research seeks to address the growing demand for natural antioxidants, leveraging green extraction techniques to minimize environmental impact and maximize the yield and efficiency of antioxidants compound extraction from ginger.

2. Materials and Methods

2.1. Materials

Raw materials and supplies included powdered ginger peels processed from fresh ginger purchased in a local supermarket located in 02804 Chimbote, Peru. The reagents used were chromatographic grade methanol (J.T. Baker, Radnor, PA, USA), gallic acid monohydrate ≥ 98.5% ACS (Sigma-Aldrich, Shanghai, China), 2,2-diphenyl-1-picrylhydrazyl (DPPH) 95% (Alfa Aesar, Karlsruhe, Germany), 6-hydroxy-2,5,7,8-tetramethylchroman-2-carboxylic acid (Trolox) 97% (Sigma-Aldrich, Shanghai, China), sodium carbonate, Folin–Ciocalteu reagent, and distilled water (ρ = 0.9982 g/cm³).

Common-use materials comprised 4% sodium hypochlorite (bleach), kitchen knives, potato peelers, latex gloves, aluminum foil, paper towels, harvest crates, buckets, volumetric pitchers, zip-lock bags, food cooler boxes, porcelain supports, metal spatulas, 250 mL glass containers, steel knives, coolers, gel packs, and permanent markers.

2.2. Instruments

The equipment utilized throughout the procedural and analytical stages of the research included the following: a multisolvent extractor (Top Industrie, series 2802.0000, Vaux-le-Pénil, France), a sonicator (VWR International, SymphonyTM, 97043-942, Shanghai, China), a spectrophotometer (Perkin Elmer^®, LAMBDA 950, San Diego, CA, USA), an analytical balance (Ohaus^®, Discovery DV 214C, Aesch, Switzerland; RADWAG, model PS 6000.R2, Radom, Poland), a water bath (Thermo Scientific™, AquaBath™, Waltham, MA, USA), a muffle furnace (Thermolync, Type 1300 Furnace, Arlington, MA, USA), a convection oven (POL-EKO, SLW 115, Wodzisław Śląski, Poland), a water purifier (Thermo Scientific™, Barnstead Nanopure^®, model D 11911, Waltham, MA, USA), a tube shaker (Thermolyne, model 16700 Maxi-Mix I, Boston, MA, USA), a magnetic stirrer (IKA, C-MAG HS 7, Campinas, Brazil), and an electric sieve (RICELI, motor ½ HP, Lima, Peru).

The laboratory instruments included magnetic bars, 10 mL and 20 mL graduated cylinders, 125 mL and 250 mL volumetric flasks, crucibles, 10 mL and 50 mL volumetric pipettes, Petri dishes, micropipettes (100 μL, 250 μL, 500 μL, 1000 μL, and 5000 μL), mortars, Whatman No. 40 filter paper (90 mm), pipettes, 250 mL and 500 mL graduated cylinders, 500 mL precipitation tubes, test tubes, vials, and flasks.

2.3. Sample Preparation and Characterization

The sample preparation process included washing raw material, sanitizing, cutting, drying, grinding and sieving (see Figure 1).

2.3.1. Raw Material

A total of 60.00 kg of fresh ginger rhizomes, uniform in size, color, and maturity, were purchased from the Plaza Vea supermarket in Chimbote, Santa Province, Ancash (UBIGEO 21801, latitude-9.07444, longitude-78.5936). Processing and sample preparation were conducted in the Microbiology and Toxicology Laboratory at the National University of Santa.

2.3.2. Washing and Sanitizing

The fresh ginger rhizomes were washed to remove impurities and then immersed in a chlorinated solution at a concentration of 150 ppm for 10 min to reduce the microbial load. Afterward, the raw material was placed on paper towels to remove any residual aqueous solution.

2.3.3. Cutting and Drying

The rhizomes were then cut and peeled using a conventional potato peeler, aiming to obtain peels with uniform thickness and size to facilitate drying. The yield at this stage was 19.40%, producing 11.64 kg of ginger peels. Then, the ginger peels were subjected to a drying process in a convection oven (POL-EKO, SWL 115, Poland) at 60 °C for 12 h. The process was carried out at 60 °C. The final weight of the peels after this procedure was 3274.60 g, representing a yield of 5.46% relative to the initial weight of the raw material.

2.3.4. Grinding and Sieving

The grinding process was carried out for 5 min using a mill with a 3 mm mesh screen. The purpose was to achieve a ground product with a relatively homogeneous particle size close to the desired size, and to minimize losses in the subsequent sieving process. The powder was then sieved through ASTM #45, ASTM #35, ASTM #20, and ASTM #10 mesh sieves. Seventeen samples of approximately 100 g were fractionated using an analytical balance (Ohaus^® Discovery DV 214C, Switzerland). Then, the sample was vacuum-packed, labeled, and stored at 4 ± 1 °C.

2.3.5. Characterization

Proximal analysis was performed using 100 g of the sample at the Laboratorio de Química, Instituto Tecnológico de la Producción (ITP) located in Ventanilla, Callao, 07046 Peru. The analyses included the determination of moisture (FAO, Food and Nutrition Paper pp. 205 T 14/7, 1986), crude fat (LABS-ITP-FQ-003-2009, Rev. 00, 2009), crude protein (LABS-ITP-FQ-001-2009, Rev. 00, 2009), and ash (Food and Nutrition Paper pp. 228 T 14/7, 1986).

2.4. Pressurized Liquid Extraction (PLE)

This procedure was carried out using a multi-solvent extractor with a capacity of 1.70 L (Top Industrie series 2802.0000, France), following the methodology described by Barriga-Sánchez and Rosales-Hartshorn [21].

2.4.1. Step 1: Loading the Extraction Cell in the Extractor

For each extraction run, the extraction cell—a detachable hollow unit—was loaded with alternating layers of the sample (solute) and 5 mm glass microspheres. Approximately 40 g of the sample was distributed into four layers of 10 g each, interspersed with five layers of glass microspheres (totaling 525 g). The extraction cell was then placed into the apparatus and filled with approximately 1080 mL of solvent, as specified by the manufacturer (see Figure 2). The solvent used was sonicated distilled water. Sonication conditions were 30 min at 25 °C in a sonicator (VWR International, SymphonyTM, 97043-942, China).

2.4.2. Step 2: Establishing Operation Conditions

The control software of the equipment allowed for the establishment of the desired temperature (°C), and pressure. The pressure was 20 bar and constant in all experiments. The general procedure consisted of programming the preheater (coil type) and reactor temperature according to the conditions of each run of the experimental design.

2.4.3. Step 3: Operation Control

From the equipment’s software, once the operating parameters were configured, the equipment was allowed to reach appropriate temperature and pressure conditions, verifying this information from the sensors and the software graphs. The operation time was manually controlled.

2.4.4. Step 4: Extract Discharge

Upon completion of the extraction time (for each of the experimental runs), the extract was discharged and cooled in an ice bath for 10 min. Each aqueous extract was stored at 4 ± 1 °C until further analysis.

2.5. Total Phenolic Content (TPC) Assay

TPC were determined using a modified Singleton et al. [22] method. A gallic acid calibration curve was prepared, and samples reacted with Folin reagent and sodium carbonate. Absorbance was measured at 750 nm using UV–VIS spectrophotometry. The results were expressed as mg GAE/g of sample based on the calibration curve.

2.6. Antioxidant Activity (AA) Assay

AA was measured using the DPPH method modified from Brand-Williams et al. [23] and Kim et al. [24]. A DPPH solution and a calibration curve with Trolox were prepared, with absorbances measured at 518 nm using UV–VIS spectrophotometry. Subsequently, the sample solutions were prepared and diluted, with absorbances recorded after 60 min. The results were calculated in μmol ET/g of the sample, based on the calibration curve.

2.7. Experimental Design

A Box–Behnken 3³ design with four center points and 16 runs was created using Minitab^® 19.1 (64-bit). The design included the following three independent variables (factors): temperature (100–130 °C), extraction time (15–45 min), and particle size (A, B and C, according to <355–500>, <500–850> and <850–2000> μm, respectively). High-temperature (between 100 °C and 374 °C) and high-pressure conditions enhances mass transfer rates, absorption into the particle matrix, and selectivity [12]. The response variables were TPC (mg GAE/g sample) and AA (μmol TE/g sample) from aqueous extracts of ginger peel powder.

2.8. Greenness Character and Applicability of the Method

To assess the greenness and applicability of the method, two established tools, AGREE [25] and BAGI [26], were employed. The AGREE analysis indicates the alignment of the method with green analytical chemistry principles. Additionally, the BAGI tool evaluates the balance between green chemistry and method applicability.

2.9. Data Analysis

An analysis of variance (ANOVA) was used to evaluate the effect of factors on the response variables. Then, standardized effects, response surface diagrams, and correlating response variables with Pearson’s product–moment test were performed. Minitab^® 19.1 (64-bit) software was used for analysis.

3. Results

3.1. Material Characterization

The characterization of dried ginger peel powder brought the following results: the total carbohydrate content was 64.08%, the moisture content was 11.25%, the ash content was 10.69%, the crude fat content was 7.62% and the crude protein content was 6.36%.

3.2. Extraction, TPC, and AA Assay Results

The pressure was set at 20 bar and the average volume of extracts obtained from experimental procedures was 867.0 ± 18.6 mL.

Table 1. Assay results.

Sample Extracts	Sample Material (g)	Water Volume (mL)	S/F (g/g)	Conditions			Yield (%)	Responses 2
				Temperature (°C)	Time (min)	Particle Size (μm) 1		TPC (mg GAE/g Sample)		AA (μmol TE/g Sample)
M1	40.02	1092	27.24	100	15	B	3.66	10.84	11.28	117.46	117.90
M2	40.06	1088	27.11	115	30	B	3.68	11.27	10.89	111.94	112.02
M3	40.01	1091	27.22	115	30	B	3.67	12.43	12.76	106.70	104.83
M4	40.01	1083	27.02	100	30	C	3.69	10.29	10.42	89.80	89.53
M5	40.04	1095	27.30	115	30	B	3.66	12.16	12.32	98.19	98.87
M6	40.02	1083	27.01	115	45	A	3.70	13.22	13.45	107.85	109.16
M7	40.01	1110	27.69	130	30	A	3.60	13.73	14.10	106.52	106.12
M8	40.03	1057	26.36	130	15	B	3.79	12.68	12.36	91.83	91.66
M9	40.00	1093	27.28	115	45	C	3.66	12.53	12.23	94.33	93.99
M10	40.07	1083	26.98	115	15	A	3.70	12.06	12.40	90.98	95.68
M11	40.01	1081	26.97	130	30	C	3.70	12.93	12.79	90.36	90.26
M12	40.01	1081	26.97	100	45	B	3.70	10.95	11.02	72.88	72.30
M13	40.02	1096	27.34	115	30	B	3.65	13.06	12.61	88.12	88.80
M14	40.06	1083	26.99	115	15	C	3.70	10.96	11.08	78.60	79.07
M15	40.07	1082	26.95	130	45	B	3.70	12.90	13.07	88.79	89.72
M16	40.03	1110	27.68	100	30	A	3.61	10.40	10.85	73.95	73.34

¹ Retained powder (μm): 355 < size A < 500; 500 < size B < 850; 850 < size C < 2000. ² Duplicate measures.

shows extract volume according to each sample out of 16.

3.3. ANOVA of TPC and AA Responses

The values of R² and adjusted R² for TPC were 92.15% and 79.58%, respectively. The values of R² and adjusted R² for AA were 81.07% and 50.78%, respectively. The ANOVA showed that the variation in the temperature had a significant effect (α = 0.05) on the TPC and AA values (see

Table 2. ANOVA results of TPC and AA.

Variation Source	TPC		AA
	Contribution	p	Contribution	p
Model	92.15%	0.02	81.07%	0.15
Lineal	89.12%	0.01	38.69%	0.15
Temperature	61.88%	0.00	23.14%	0.03
Time	10.99%	0.07	9.23%	0.12
Particle	16.25%	0.06	6.32%	0.59
Quadratic	1.70%	0.61	24.80%	0.12
Temperature*Temperature	1.68%	0.35	14.35%	0.07
Time*Time	0.02%	0.93	10.45%	0.16
Two-factor interaction	1.33%	0.68	17.58%	0.19
Temperature*Particle	1.33%	0.68	17.58%	0.19
Error	7.85%	-	18.93%	-
Lack of fit	0.57%	0.89	4.21%	0.69
Pure error	7.29%	-	14.73%	-
Total	100.00%	-	100.00%	-

).

3.4. Graphical Analysis of TPC and AA Responses

Figure 3 shows a Pareto chart used to determine the magnitude and importance of the effects in the model. In the displayed charts, the bars that cross the reference line (2.57) are statistically significant. Therefore, temperature is significant with the current model terms for TPC and AA.

Figure 4 shows the main factors effects on TPC and AA. For TPC, the temperature and time levels have a greater magnitude effect than particle size. Moreover, higher levels of temperature and time and small particle size produced higher AA values. For AA, the temperature and time levels have a greater magnitude of effect than particle size. Intermediate levels of temperature and time are those that maximize antioxidant activity values, while the smallest particle size produced higher antioxidant activity values.

Figure 5 shows the interaction plot for TPC. There was no interaction between factors.

Figure 6 shows the interaction plot for AA. The interaction among the evaluated factors indicates the relationship between particle size and AA depends on temperature. Higher values of temperature and particle size produce lower AA values.

Figure 7 shows 3D surface plots for TPC response at different particle sizes (A, B, and C), where A represents the smallest particle size and C the largest. Particle size A yielded the highest TPC, followed by size B, and lastly size C. Furthermore, increasing the levels of temperature and time enhances the response, regardless of the selected particle size.

Figure 8 shows 3D surface plots for AA response at different particle sizes (A, B, and C), with A being the smallest particle size and C the largest. Particle size A yielded the highest antioxidant activity, followed by size B, and lastly size C. All plots depict a response surface with a single maximum.

3.5. TPC and AA Correlation

A positive and significant correlation between TPC and AA responses was found (see

Table 3. Pearson correlation output.

Response 1	Response 2	ρ	95% CI	p
TPC	AA	0.58	(0.07; 0.85)	0.03

).

3.6. Response Optimization

The optimized values for temperature and time factors were 126.36 °C, 37.73 min, and a particle size of <355–500> μm. Adjusted values show that the model predicts a TPC value of 112.44 and an AA value of 14.20. However, the standard error of the fit is higher for TPC compared to AA, indicating that the TPC predictions are less precise. The confidence and prediction intervals for TPC are also wider than those for AA, suggesting greater variability and uncertainty in the TPC estimates. This is further reflected in the broad prediction interval for TPC, which indicates a significant range in potential future observations (see

Table 4. Multiple response optimization.

Response	Fit	SE Fit	95% CI	95% PI
TPC	112.44	6.77	(95.03; 129.85)	(84.30; 140.58)
AA	14.20	0.38	(13.23; 15.17)	(12.64; 15.76)

).

3.7. AGREE and BAGI Evaluation

The AGREE analysis resulted in a score of 0.61, indicating moderate alignment with green analytical chemistry principles. Additionally, the BAGI tool produced a score of 75.0, demonstrating a good balance between green chemistry and method applicability. (see Figure 9). These results highlight the method’s potential for sustainable use while maintaining practical effectiveness.

4. Discussion

In terms of the experimental factors, previous studies highlight the critical role of temperature in the extraction of phenolic compounds and antioxidant activity in plant extracts. Temperature influences both the solubility of these compounds and the diffusion rate of solutes within the solvent [6,27,28]. Furthermore, Siti Nur Khairunisa et al. [29] underscore that maintaining appropriate pressure is crucial to ensuring that water remains in its liquid state during the extraction process. Regarding extraction time, Nourbakhsh Amiri et al. [27] indicate that excessive durations can lead to a reduction in bioactive compound yield due to their instability at elevated temperatures. As for particle size, smaller particles increase the contact surface area between solute and solvent, thereby enhancing extraction efficiency. However, if the particle size is too small, it may lead to channeling effects, which could hinder mass transfer [27,30].

In terms of valorizing Zingiber officinale, ginger peels demonstrate antioxidant properties that may surpass those of conventional synthetic antioxidants [31]. Mao et al. [32] highlighted that the health benefits of ginger are primarily attributed to its phenolic compounds. Additionally, numerous researchers have carried out studies on Zingiber officinale Roscoe [33,34,35,36,37] and other ginger species, including Zingiber zerumbet [29,38,39], Zingiber montanum [40], Zingiber officinale rubrum, and Zingiber officinale amarum [35]. The primary contribution of this work, compared to previous studies on ginger, lies in the evaluation of the phenolic content and antioxidant activity of Zingiber officinale peel extract using the PLE method with water as the sole solvent. While previous studies have emphasized the health benefits of ginger due to the presence of phenolic compounds, few studies have addressed the valorization of ginger residues, specifically peels, using sustainable techniques like PLE. Furthermore, although numerous authors [33,34,35,36,37] have explored the antioxidant activity of ginger and other related species, this study provides an optimization of the extraction process in terms of temperature and time, improving both efficiency and solvent usage, which represents a significant advance in the valorization of food industry by-products.

Regarding the results obtained from other ginger varieties, Mahmudati et al. [35] reported a maximum TPC value of 22.97 mg GAE/g using the decoction method for Zingiber officinale var. rubrum. Additionally, the highest antioxidant activity observed was 79.83% inhibition, as measured by the DPPH method through the infusion process. Various authors have also experimented with different raw materials. Barriga-Sánchez and Rosales-Hartshorn [21] analyzed extracts from cherimoya leaves (Annona cherimola Mill), obtaining a maximum TPC of 5.6 g GAE/100 g of dry leaf using hot water extraction under high pressure and temperature (130 °C). However, the highest antioxidant activity observed was 0.86 mg TE/mg of dry ethanolic extract (70% v/v). Similarly, Sánchez-Gonzáles et al. [30] studied grape seeds (Vitis vinifera), achieving antioxidant activity values of 1628.15 ± 80.32 μmol TE/g dry weight through the PLE method.

However, the quantification of TPC and AA is highly dependent on the extraction method and conditions employed. Several authors have utilized the PLE method [21,29,30,37,38,39,41], while ultrasound-assisted extraction has also been widely applied [33,34,36,40]. Additionally, infusion and decoction techniques [35], as well as organic solvent extraction [21,30,34,38], have been used in various studies. Regarding findings from previous studies using the PLE method, Razak et al. [37] reported AA values of 71.46 ± 2.44% inhibition. Similarly, Siti Nur Khairunisa et al. [39] observed maximum AA values of 63.26% inhibition at 170 °C, with an extraction time of 20 min and a solvent-to-sample ratio of 20 mL/g for Zingiber zerumbet. These results can be explained because the PLE method enhances mass transfer rates, absorption into the particle matrix, and selectivity [12].

On the other hand, using the ultrasound-assisted extraction method, Murphy et al. [36] reported a maximum TPC value of 1039.64 mg GAE/g dry weight and AA values of 54.50% in ethanolic extract. Similarly, Contreras-López et al. [33] achieved maximum TPC values of 17.11 mg GAE/100 g and AA values of 157.15 mg TE/100 g. Additionally, in extracts of Zingiber montanum, Thepthong et al. [40] obtained a maximum TPC of 71.45 ± 1.45 mg GAE/g in methanolic extract and a maximum AA value with an IC₅₀ of 38.89 ± 0.27 μg/mL in ethanolic extract.

Similarly, Jorge-Montalvo et al. [34] obtained higher TPC values using the maceration method, reporting 10.03 ± 0.14 mg GAE/g sample (25 °C for 24 h). Higher AA values were achieved using the reflux method, with an IC₅₀ of 0.72 ± 0.05 mg dry matter/mL (85 °C for 12 h). Conventional methods, however, often face challenges such as extended extraction times and significant solvent loss. In contrast, the PLE method offers a faster, less polluting, and more cost-effective alternative.

Regarding the results obtained from the statistical analysis, findings similar to those of Siti Nur Khairunisa [29] were observed, where a fractional factorial design indicated that temperature was the significant factor, contributing 38.36%. Yulianto et al. [41] also identified temperature as a significant factor in the extraction process using a central composite design. In this study, the application of the Box–Behnken design to optimize extraction conditions represents a noteworthy innovation aimed at maximizing antioxidant activity, with potential industrial applications. The significant positive correlation between total phenolic content and antioxidant activity further emphasizes the relevance of this by-product as a viable source of natural antioxidants, which may surpass the use of synthetic antioxidants in various industrial contexts [11].

Despite the promising results, the study faced several limitations related to the extraction equipment employed. The thermal fragility of certain components necessitated restrictions on the operational conditions, capping the maximum operating temperature at 130 °C. This limitation hindered a comprehensive investigation of temperature effects across a broader range. Furthermore, the presence of starch in the dried ginger rhizome led to the formation of a cake, which impeded the complete recovery of the operating water volume and consequently reduced the extract yield (w/v). Therefore, these factors should be carefully considered when designing future experiments.

This article enhances the scientific understanding of extracting bioactive compounds from ginger by demonstrating the effectiveness of utilizing the PLE method. It establishes a foundation for future research and applications within the pharmaceutical and food industries, particularly for developing supplements and functional foods. This approach also supports the valorization of agricultural by-products and the creation of high-value natural products. Moreover, by employing water as the sole extraction solvent, we promote a sustainable and pollution-free industry.

5. Conclusions

Considering that temperature was found to be the significant factor in the extraction process and acknowledging that temperature constraints were a limiting factor in this research due to equipment operational conditions, further studies are recommended to optimize temperature for the extraction of bioactive compounds with antioxidant activity. Additionally, the precise control of storage conditions is advised to maintain the stability of sample composition and preserve product quality for subsequent analysis.

The continuous monitoring of these parameters is suggested to ensure consistency and quality in future experiments. Although particle size was not significant, further investigation into its impact could provide insights and potential improvements in extraction efficiency.

Finally, future directions could include more detailed investigations into the compounds and toxicity of the extracts, as well as sensory and nutritional studies to evaluate the impact on food products. Additionally, exploring other parameters in the PLE method could provide additional insights and improve extraction efficiency.