**1. Introduction**

Since ancient times, the onion (*Allium cepa* L.) has been one of the most important vegetable crops and it is the world's second most developed agricultural crop after the tomato. Onions are grown in various shapes, colors, sizes, and pungency to fulfill specific culinary and nutritional needs and have become a nearly universal ingredient in food preparation worldwide [1]. Onion production has grown over the last decade and it now reaches about 98 million tons around the world. More than 550,000 tons of byproducts (onion skins) are produced yearly, causing various biological and environmental problems [2]. Valorization is widely applied to managing agro-industrial by-products, in which by-products are considered valuable secondary raw materials with potential functional constituents for developing value-added products [3]. Onion by-products have been an intriguing challenge for researchers aiming to create efficient reuse strategies for its bioactive compounds due to onion increased production and a relatively substantial amount of generated by-products without acceptable disposal.

Onion by-products have generally been recognized as a source of non-structural carbohydrates, dietary fibers, polyphenols, and flavor compounds. Bioactive compounds such as phenolics, flavonoids, and anthocyanins are abundant in red onions and their dry outer layers. Their quantities in the skin of red onion are higher than in the edible

**Citation:** Stoica, F.; Constantin, O.E.; St ˘anciuc, N.; Aprodu, I.; Bahrim, G.E.; Râpeanu, G. Optimization of the Parameters Influencing the Antioxidant Activity and Concentration of Anthocyanins Extracted from Red Onion Skins Using a Central Composite Design. *Inventions* **2022**, *7*, 89. https:// doi.org/10.3390/inventions7040089

Academic Editor: Monique Lacroix

Received: 6 September 2022 Accepted: 28 September 2022 Published: 3 October 2022

**Publisher's Note:** MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

**Copyright:** © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).

81

portion because of their preventive properties against soil microorganisms [4]. The phenolic compounds in the red onion skin mainly consist of flavonoids. They include two main groups, namely, flavonols (such as quercetin, kaempferol, and its glucoside derivatives) and anthocyanins (especially cyanidin derivatives) [5]. Flavonols are generally found in glycosylated forms; the two most frequent quercetin forms in red onion skin are quercetin 4 -O-*β*-D-glucoside and quercetin 3,4 -O-*β*-D-diglucoside, which account for 80–85% of the total flavonoid content [1]. Cyanidin 3-glucoside is the major anthocyanin found in red onion skin. Smaller quantities of cyanidin 3-laminaribioside, peonidin, and pelargonidin glucosides are also present [6]. Red onion skins may be a source of natural colorants that can be extracted using various methods and utilized in foods as a substitute for synthetic compounds. These red onion skins can be a natural, low-cost, and widely available source of beneficial ingredients, including antioxidants [7].

Anthocyanins form an important group of water-soluble plant pigments and are used as food colorants. Additionally, anthocyanins have health-promoting effects such as anti-cancer, anti-inflammatory, antidiabetic, anti-obesity, and enzyme inhibitory effects, contribute to the prevention of cardiovascular disease, and have powerful antioxidant properties [8].

Different methods have been used to obtain phytochemicals, and extraction is the most important stage in providing bioactive compounds. Developing effective extraction procedures is crucial to improve the extraction of valuable compounds in terms of cost-effectiveness and environmental friendliness. The principal elements to consider in extraction processes include matrix properties, solvent selection, temperature, liquid-tosolid ratio, pressure, and extraction time. The most common method for the extraction of bioactive compounds is solvent extraction (such as extraction based on ethanol and methanol) [9].

Solvent extraction is used to increase the extraction efficiency, extraction time, extraction quality, and solvent consumption. Anthocyanins are more soluble in polar solvents than in non-polar solvents. In addition, because anthocyanins are unstable in alkaline solutions, highly acidic aqueous solvents are used. Due to the swelling of the tissue walls, adding acid to a solvent enhances the extraction yield [10]. Aqueous ethanol (50 to 75%) is often used to extract flavonoids from onion skin waste. Temperature, extraction duration, and the solvent-to-raw material ratio also affect the extraction of flavonoids from onion skin waste [11].

In the current study, a conventional solvent extraction method with four variable factors was developed (ethanol concentration, citric acid, temperature, and time). Furthermore, a central composite design (CCD) was employed to optimize the extraction technique and enhance the antioxidant activity. Anthocyanins extraction from red onion skin extracts under stirring was also studied for a more efficient solid/liquid extraction of bioactive compounds. This research offers new insights into the impact of conventional extraction methods on and the determination of the optimal extraction conditions for anthocyanin-rich by-products.

#### **2. Materials and Methods**

#### *2.1. Reagents and Chemicals*

HPLC-grade methanol, ethanol, Folin–Ciocalteu reagent, glacial acetic acid, 2,2-diphenyl-1-picrylhydrazyl (DPPH), 6-hydroxy2,5,7,8 tetramethylchromane-2-carboxylic acid (Trolox), gallic acid, potassium chloride, sodium nitrite, sodium hydroxide, sodium bicarbonate, sodium acetate, sodium carbonate, aluminum chloride were obtained from Sigma Aldrich Steinheim (Darmstadt, Germany). All other reagents used in the experiments were of analytical grade.

#### *2.2. Red Onion Skins Preparation*

Red onions were purchased from a local market in Galat,i, Romania. The outer layers of the red onions were collected, washed with ultrapure water, and dried for 2 h at 40 ◦C in a typical oven (Stericell 111, MMM Medcenter, München, Germany) to a moisture content of 11.0%. The red onion skins were powdered (mean particle diameter of 1 mm), stored at room temperature in an airtight glass jar in the dark, and utilized for extraction.

#### *2.3. Conventional Solvent Extraction*

The extraction was carried out using 1 g of red onion skin and 15 mL of ethanol in various concentrations, ranging from 6.36 to 73.63%. The plant material-to-solvent ratio was 1 to 15. Each extraction was acidified with a citric acid solution (ratio 14:1, *v*/*v*), using varying quantities from 0.05 to 2.64%. The extractions were carried out using an orbital shaker (SI-300R Medline Scientific, Chalgrove, UK) at 150 rpm at 16.47–58.52 ◦C for 10 to 234.54 min. The samples were centrifuged for 10 min at 14,000 rpm and 4 ◦C using a Hettich Universal 320R equipment, Germany, and the supernatant was phytochemically examined.

#### *2.4. Determination of the Total Anthocyanins Content (TAC)*

TAC was calculated using the pH differential method with two reagents, i.e., potassium chloride buffer (pH 1.0) and sodium acetate buffer (pH 4.5). The absorbances at 520 and 700 nm were measured using a UV–VIS spectrophotometer (Libra S22, Biochrom, Cambridge, UK).

The total anthocyanin content (TAC) was expressed in mg cyanidin 3-O-glucoside (C3G)/g dry weight (DW) and was calculated according to Equation (1) as described by Lee et al. [12], with slight modifications.

$$\text{TAC}\,\text{mg/g} = \frac{A \times MW \times DF \times Vt}{\varepsilon \times 1 \times \text{M}} \tag{1}$$

where *A* is the difference between (*A*520–*A*700) at pH 1.0 and (*A*520–*A*700) at pH 4.5, *MW* is the molecular weight (449.2 g/mol) of cyanidin-3-glucoside, *DF* is the dilution factor, *Vt* is the total volume (mL), E is the molar extinction coefficient (26,900) of cyanidin-3-glucoside, l is the path length, and M is the weight of red onion skins (g).

#### *2.5. Determination of the Antioxidant Activity (AA)*

The DPPH free radical-scavenging method was used to determine the antioxidant activity, which was expressed as mM Trolox Equivalents (TE)/g DW [13]. To measure the in vitro antioxidant activity, 100 μL of the extract was mixed with 3.9 mL of a DPPH stock solution. The mixture was then kept at room temperature for 30 min in complete darkness. The absorbance was measured at 515 nm, and the results were quantified using a Trolox calibration curve.

#### *2.6. Experimental Design*

The Central Composite Design (CCD) method was used to determine experimentally the antioxidant activity and optimize the TAC in the red onion skins extract. A central component of five factors, three central points, and the design of 21 experimental variants were used in an experimental factorial model. Table 1 shows the maximum and minimum values of the variables explored in the experimental plan in their current and coded forms. In addition, for response variables, the CCD creates a quadratic model.

**Table 1.** Range of values for the factors investigated and encoded values.


A second-order polynomial model (2) can be used to represent the software used to test the experimental conditions:

$$\mathbf{R} = b\_0 + \sum\_{i}^{n} b\_i \cdot \mathbf{x}\_i + \sum\_{i=1}^{n} b\_{ii} \cdot \mathbf{x}\_{ii}^2 + \sum b\_{ij} \cdot \mathbf{x}\_i \cdot \mathbf{x}\_{jd} \tag{2}$$

where R is the predicted response, *b*<sup>0</sup> is the intercept, *bi*, *bii*, and *bij* are the regression coefficients, *xi* and *xjd* are the independent variables analyzed, *n* is the number of factors.

#### *2.7. Statistical Analysis*

In the study, we utilized the statistical software Design Expert (v. 13) from Design-Expert® to examine the experimental model (Stat-Ease, Inc., Minneapolis, MN, USA). All analyses were carried out in triplicate, and the findings are expressed as mean ± standard deviation.

#### **3. Results**

A Central Composite Design (CCD) and surface response modeling were utilized to establish the ideal parameters for optimizing the extraction process. Additionally, the content of anthocyanins and the antioxidant activity were determined. The complete CCD matrix used to optimize the principal variables evaluated and the corresponding values are shown in Table 2.


**Table 2.** Actual values of the principal variables analyzed in the CCD matrix.

#### *3.1. Influence of the Extraction Parameters on AA*

This research aimed to determine the effect of a suitable optimal pattern of variables on the antioxidant activity of the extract from red onion skins. The antioxidant activity varied from 24.29 to 37.20 mM TE/g DW depending on the values of the various variables (Table 2). According to the variables of the extraction environment, the regression equations developed after the ANOVA explained the antioxidant activity values of the red onion skin extract obtained (Table 3). For the AA, the Model F-value of 112.73 implied the model was significant. In this case, B, C, D, AB, AC, AD, BC, BD, CD, A2, and B2 were significant model terms. According to the regression model used for the DPPH free radicalscavenging potential, the determination coefficient of R<sup>2</sup> was 0.99, indicating that only 0.01 of the variation of the antioxidant activity could not be specified by the current model. The predicted determination coefficient R2 of 0.95 was in reasonable agreement with the adjusted determination coefficient R<sup>2</sup> of 0.98.


**Table 3.** ANOVA for the reduced quadratic model for AA and TAC.

Sum of Squares—SS; Mean Square—MS; <sup>a</sup> Significant; <sup>b</sup> Not significant.

After eliminating the minor model terms, a model reduction was accomplished. Equation (3) illustrates the model equation for the relationship between the antioxidant activity (R1) and the variables in coded units.

$$\text{R1 (AA)} = +26.92 + 2.41 \text{B} - 0.345 \text{AC} + 2.50 \text{D} + 1.37 \text{AB} + 2.41 \text{AD} + 0.5912 \text{BC} + 1.51 \text{BD} - 0.533 \text{CD} - 0.4301 \text{A}^2 \tag{3}$$

$$+ 2.26 \text{B}^2$$

The regression equation's b coefficients showed that the temperature had a minor negative effect on the antioxidant activity. Additionally, the interactions between temperature and time (CD) and temperature (C) and quadratic citric acid concentration (A2) significantly negatively affected the antioxidant activity of the red onion skins extract. Additionally, the antioxidant activity of the extract was enhanced by ethanol concentration (B) and extraction time (D). The interaction between citric acid concentration and ethanol concentration (AB), between citric acid concentration and time (AD), and between ethanol concentration and extraction time (BD) also had a favorable impact on the antioxidant activity. In contrast, citric acid concentration and temperature (AC) and ethanol concentration and temperature (BC) moderately affected the antioxidant activity.

The correlation between the independent and dependent variables was predicted using second-order contour plots (Figure 1A), which were also used to show the synergistic effects of the independent variables on the antioxidant activity of the extract obtained. The three-dimensional response area describes the correlative impact of the chosen parameters on the extract's antioxidant activity.

Figure 1A displays the 3D surface and second-order contour plots for the AA determination. Figure 1A(a,b) show that the ethanol concentration and time influenced the antioxidant activity; AA increased as the citric acid concentration decreased. The maximum antioxidant activity could be attained at a nearly 60% ethanol concentration and about 180 min extraction time. Further, as the plots show, lower extraction times and higher percentages of citric acid led to a decreased DPPH free radical-scavenging potential. Additionally, reducing the temperature and ethanol concentration decreased the red onion skin extract's antioxidant activity (Figure 1A(c)). As shown in Figure 1A(d), the AA increased when the ethanol concentration increased at a constant extraction temperature. Higher temperatures may improve phenolic component solubility, resulting in an AA increase. Still, as temperature and time continued to rise, the extracted phenolic compounds started to degrade and stopped showing AA after reaching equilibrium, reducing AA levels.

**Figure 1.** Second-order contour and 3D surface plots screening the variables' effect on the antioxidant activity (**A**) and extraction yield of anthocyanins (**B**).

The perturbation plot for several parameters illustrates how each element affected the current response (Figure 2a). When analyzing the deviation from a reference point, a slope with a large or curved inclination for a specific factor shows that the response is sensitive to this factor. At the same time, a relatively flat line demonstrates insensitivity to changes in this factor. In the perturbation graph, curve B appeared to be critical in determining AA, indicating that the impact of the ethanol value was very substantial. The curves A and C, corresponding to citric acid and temperature, respectively, indicated a lesser effect of these factors on the extraction than ethanol.

**Figure 2.** Perturbation graphs representing the effect of each independent variable (A, B, C, and D) on AA (**a**) and TAC (**b**) of the red onion skins extract.
