Structural characterization and functional properties of safflower seed protein extracted by natural deep eutectic solvents

Abstract

In this study, betaine-based natural deep eutectic solvents (NADES) were formulated for the extraction of safflower seed protein (SSP). Among the five NADES screened, betaine-glycerol (1:2 M ratio) was identified as optimal, achieving a protein purity of 85.66% and an extraction yield of 56.66%. Using response surface methodology, the extraction yield was further increased to 66.45% ± 0.43% under optimized conditions (29% water content, 52 °C, solid-to-liquid ratio of 1:24). Compared with protein extracted by alkaline solubilization–acid precipitation (AEAP), NADES-extracted SSP exhibited a lighter color, higher α-helix content (23.86%), and lower β-sheet content (34.16%), with better preservation of subunit integrity. Functionally, it demonstrated superior solubility (85.00%), emulsifying activity (93.23 m²/g), and foaming capacity (209.73%) at pH 3.0, along with higher oil-holding capacity. The betaine-glycerol NADES system was therefore established as a green and efficient approach for SSP extraction.

1. Introduction

The continuous growth of the global population, projected by the United Nations to reach approximately 9.7 billion by 2050, has necessitated a heightened demand for high-protein food products (Hadidi et al., 2024). At present, dietary protein in human nutrition has been predominantly sourced from animal-based foods. However, animal protein has been confronted with multiple challenges, including health risks, high production costs, and pressures on resources and the environment. Consequently, the development and utilization of high-quality plant protein resources have been recognized as a critical direction toward achieving a sustainable global food supply. Dietary studies have indicated that the replacement of meat and dairy products with plant-based alternatives not only contributes to improved cardiovascular health (Glenn et al., 2024) but also aids in the preservation of renal function in diabetic patients (Cai et al., 2026). Among the numerous underutilized plant resources, oilseed meals, as by-products of agricultural processing, have demonstrated great potential for high-value utilization within the circular bioeconomy, with safflower seed meal representing a typical example. According to the Food and Agriculture Organization (FAOSTAT), global safflower seed production reached approximately 693,000 t in 2024, generating substantial quantities of safflower seed meal, most of which have been used as animal feed or horticultural fertilizer, thereby offering low added value. Nevertheless, safflower seed meal contains 20–50% protein, positioning it as a promising high-quality plant protein resource. Previous studies have shown that safflower seed protein isolate can be incorporated into various food products, including dough, baked goods, ice cream, desserts, and beverages (Korkmaz & Mutlu, 2025). Therefore, the efficient extraction of protein from safflower seed meal has been considered of great significance for enhancing the comprehensive utilization value of this by-product. For plant-derived proteins to be effectively applied in food systems, their functional properties often need to be improved through appropriate extraction or modification strategies. Currently, the extraction of safflower seed protein has been predominantly carried out using the conventional alkaline solubilization–acid precipitation method, which has been widely adopted owing to its operational simplicity and low cost. However, exposure to strongly alkaline extraction conditions has been reported to induce alterations in the secondary, tertiary, and quaternary structures of proteins, thereby compromising their nutritional quality and functional properties. Moreover, this process has been associated with high water consumption and substantial wastewater discharge, imposing environmental burdens and deviating from the principles of green and sustainable development. Hence, there has existed an urgent need to develop a green extraction technology capable of efficiently recovering safflower seed protein while preserving its native structural and functional integrity.

As a class of emerging eco-friendly solvents, natural deep eutectic solvents (NADESs) have been recognized as possessing significant potential for widespread application across diverse industrial and scientific domains. NADESs are typically formed by mixing a hydrogen bond acceptor (HBA), such as betaine or choline chloride, with a hydrogen bond donor (HBD), such as glycerol, ethylene glycol, or urea, at a specific molar ratio, resulting in a melting point considerably lower than that of the individual components. The raw materials used for NADESs preparation have generally been recognized as inexpensive and readily available, with many components naturally occurring in organisms, thereby rendering them suitable for food-related applications. Among various hydrogen bond acceptors, although choline chloride is widely utilized, its specific functionalities in food systems remain elusive. In contrast, betaine, a vitamin B derivative, has been found to be widely present in plants such as sugar beets and spinach, and has been regarded as a non-toxic and biodegradable by-product of the sugar industry. Furthermore, it functions as a natural methyl donor and osmolyte, offering significant health benefits, particularly in the prevention of fatty liver disease and cardiovascular disorders. Glycerol has been designated as Generally Recognized as Safe (GRAS) by the U.S. Food and Drug Administration, and no acceptable daily intake (ADI) has been established by the Joint FAO/WHO Expert Committee on Food Additives. Previous studies have indicated that NADESs possess several advantages, including high protein extraction efficiency, low toxicity, simple preparation procedures, and wide applicability, thus positioning them as ideal green alternatives to conventional alkaline solubilization–acid precipitation systems (Karabulut et al., 2024). In a study conducted by Karabulut et al., a choline chloride–glycerol system was utilized to extract protein from sunflower seed meal, resulting in enhanced functional properties and retained structural integrity of the recovered protein. (Karabulut et al., 2025). Similarly, a choline chloride-urea system was utilized by Wang et al. for protein extraction from Moringa oleifera seeds, resulting in enhanced recovery and yield, along with improved biofunctional properties (Wang et al., 2026). Collectively, these studies have suggested that NADESs hold considerable promise for the extraction of proteins from oilseed crops.

Although NADESs have been demonstrated to offer advantages in the extraction of various plant proteins, their systematic application to the extraction of safflower seed protein has been rarely reported. Therefore, this study was conducted with betaine as the hydrogen bond acceptor, with which five distinct hydrogen bond donors were separately combined to synthesize NADESs. The optimal extraction system was selected based on protein purity and extraction yield. Subsequently, response surface methodology was employed to optimize the extraction process parameters of the selected betaine-glycerol system. Finally, a systematic comparison was performed among the NADESs-extracted protein, the protein extracted by alkaline solubilization–acid precipitation, and a commercially available soy protein isolate in terms of structural characteristics and functional properties. The present work sought to develop a green and efficient extraction strategy for the value-added utilization of safflower seed meal, serving as a theoretical basis for the targeted application of safflower seed protein in the food industry.

2. Materials and methods

2.1. Materials and chemicals

Defatted safflower seed meal was purchased from Anyang Man Tian Xue Food Manufacturing Co., Ltd. (Anyang, China). Soy protein isolate (SPI, ≥90%), medium-chain triglycerides (MCT), and betaine were sourced from Shanghai Yuanye Biotechnology Co., Ltd. (Shanghai, China). All other chemical reagents employed in this study were of analytical grade.

2.2. Preparation and physicochemical properties of NADESs

Betaine was used as the hydrogen bond acceptor and was separately mixed with five hydrogen bond donors-namely, 1,3-butanediol, ethylene glycol, glycerol, lactic acid, and urea-at a molar ratio of 1:2. The water content was controlled at 20%, and the mixtures were stirred under sealed conditions in a water bath at 80 °C for 2 h to generate homogeneous, transparent liquids. Successful synthesis of the NADESs was confirmed when the liquids remained stable upon cooling to room temperature. Based on the different hydrogen bond donors used, the five obtained NADESs were designated as Bet-BD, Bet-EG, Bet-Gly, Bet-LA, and Bet—U, respectively. The viscosity of each deep eutectic solvent was measured over a temperature range of 30–80 °C using an NDJ-8ST digital rotational viscometer (Shanghai Shuju Instrument Technology Co., Ltd., Shanghai, China). The pH values of the NADESs were determined using an FE28 pH meter (Mettler Toledo, Germany), which was calibrated prior to measurement. Density was determined using an electronic balance with a precision of 0.0001 g, based on 1 mL of each NADES, and the results were expressed in kg/m³.

2.3. Extraction of safflower seed protein by deep eutectic solvents and alkaline solubilization–acid precipitation

NADESs extraction of protein: The procedure described by Cao et al. (Cao et al., 2023) was followed with slight modifications. Safflower seed meal was mixed with each NADES at a solid-to-liquid ratio of 1:20 (g/g) in a beaker, and the mixture was stirred at 60 °C and 750 r/min for 1 h. After cooling to room temperature, the mixture was centrifuged at 5000 ×g for 10 min at 4 °C, and the supernatant was collected. Anhydrous ethanol was added to the supernatant (3:1, w/w), and the mixture was thoroughly blended, followed by standing at 4 °C for 12 h to allow complete protein precipitation. After another centrifugation for 10 min, the supernatant was discarded, and the obtained protein precipitate was washed with cold water and centrifuged. This washing procedure was repeated three times to remove salts, and the final precipitate was freeze-dried. The SSP samples extracted with the five aforementioned NADESs were designated as BBD-SSP, BEG-SSP, BGly-SSP, BLA-SSP, and BU-SSP, respectively.

Alkaline solubilization–acid precipitation extraction of protein: The method described by Kasapoglu and Korkmazwas referenced with minor modifications (Kasapoglu & Acar, 2025; Korkmaz, 2024). Safflower seed meal was mixed with distilled water at a ratio of 1:20 (w/v) in a beaker. The pH was adjusted to 9.5 using 1 mol/L NaOH, and the mixture was stirred at room temperature for 2 h, after which centrifugation was performed at 5000 ×g for 30 min to collect the supernatant. An equal volume of distilled water was added to the remaining precipitate, the pH was readjusted to 9.5, and the extraction was repeated once. The supernatants from both extractions were combined. The pH of the combined supernatant was adjusted to 5.0 with 1 mol/L HCl for protein precipitation. After centrifugation under identical conditions, the resulting precipitate was harvested and subjected to repeated washing with deionized water until neutrality was achieved. The SSP extracted by the alkaline solubilization–acid precipitation method was abbreviated as AEAP-SSP.

2.4. Determination of purity, yield, and extraction yield of safflower seed protein

The soluble protein content was determined using the Bradford method (Balballi & Karabulut, 2025), with bovine serum albumin (BSA) used as the standard for establishing a calibration curve. The resulting regression equation was established as y = 0.0053× + 0.1793, R² = 0.992. The purity, yield, and extraction yield of safflower seed protein were calculated according to the following formulas:

$$\text{Yield}\left(\%\right)=\frac{W_2}{W_1}\times 100\%$$ (1)

$$\begin{array}{c}\text{Extraction Yield}\left(\%\right)=\frac{W_2\times P_2}{W_1\times P_1}\times 100\%\end{array}$$ (2)

where:W₁: mass of safflower seed meal; W₂: mass of safflower seed protein obtained by extraction; P₁: protein content in safflower seed meal; P₂: purity of the extracted protein.

2.5. Appearance and color

Color parameters (L^⁎, a^⁎, b^⁎) of the extracted safflower seed protein were measured using a CR-400 colorimeter (Konica Minolta Business Solutions Co., Ltd., Shanghai, China).

2.6. Single-factor experiment for the extraction of safflower seed protein

The effects of water content (0%–50%), extraction temperature (30 °C–70 °C), and solid-to-liquid ratio (1:10–1:50, g/g) on the extraction yield, purity, and yield of SSP were investigated. For clarification of how the extraction method influenced the structure and functionality of SSP, the protein isolate obtained using the betaine–glycerol system was accordingly termed NADES-SSP.

2.7. Response surface optimization experiment

In accordance with the findings from the single-factor experiments, the experimental conditions were designed employing Design-Expert 13.0 (RSM) software, and the Box-Behnken design model was adopted, with the extraction yield of safflower seed protein serving as the response variable.

2.8. Structural characterization of safflower seed protein

2.8.1. Amino acid composition

The contents of 17 amino acids in the AEAP-SSP and NADES-SSP samples were quantified using an L-8900 automatic amino acid analyzer (Hitachi High-Tech Corporation, Japan). Following acid hydrolysis, the samples were transferred to a rotary evaporator and subjected to vacuum evaporation at 60 °C until dryness. The residues were then reconstituted with 0.05 mol/L HCl, filtered through a 0.22 μm microporous membrane, and transferred into sample vials for subsequent analysis.

2.8.2. SDS-PAGE electrophoresis

The protein samples were separated and analyzed by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). The AEAP-SSP and NADES-SSP protein solutions were prepared at a concentration of 5 mg/mL using SDS sample buffers with or without β-mercaptoethanol, respectively. The samples were heated in a boiling water bath at 100 °C for 6 min and subsequently centrifuged. A sample volume of 6.5 μL was loaded per well. Electrophoresis was performed using a 5% stacking gel and a 12% separating gel. An initial voltage of 100 V was applied; after the samples had entered the separating gel (approximately 20 min), the voltage was increased to 120 V. The gel was stained with Coomassie Brilliant Blue R-250, followed by destaining on a shaker with destaining solution. The destaining procedure was repeated until a clear background was obtained. Gel images were captured using a Molecular Imager Gel Doc XR+ protein nucleic acid gel imaging system (Shanghai, China).

2.8.3. Fourier transform infrared spectroscopy

SPI, AEAP-SSP, and NADES-SSP were employed as the analytical samples. Under a drying lamp, each sample was homogenized with potassium bromide at a ratio of 1:100, ground, and compressed into a pellet. The resulting pellets were analyzed using a Tensor 27 Fourier transform infrared spectrometer (Beijing, China). A potassium bromide pellet served as the background blank. The spectral resolution was maintained at 4 cm⁻¹, with 32 scans accumulated over a scanning range of 400–4000 cm⁻¹.

2.8.4. Thermogravimetric measurement

Each protein sample, with a mass of 2 mg, was weighed and subsequently subjected to heating from 30 °C to 600 °C under a nitrogen atmosphere at a constant heating rate of 10 °C/min.

2.8.5. Interfacial tension and contact angle

Following the method described by Aslan with slight modifications (Aslan Türker, 2025). Interfacial tension and three-phase contact angle were determined using a Theta Lite optical contact angle meter (Stockholm, Sweden). The pendant drop method was employed for interfacial tension measurements. Ultrapure water served as the blank control. The influence of SPI, AEAP-SSP, and NADES-SSP solutions at varying concentrations (0.05%, 0.1%, 0.5%, and 1%) on the interfacial tension at the MCT/water interface was investigated. The tip of a high-precision syringe was immersed into the MCT, and sample droplets were slowly dispensed. Changes in droplet shape were continuously recorded by the instrument, and the interfacial tension was calculated according to the Young-Laplace equation. For three-phase contact angle measurement, the sessile drop method was adopted. The three-phase contact angles of SPI, AEAP-SSP, and NADES-SSP were measured. A 0.3 g aliquot of each protein powder was weighed and compressed into a thin sheet with a thickness of approximately 1 mm under a pressure of 20 MPa, and the sheet was placed in MCT. A 5 μL droplet of ultrapure water was dispensed onto the surface of the sheet using a high-precision syringe, the droplet morphology was recorded, and the contact angle was calculated based on an elliptical fitting model.

2.8.6. Surface hydrophobicity

Surface hydrophobicity of the proteins was determined using the bromophenol blue binding method (Bertsch et al., 2003). The protein samples were prepared as 2 mg/mL solutions in PBS buffers with different pH values, each containing 0.6 M NaCl. A 200 μL portion of 1 mg/mL bromophenol blue solution was combined with 1 mL of the protein solution, followed by vortexing for 30 s, the mixture was centrifuged at 5000 ×g for 15 min. The supernatant was then diluted 10-fold, and the absorbance was measured at 595 nm (A_sample). PBS buffer containing 0.6 M NaCl was used as the control (A_control). Surface hydrophobicity of the proteins was expressed as the amount of bromophenol blue bound, calculated using the following formula:

$$\begin{array}{c}\text{Bromophenol blue bound amount}\left(\mathrm{\mu L}\right)=\frac{\left(A_{\text{control}}-A_{\text{sample}}\right)\times 200}{A_{\text{control}}}\end{array}$$ (3)

2.9. Functional properties of safflower seed protein

2.9.1. Solubility determination

Following the method of Balballi et al. (Balballi et al., 2025) with slight modifications, a protein solution of 0.25 mg/mL was prepared, mixed with Bradford reagent, and the absorbance was measured at 595 nm using a UV–visible spectrophotometer.

$$\begin{array}{c}\text{Solubility}\left(\%\right)=\frac{\mathbf{Soluble\; protein\; content}}{\mathbf{Total\; protein\; content}}\times 100\%\end{array}$$ (4)

2.9.2. Water-holding capacity and oil-holding capacity

WHC determination, 0.5 g (m) protein sample (SPI, AEAP-SSP, NADES-SSP) was accurately weighed and dispersed in 50 mL of ultrapure water. The pH was adjusted to different values using HCl or NaOH. A 5 mL portion of the sample suspension at each pH was placed into a pre-weighed 10 mL centrifuge tube (m₁) and centrifuged at 5000 ×g for 20 min. Following centrifugation, the supernatant was removed, and any residual liquid on the inner wall of the tube was dried by blotting with filter paper, and the total mass of the precipitate together with the centrifuge tube (m₂) was recorded. For oil-holding capacity (OHC) determination, 0.5 g (m) protein sample was precisely weighed into a pre-weighed 10 mL centrifuge tube (m₁). Sunflower seed oil (5 mL) was then added, and the mixture was vortex-mixed for 2 min, followed by a standing period of 10 to 110 min. After centrifugation at 5000 ×g for 20 min, the upper oil layer was discarded, and the total mass of the precipitate together with the centrifuge tube (m₂) was recorded. WHC and OHC were calculated using the following formulas:

$$\begin{array}{c}\mathrm{WHC}/\mathrm{OHC}=\frac{m_2-m_1}{m}\times 100\end{array}$$ (5)

where:m: sample mass, g; m₁: empty tube mass, g; m₂: total mass of precipitate and centrifuge tube, g.

2.9.3. Emulsifying activity index and emulsifying stability index

Following the method described by Vioque et al. (Vioque et al., 2000), the emulsifying activity index (EAI) and emulsifying stability index (ESI) of the proteins were determined. Protein solutions of 0.2% (w/v) were prepared at different pH values. An emulsion was prepared by mixing 4 mL of sunflower seed oil with 12 mL of the protein solution, followed by homogenization using an Ultra-Turrax T18 high-speed shear homogenizer (IKA, Staufen, Germany) at 15,000 rpm for 1 min. Immediately after homogenization, 50 μL was taken from the bottom of the emulsion and diluted to 5 mL with the same buffer containing 0.1% SDS, and the absorbance was measured at 500 nm (recorded as A₀). After the emulsion was allowed to stand for 10 min, another 50 μL aliquot was taken from the bottom and diluted in the same manner, and the absorbance was measured (recorded as A₁₀). The emulsifying activity index (EAI) and emulsion stability index (ESI) were determined using the following formulas:

$$\begin{array}{c}\mathrm{EAI}=\frac{2\times T\times A_0\times D}{c\times \phi \times 10000}\end{array}$$ (6)

$$\begin{array}{c}\mathrm{ESI}=\frac{A_0}{A_0-A_{10}}\times 10\end{array}$$ (7)

where:T: 2.303; D: dilution factor; c: protein concentration (g/mL); $\phi$: volume fraction of the oil phase; 10: standing time of the emulsion (min).

2.9.4. Foaming capacity and foam stability

Following the method of Mizuguchi et al. (Mizuguchi et al., 2025) with slight modifications, Protein solutions at a concentration of 1% (w/v) were formulated across a range of pH conditions. A 10 mL volume of each protein solution (V₀) was transferred to a 50 mL graduated cylinder and subjected to homogenization using a high-speed shear homogenizer at 15,000 rpm for 2 min. The foam volume (V₁) and the remaining liquid volume (V₂) were subsequently recorded. After standing for 30 min, the foam volume (V₃) was measured again. The foaming capacity and foam stability were calculated using the following formulas:

$$\begin{array}{c}\mathrm{FA}=\frac{V_1+V_2-V_0}{V_0}\times 100\%\end{array}$$ (8)

$$\begin{array}{c}\mathrm{FS}=\frac{V_3}{V_1}\times 100\%\end{array}$$ (9)

2.10. Statistical analysis

All experiments were conducted in triplicate, and the results were presented as mean ± standard deviation. Statistical analyses were performed with IBM SPSS Statistics 21.0 software, and significant differences were determined using Duncan's multiple range test (p < 0.05). Graphical representations were created with Origin 2024 software, while experimental design and data analysis for response surface methodology (RSM) were performed using Design-Expert 13.0 software.

3. Results and discussion

3.1. Characterization of deep eutectic solvents

3.1.1. Density and pH of NADESs

The performance of deep eutectic solvents in protein extraction largely depended on their unique physicochemical properties, which modulated the interactions between the solvent and protein molecules, thereby influencing extraction efficiency and selectivity to a certain extent. As shown in Fig. 1A, the NADESs prepared in this study presented pH values ranging from acidic to neutral. This variation in pH was primarily attributed to the type of HBD, a key factor governing the acid-base environment of the NADESs system, consistent with the findings reported by Vilkova et al. (Vilková et al., 2020). Density was identified as one of the critical physical parameters affecting NADESs extraction performance. All NADESs prepared in this study exhibited densities higher than that of water, and such compact molecular packing was considered to facilitate solvent penetration into the biomass matrix by overcoming resistance. Meanwhile, the high-density solvent structure enhances the affinity with protein molecules through closer physical contact and stronger polar interactions, and maintains continuous contact via stable intermolecular forces, thus improving extraction efficiency (Wong et al., 2025). The density of NADESs was influenced by water content, HBD type, and temperature. According to previous studies, density tended to decrease approximately linearly with increasing water content or with rising temperature within the moderate temperature range (Dai et al., 2015; Deng et al., 2016). Additionally, higher numbers of hydroxyl groups within the hydrogen bond donor were associated with increased density. For instance, the density of Bet-Gly (1.29 g/cm³), which contained three hydroxyl groups, was significantly higher than that of Bet-BD (1.17 g/cm³) and Bet-EG (1.19 g/cm³), both of which possessed only two hydroxyl groups.

Fig. 1.

Physicochemical properties of the five NADESs and their extraction performance for SSP (A, pH and density; B, viscosity at different temperatures; C, yield, purity, and extraction yield of SSP; D, color of the corresponding proteins) Error bars represent standard deviations (n = 3). Different lowercase letters above the error bars indicate significant differences among samples (p < 0.05).

3.1.2. Viscosity of NADESs

Owing to strong molecular interactions between the HBD and HBA, the internal molecular free volume of NADESs was reduced and molecular motion was restricted, resulting in high viscosity values, which ranged from approximately 10 to 700 mPa·s. As illustrated in Fig. 1B, the viscosities of all five NADESs decreased nonlinearly with increasing temperature, as elevated temperatures disrupted the hydrogen bonds that stabilized the solvent structure, thereby enhancing molecular mobility. Reduced viscosity contributed to improved mixing and mass transfer efficiency, which were essential for efficient protein extraction. Bet-Gly exhibited the highest viscosity, a phenomenon attributed to the polyhydroxy structure of glycerol. The three hydroxyl groups of glycerol enabled the formation of a more complex and crosslinked hydrogen-bonding network with betaine, thereby increasing intermolecular friction and resulting in markedly higher viscosity at the same temperature compared with the other systems. As the temperature increased, this strong hydrogen-bonding network became more susceptible to thermal disruption, leading to a greater reduction in viscosity and a more pronounced temperature dependence. These observations indicated that the viscosity behavior of NADESs was closely associated with the strength of its internal hydrogen-bonding interactions and the structural characteristics of the network.

3.2. Protein extraction yield and purity analysis

The betaine-based deep eutectic solvent disrupted the stability of the plant cell wall through strong hydrogen bonding, inducing a physical swelling effect that opened pathways for protein release. Subsequently, multiple interactions, such as hydrogen bonding, electrostatic forces, and van der Waals forces, occurred between the protein molecules and the NADESs/water binary mixture, enabling the selective dissolution of proteins. As shown in Fig. 1C, significant differences were observed in the extraction efficiency of safflower seed protein among NADESs composed of different HBDs. Polyol-based NADESs exhibited superior extraction performance compared with acid-based and amide-based NADESs, likely because the relatively mild chemical properties of alcohol solvents better maintained protein solubility and structural integrity. In contrast, the strong acidity of acid-based NADESs or the potential denaturation tendency of amide-based NADESs may have disrupted the native conformation of proteins during extraction, limiting mass transfer efficiency within the solvent phase and resulting in relatively low extraction yield and purities. Among the three polyol-based NADESs, the protein extracted with Bet-Gly exhibited the highest purity (85.66 ± 0.01%) and extraction yield (56.66 ± 0.48%), and its purity was not significantly different from that obtained by alkaline solubilization–acid precipitation. This superior extraction performance was possibly attributed to the relatively high density of Bet-Gly (1.29 g/cm³), which enhanced the mass transfer efficiency between the protein and the solvent, thereby increasing the protein extraction yield. This finding was in agreement with the results presented by Peng et al. (Peng et al., 2026). Although alkaline solubilization–acid precipitation achieved the highest extraction yield (63.71 ± 0.45%) by promoting protein deprotonation under strong alkaline conditions, which generated strong electrostatic repulsion, such drastic pH changes were often accompanied by protein denaturation. In contrast, Bet-Gly achieved comparable protein purity to alkaline solubilization–acid precipitation while causing less disruption to the native protein structure and being green and non-toxic. Therefore, considering extraction efficiency, product purity, and structural integrity, the Bet-Gly system was selected as the optimal solvent for safflower seed protein in subsequent experiments, and the process parameters were optimized accordingly.

3.3. Appearance and color analysis

Color was regarded as one of the important indicators for evaluating protein quality, as it not only directly affected consumer sensory acceptance but also reflected, to a certain extent, the nutritional quality and purity of the protein. The appearance and comprehensive color parameters (L^⁎, a^⁎, b^⁎) of the six SSP samples were presented in Fig. 1D. The results showed that AEAP-SSP appeared yellowish-brown with a noticeable granular texture. This phenomenon was attributed to the alkaline environment, which caused the protein molecules to unfold and expose hydrophobic groups. Upon acid precipitation near the isoelectric point, the electrostatic repulsion between molecules was weakened, leading to intense and often irreversible aggregation through hydrophobic interactions, disulfide bonds, and hydrogen bonding, ultimately resulting in the formation of larger particles. In contrast, the five NADES-extracted proteins exhibited lighter colors and presented as fine, uniform powders.

The L^⁎ values of the six SSP samples followed the order: BLA-SSP > BGly-SSP > BEG-SSP > BBD-SSP > BU-SSP > AEAP-SSP, which was inversely related to their pH values. This finding indicated that protein brightness was closely correlated with the pH of the extraction environment, with brightness decreasing as the pH of the extraction environment increased. This observation was consistent with findings reported by Laursen et al. (Laursen et al., 2024). Among all samples, BLA-SSP exhibited the highest L^⁎ value (86.06 ± 0.66), likely because the acidic environment (pH 3.41 ± 0.04) effectively inhibited phenolic oxidation and the Maillard reaction, thereby preserving the natural whiteness of the protein to the greatest extent. BGly-SSP appeared off-white with an L^⁎ value of 80.51 ± 0.20, which, although slightly lower than that of BLA-SSP, remained significantly higher than that of AEAP-SSP (61.10 ± 0.75). The lowest L^⁎ value and the highest a^⁎ and b^⁎ values were observed for AEAP-SSP, which was possibly attributed to the oxidation of phenolic compounds under alkaline conditions and their subsequent conjugation with amino or sulfhydryl groups of the protein, forming colored complexes. Additionally, the a^⁎ and b^⁎ values of all samples were greater than 0, indicating that the SSP obtained by the different extraction methods generally exhibited yellowish-red tones.

3.4. Factors affecting protein extraction yield

3.4.1. Water content of NADES

Water content was recognized as a critical variable in modulating the physicochemical properties of NADES, as it reduced the viscosity of the system to enhance mass transfer efficiency while simultaneously posing a risk of disrupting the microscopic hydrogen-bonding network of NADES. As shown in Fig. 2A, the yield, purity, and extraction yield of NASSP initially increased and then plateaued with increasing water content. When the water content was increased from 0% to 20%, the purity of NASSP increased from 69.13 ± 0.98% to 84.40 ± 2.78%, and the extraction yield increased from 45.08 ± 0.64% to 60.98 ± 2.00%. This phenomenon was attributed to the addition of water, which disrupted the original dense structure of NADES, significantly reduced the viscosity of the system, and decreased mass transfer resistance, thereby enhancing the penetration and dissolution efficiency of the solvent toward protein molecules. Previous studies have indicated that when the water content remained below 50% (w/w), water molecules were able to penetrate between NADES components, inserting into and partially disrupting the hydrogen-bonding network, leading to moderate relaxation and rearrangement of molecular packing without completely dismantling the characteristic supramolecular structure of NADES; thus, the system retained typical NADES properties (Vilková et al., 2020). In the present study, when the water content ranged from 20% to 50%, although further dilution of the solvent occurred, the core hydrogen-bonding interaction network of NADES was not completely disrupted, and the specific protein solubility capacity was maintained. Consequently, no substantial fluctuations in yield, purity, or extraction yield were observed with further increases in water content, and a plateau phase was reached. Based on these results, and with consideration of both extraction efficiency and solvent stability, a water content range of 10%–30% was selected for subsequent process optimization.

Fig. 2.

Effects of single factors and their interactions on NADES-SSP extraction (A-C, Effects of water content, temperature, and solid-to-liquid ratio on the purity, yield, and extraction yield of NADES-SSP; D—F, Effects of interactions among factors on the extraction yield of NADES-SSP).

3.4.2. Extraction temperature

Extraction temperature was considered to influence mass transfer efficiency by reducing the viscosity of NADES and affecting molecular kinetic energy, while also potentially inducing protein thermal denaturation. As shown in Fig. 2B, the purity, extraction yield, and yield of the protein exhibited substantial fluctuations with changes in temperature. When the extraction temperature was increased from 30 °C to 50 °C, a significant increase in extraction yield was observed. This phenomenon was attributed to the reduction in solvent viscosity and the increase in diffusion coefficient, which facilitated hydrogen bonding and hydrophobic interactions between NADES and protein molecules, thereby enhancing dissolution and extraction efficiency. As the temperature was further raised to 70 °C, the three extraction parameters reached a plateau, indicating that extraction kinetics had approached equilibrium under these conditions, and further temperature elevation did not improve extraction performance. Moreover, when the extraction temperature surpassed the protein's denaturation temperature, structural unfolding and aggregation of the protein might have occurred, leading to the formation of insoluble aggregates. For instance, Hewage et al. reported that when the extraction temperature for faba bean protein using DES was increased from 50 °C to 90 °C, a decrease in extraction yield was observed due to protein thermal denaturation (Hewage et al., 2024). Based on these results, and with consideration of extraction efficiency, energy costs, and the avoidance of excessive heat-induced protein denaturation, a temperature range of 40 °C–60 °C was subsequently selected as the core temperature range for process optimization.

3.4.3. Solid-to-liquid ratio

The selection of the solid-to-solvent ratio was recognized as a critical factor in achieving a balanced process design and optimizing protein extraction yield and process efficiency. As illustrated in Fig. 2C, with increasing solid-to-liquid ratio, no significant change was observed in protein yield, whereas both purity and extraction yield initially increased significantly before reaching a plateau. The maximum extraction yield was achieved at a solid-to-liquid ratio of 1:30. Due to the inherent viscosity of deep eutectic solvents, an excessively low solid-to-liquid ratio might have resulted in insufficient contact between NADES and the sample, thereby reducing extraction efficiency and increasing process costs (Durrani et al., 2025). Within an appropriate range, a higher solid-to-liquid ratio was considered to enhance extraction efficiency by increasing the solvent volume and expanding the surface area for protein diffusion, thereby improving extraction performance. Based on these findings, and with consideration of extraction efficiency, product quality, and process economics, a solid-to-liquid ratio in the range of 1:20 to 1:40 was selected for subsequent extraction process optimization.

3.5. Analysis of response surface optimization results

The response surface design and corresponding experimental results were summarized in Table 1. Based on the findings from the single-factor experiments, the ranges for three variables-X₁ (water content), X₂ (extraction temperature), and X₃ (solid-to-liquid ratio)-were established. A response surface optimization was carried out using a three-factor, three-level design with five replicates at the central point, with the extraction yield (R, %) of SSP serving as the response variable. Through regression analysis, a quadratic polynomial regression model was derived, as expressed below: R = 64.83 + 6.37 × ₁ + 14.73 × ₂–2.02 × ₃–1.32X₁X₂ + 4.86X₁X₃–0.1701X₂X₃₋3.12 × ₁²–12.69 × ₂²–4.94 × ₃².

Table 1.

Experimental design and RSM results.

RSM experiment						ANOVA
Run	X1 (%)	X2(°C)	X3	R (%)		Source	Sum of squares	df	Mean square	F-value	P-value
1	20(0)	40(−1)	20(−1)	31.87 ± 0.12		Model	3077.69	9	341.97	46.05	< 0.0001
2	10(−1)	40(−1)	30(0)	29.36 ± 1.71		X1	324.49	1	324.49	43.70	0.0003
3	20(0)	40(−1)	40(1)	29.45 ± 0.16		X2	1736.37	1	1736.37	233.84	< 0.0001
4	20(0)	60(1)	20(−1)	65.27 ± 0.94		X3	32.80	1	32.8	4.42	0.0737
5	20(0)	60(1)	40(1)	62.17 ± 1.20		X1X2	6.99	1	6.99	0.9412	0.3643
6	30(1)	50(0)	40(1)	66.29 ± 0.33		X1X3	94.38	1	94.38	12.71	0.0092
7	30(1)	50(0)	20(−1)	61.91 ± 1.32		X2X3	0.1157	1	0.1157	0.0156	0.9042
8	10(−1)	50(0)	20(−1)	56.95 ± 0.22		X12	41.04	1	41.04	5.53	0.0510
9	30(1)	60(1)	30(0)	66.03 ± 0.61		X22	678.36	1	678.36	91.36	< 0.0001
10	20(0)	50(0)	30(0)	66.55 ± 0.32		X32	102.86	1	102.86	13.85	0.0074
11	20(0)	50(0)	30(0)	66.80 ± 0.46		Residual	51.98	7	7.43
12	20(0)	50(0)	30(0)	62.03 ± 0.56		Lack of fit	36.67	3	12.22	3.19	0.1457
13	10(−1)	50(0)	40(1)	41.90 ± 0.35		Credibility analysis of the regression equations
14	10(−1)	60(1)	30(0)	57.87 ± 2.87		Std. dev.	2.72	R-squared	0.9834
15	20(0)	50(0)	30(0)	64.73 ± 0.52		Mean	55.06	Adj. R-squared	0.9620
16	30(1)	40(−1)	30(0)	42.80 ± 0.86		Second-order polynomial equation
17	20(0)	50(0)	30(0)	64.03 ± 0.72		R = 64.83 + 6.37 × 1 + 14.73 × 2–2.02 × 3–1.32 X1X2 + 4.86 X1X3–0.1701 X2X3–3.12 × 12–12.69 × 22–4.94 × 32

Note: To maintain the model's hierarchical structure and interpretability, individual regression coefficients with p-values greater than 0.05 were still retained.

The results of the regression and variance analysis indicated that the regression model was highly significant (p < 0.0001), while the lack of fit was not significant (p > 0.05), suggesting a good model fit. The coefficient of determination (R² = 0.9834) demonstrated a high degree of agreement between the experimental data and the model-predicted values, confirming that the model accurately reflected the variation in the extraction yield of NADES-SSP. The adjusted coefficient of determination (R²_adj = 0.9620) suggested that approximately 96.20% of the variability in the response could be accounted for by the model. Consequently, this quadratic polynomial regression model was deemed adequate for analyzing and predicting the actual variation in SSP extraction yield. According to the F-values, the ranking of influence of the three factors on the extraction yield of NADES-SSP was determined as follows: extraction temperature > water content > solid-to-liquid ratio. Durrani et al. also reported that temperature was the most critical factor affecting protein extraction yield during the extraction of Torreya grandis protein using choline chloride-based deep eutectic solvents (Durrani et al., 2025).

The effects of factor interactions on the extraction yield are illustrated in Fig. 2D-2F. Based on the shapes of the response surfaces and the contour plots, certain interactions were observed among the factors, with extraction temperature exerting the most pronounced effect on SSP extraction yield, which was corroborated by the results of the variance analysis. Elevated temperatures effectively reduced the viscosity of the NADES system, facilitating faster solvent penetration into the biomass matrix and thereby significantly affecting the extraction yield. According to the response surface optimization and regression model prediction, the optimal extraction conditions were established as follows: water content of 28.640%, extraction temperature of 51.503 °C, and solid-to-liquid ratio of 1:24.392, corresponding to an NADES-SSP extraction yield of 67.00%. Considering practical feasibility, the optimized conditions were adjusted to a water content of 29%, an extraction temperature of 52 °C, and a solid-to-liquid ratio of 1:24. Under these conditions, three parallel validation experiments were conducted, yielding an average protein extraction yield of 66.45% ± 0.43%, which was close to the predicted value, indicating that the model was reliable and possessed good predictive capability.

3.6. Amino acid composition analysis

Certain differences in amino acid composition were observed between AEAP-SSP and NADES-SSP, with detailed results presented in Table 2 (tryptophan was not quantified owing to its degradation during hydrolysis). Essential amino acids (EAA) were recognized as crucial determinants of human nutrition and the functional performance of proteins. Among the measured EAAs, leucine emerged as the most abundant in both protein samples. This amino acid was recognized for its important regulatory function in muscle protein synthesis after exercise, suggesting its potential value in the development of sports nutritional supplements. Additionally, the cystine content in NADES-SSP (15.57 mg/g) was observed to be higher than that in AEAP-SSP (14.21 mg/g). Cystine, an amino acid containing disulfide bonds, was recognized as important for protein structural stability. Feyzi et al. reported that alkaline extraction conditions could induce β-elimination reactions in cysteine residues, leading to disulfide bond cleavage and subsequent cross-linking or degradation, thereby disrupting the native conformation of proteins (Feyzi et al., 2018).

Table 2.

Amino acid composition of AEAP-SSP and NADES-SSP.

Amino acid (mg/g)	AEAP-SSP		NADES-SSP
Essential amino acids (EAA)	Content	Amino acid score	Content	Amino acid score
Threonine (Thr)	28.55	1.24	28.02	1.22
Cystine (Cys)	14.21		15.57
Valine (Val)	39.72	1.02	38.53	0.99
Methionine (Met)	9.23		10.34
Isoleucine (Ile)	32.71	1.09	30.45	1.02
Leucine (Leu)	56.12	0.95	55.11	0.93
Phenylalanine (Phe)	46.11		42.53
Lysine (Lys)	23.34	0.52	25.26	0.56
Histidine (His)	24.96		24.17
Total EAA	274.95		269.98
Non-essential amino acids (NEAA)
Aspartic acid (Asp)	96.12		90.44
Serine (Ser)	40.24		40.01
Glutamic acid (Glu)	199.31		206.13
Glycine (Gly)	41.04		42.26
Alanine (Ala)	37.12		35.28
Tyrosine (Tyr)	35.55		32.16
Arginine (Arg)	86.18		87.65
Proline (Pro)	47.96		47.38
Total NEAA	583.52		581.34
Sulfur amino acids (Met+Cys)	23.44	1.07	25.91	1.18
Aromatic amino acids (Phe + Tyr)	81.66	2.15	75.69	1.97
Hydrophilic amino acids	589.50		591.67
Hydrophobic amino acids	268.97		259.62

Among the non-essential amino acids (NEAA), glutamic acid was found to be the most abundant in both proteins, followed by aspartic acid and arginine. These amino acids were considered crucial for protein solubility, buffering capacity, and interfacial activity, and were also associated with health-promoting effects, such as umami enhancement and cardiovascular benefits. The hydrophilic amino acid content was found to be higher than the hydrophobic amino acid content in proteins obtained by both extraction methods. Compared with AEAP-SSP, NADES-SSP exhibited a slightly lower total hydrophobic amino acid content but a higher total hydrophilic amino acid content. This observation suggested that NADES, as a mild and strongly hydrogen-bonding solvent, tended to selectively dissolve and preserve the native conformational state of proteins with greater hydrophilic character, which might partially account for the superior solubility of NADES-SSP observed in subsequent measurements. Based on the amino acid scoring pattern recommended by FAO/WHO 2013 adult pattern, lysine was identified as the first limiting amino acid in SSP, a pattern similar to that of conventional cereal proteins such as corn and wheat. This finding was consistent with the results reported by Kutsenkova et al. in their study on safflower seed protein-fortified biscuits (Kutsenkova et al., 2020). This indicated that SSP shared similar nutritional limitations with most cereal proteins. To improve its nutritional quality, future work could combine SSP with lysine-rich wheat or legume proteins to achieve amino acid complementation, thereby offering new perspectives for its application in functional foods.

3.7. SDS-PAGE analysis

The SDS-PAGE profiles of SPI, AEAP-SSP, and NADES-SSP under non-reducing and reducing conditions were presented in Fig. 3A and B, respectively. Under non-reducing conditions (Fig. 3A), SPI (Lane 1) exhibited characteristic bands in the regions of 70–100 kDa, 55 kDa, 35–40 kDa, and 20 kDa, reflecting its typical storage protein subunit composition, which primarily corresponded to the native aggregated structures formed by multi-subunit proteins such as 7S β-conglycinin and 11S globulin in the absence of disulfide bond reduction. The bands of safflower seed protein were mainly distributed in the range of 10–70 kDa, indicating that it was also composed of various storage protein subunits with different molecular weights. In the high molecular weight region (130–180 kDa), a faint band was observed for NADES-SSP (Lane 3), whereas this band was almost absent in AEAP-SSP (Lane 2). This phenomenon was possibly attributed to protein degradation or structural alterations induced by the high pH extraction during the alkali extraction-acid precipitation process, which led to the disappearance or modification of electrophoretic bands (Yao et al., 2023). A faint band at approximately 130 kDa was also observed in the SDS-PAGE analysis of alkali-extracted safflower seed protein in a previous study, although it was barely distinguishable in the electrophoretogram (Zazueta & Javier, 1989). The most intense band for both proteins was found near 55 kDa, a molecular weight range typical of plant storage protein subunits. Previous studies have indicated that many plant seed storage proteins, such as legumin- or vicilin-type proteins, typically exhibited bands in the range of 40–60 kDa under SDS-PAGE (Di Francesco et al., 2024). Additionally, NADES-SSP exhibited a distinct band near 30 kDa that was absent in AEAP-SSP, and clearer, more intense bands were observed in the 15–20 kDa region. These observations were likely related to the relatively mild nature of the NADES extraction process, which preserved the native protein structure to a certain extent and enhanced solubility, thereby enabling more efficient extraction of certain low molecular weight subunits or albumin fractions.

Fig. 3.

Structural characterization of SPI, AEAP-SSP, and NADES-SSP. (A-B) SDS-PAGE profiles of SPI (lane 1), AEAP-SSP (lane 2), and NADES-SSP (lane 3) under non-reducing (A) and reducing (B) conditions (M: marker); (C) Fourier transform infrared spectra; (D) Secondary structure contents; (E-G) Thermogravimetric analysis and derivative thermogravimetric analysis (SPI, AEAP-SSP, NADES-SSP).

Under reducing conditions (Fig. 3B), the addition of β-mercaptoethanol disrupted disulfide bonds between protein molecules, resulting in the dissociation of high molecular weight aggregates into subunits of lower molecular weight. SPI displayed the characteristic subunit features of 7S β-conglycinin: α' and α subunits (60–80 kDa) and β subunit (42–53 kDa), as well as the acidic subunits (approximately 35–40 kDa) and basic subunits (approximately 15–25 kDa) of 11S globulin. After reduction, the subunit composition of NADES-SSP and AEAP-SSP was largely consistent. NADES-SSP exhibited distinct and dense bands in the low molecular weight region, whereas the bands for AEAP-SSP remained somewhat diffuse, suggesting that alkaline extraction might have induced partial protein degradation or covalent modification. For both proteins, the band intensities in the 130–180 kDa and 50–70 kDa regions were markedly reduced, whereas band intensities in the 30–40 kDa and 15–20 kDa regions increased. These changes indicated that these high molecular weight proteins formed oligomeric structures via disulfide bonds in their native state, which were dissociated into smaller subunits under reducing conditions. Notably, the band near 30 kDa observed in NADES-SSP remained at the same position before and after reduction, whereas AEAP-SSP exhibited almost no band in this region under non-reducing conditions but showed a clear band at the same position after reduction. This finding suggested that this subunit might have been involved in disulfide-linked aggregation or conformational changes during alkaline extraction and was released under reducing conditions. Collectively, these results indicated that the NADES extraction method effectively preserved the subunit composition of safflower seed protein, whereas the alkali extraction-acid precipitation method might have led to alterations or degradation of certain protein subunits to some extent.

3.8. Fourier transform infrared spectroscopy analysis

The vibrational frequency shifts and secondary structure contents of SPI, NADES-SSP, and AEAP-SSP were characterized using FTIR. As shown in Fig. 3C, all proteins exhibited typical characteristic absorption bands. A broad peak near the amide A band (3300–3400 cm⁻¹) was observed, corresponding to O—H stretching vibrations. The absorption band observed at approximately 2926 cm⁻¹ was primarily assigned to C—H stretching vibrations, suggesting the presence of aliphatic side-chain structures in all three proteins. The amide I region (1600–1700 cm⁻¹) was considered the most informative spectral window for probing protein secondary structure, arising mainly from the C O stretching vibrations of the peptide backbone. The amide I peaks of SPI, NADES-SSP, and AEAP-SSP were observed at 1654.87 cm⁻¹, 1654.87 cm⁻¹, and 1658.72 cm⁻¹, respectively. The slight shift in the peak position for AEAP-SSP suggested that different extraction methods exerted a certain influence on the secondary structure of the proteins. The amide II band was observed near 1533–1535 cm⁻¹, primarily arising from N—H bending and C—N stretching vibrations. All three proteins exhibited distinct absorption peaks in this region, indicating that the backbone structure of the proteins remained overall stable. Overall, the intensities of several characteristic absorption peaks of AEAP-SSP and SPI were lower than those of NADES-SSP, possibly suggesting that intermolecular or intramolecular chemical bonds in SPI and AEAP-SSP were partially disrupted (Peng et al., 2026). Since both AEAP-SSP and SPI were extracted under alkaline conditions, the relatively high pH values might have facilitated protein deamidation, hydrogen bond disruption, and disulfide bond oxidation. In contrast, NADES-SSP exhibited clearer FTIR bands and peak shapes.

To further analyze the secondary structure composition of the proteins, peak separation and fitting analysis were performed on the amide I region (1600–1700 cm⁻¹), and the results were presented in Fig. 3D. Previous studies have shown that most legume seed proteins were dominated by β-sheet structures, while the α-helix content was relatively low (Shevkani et al., 2019), which was consistent with the structural characteristics of SPI observed in this study, where the β-sheet content was 41.19% and the α-helix content was 21.07%. The predominant secondary structure of SSP was found to be β-sheet, followed by α-helix, random coil, and β-turn. Compared with AEAP-SSP, NADES-SSP exhibited a decrease in β-sheet content and an increase in α-helix content, a trend consistent with the findings reported by Zhu et al. (2025). The β-sheet structure typically presents as a zigzag sheet-like conformation, and an increase in its proportion was generally associated with greater exposure of hydrophobic groups within the protein molecule, accompanied by enhanced reactivity. However, excessive accumulation of β-sheet structures was considered to promote intermolecular interactions, thereby adversely affecting solubility. The α-helix in proteins was recognized for its flexible helical structure, which rendered hydrophobic residues less exposed, thus contributing to the maintenance of protein functional properties (Guo et al., 2021). Additionally, the increased contents of random coil and β-turn in NADES-SSP suggested that the protein structure was more flexible and loosely organized, which might have facilitated the exposure of certain functional groups and further influenced its functional properties.

3.9. Thermogravimetric analysis

Thermogravimetric (TG) and derivative thermogravimetric (DTG) analyses were utilized to assess the thermal stability and structural integrity of the proteins. The TG/DTG curves for the three proteins over the temperature range of 30 °C to 600 °C were displayed in Fig. 3E–3G, with the thermal degradation process being broadly categorized into three stages. The first stage took place within the range of 30–200 °C, and the mass loss in this stage was mainly attributed to the evaporation of bound water and the release of minor volatile components from the samples (Orellana-Palacios et al., 2025). The mass losses of the three proteins in this stage were relatively similar, ranging from 5.57 to 5.81 g/100 g. The second stage (200–400 °C) was identified as the major thermal degradation stage of the proteins, corresponding to the cleavage of peptide chains, decomposition of amino acid side-chain groups, disruption of hydrogen-bonding networks, and the generation of volatile compounds such as CO₂ and NH₃. The maximum mass loss rates (DTG peaks) for SPI, AEAP-SSP, and NADES-SSP were observed at 318 °C, 311 °C, and 317 °C, respectively. Among these, SPI and AEAP-SSP exhibited a single DTG peak in this stage, suggesting a relatively uniform protein structure with a concentrated thermal degradation process. In contrast, NADES-SSP displayed a two-peak degradation characteristic. The first degradation peak was observed at 272 °C with a mass loss rate of 0.495%/°C, corresponding to an approximately 18% mass loss. It has been reported in the literature that hydrogen bond donors and acceptors in the NADES system could form reversible hydrogen bonds or weak interactions with proteins, and such interactions might alter the microstructural stability of the protein molecules, leading to the decomposition of certain fractions at lower temperatures while other stable fractions decomposed at higher temperatures (Q. Zhang et al., 2012). The third thermal degradation stage occurred mainly above 400 °C, primarily corresponding to further cleavage of the protein carbon backbone and carbonization of the residual organic structures. When the mass loss of SPI, AEAP-SSP, and NADES-SSP reached 50%, the corresponding temperatures were 344 °C, 355 °C, and 339 °C, respectively. After the completion of thermal degradation, the final residual contents were determined to be 25.38, 31.54, and 31.51 g/100 g, respectively. Based on the DTG peak characteristics and the characteristic temperature data, AEAP-SSP was found to exhibit the highest thermal stability. This result was possibly related to its extraction method, as the alkali extraction-acid precipitation process promoted protein aggregation and the formation of a more compact structure, thereby enhancing its resistance to thermal degradation.

3.10. Interfacial tension and contact angle analysis

During emulsion formation, protein molecules were adsorbed onto the surface of oil droplets and stabilized the system by reducing the oil-water interfacial tension. The extent of interfacial tension reduction was modulated by factors such as protein concentration and molecular structural characteristics. In this study, the effects of different concentrations of SPI, AEAP-SSP, and NADES-SSP on the interfacial tension at the MCT oil/water interface were investigated, and the results were presented in Fig. 4A. Compared with pure water (35.21 ± 1.33 mN/m), all three proteins effectively reduced the interfacial tension of water, and their interfacial tension-lowering capacity increased with increasing protein concentration. Under the same concentration conditions, NADES-SSP exhibited the highest interfacial activity, followed by AEAP-SSP and SPI. The superior interfacial adsorption capacity of NADES-SSP was possibly attributed to its highly flexible structure, which was conferred by its higher random coil and β-turn contents. Such a structure was considered more prone to conformational rearrangement at the interface and promoted interfacial adsorption (Lin et al., 2022), thereby effectively reducing interfacial tension. The safflower seed proteins extracted by the two different methods both exhibited a greater capacity to reduce interfacial tension than soy protein isolate, indicating that safflower seed protein possessed strong surface activity and was able to rapidly adsorb at the oil-water interface and reduce the interfacial energy during emulsification. These findings suggested that safflower seed protein had certain advantages for the development of high-performance natural emulsifiers.

Fig. 4.

Interfacial properties of SPI, AEAP-SSP, and NADES-SSP. (A) Interfacial tension at different concentrations; (B—D) Three-phase contact angle.

To further evaluate the interfacial properties of the proteins, the three-phase contact angles (θ) of SPI, AEAP-SSP, and NADES-SSP were measured in this study, which were used to reflect the surface wettability and interfacial activity of the proteins. When θ < 90°, the protein was considered hydrophilic and tended to interact more readily with water; when θ > 90°, the protein was considered hydrophobic and tended to interact more readily with the oil phase or air. As shown in Fig. 4B-4D, SPI exhibited the largest contact angle of 105°, indicating its strong hydrophobicity, followed by AEAP-SSP with a contact angle of 99°. Notably, the contact angle of NADES-SSP was approximately 90°, approaching a balanced state between hydrophilicity and hydrophobicity. This characteristic was considered favorable for its adsorption and rearrangement at the oil-water interface, thereby enhancing interfacial stability.

3.11. Surface hydrophobicity analysis

Surface hydrophobicity of proteins was considered to reflect the conformational state of protein molecules and the degree of exposure of hydrophobic groups on the surface. In this study, surface hydrophobicity was expressed as the amount of bromophenol blue bound. Because bromophenol blue changed color and lost its indicator function under acidic conditions, protein solutions in the pH range of 5.0–8.0 were selected for measurement. The results were presented in Fig. 5A. At pH 5.0, the surface hydrophobicity of all three proteins reached its maximum. This phenomenon was attributed to the proximity of this pH to the isoelectric point of the proteins, where the net charge between molecules was reduced, electrostatic repulsion was weakened, and hydration was diminished, leading to protein aggregation or conformational changes that significantly increased surface hydrophobicity. As the pH gradually increased, the surface hydrophobicity of all three proteins exhibited a decreasing trend, and in the pH range of 6.0–8.0, the order of hydrophobicity was SPI > AEAP-SSP > NADES-SSP. This difference was likely related to the extraction methods. The high-pH extraction environment caused protein molecules to unfold and exposed internal hydrophobic structures; therefore, SPI and AEAP-SSP, which were subjected to alkaline treatment, exhibited higher surface hydrophobicity. In contrast, the extraction conditions for NADES were relatively mild, resulting in a lower degree of exposure of internal hydrophobic groups. This trend was consistent with the three-phase contact angle measurements described above. Furthermore, the surface hydrophobicity of proteins was generally associated with their secondary structure. Studies have indicated that protein surface hydrophobicity was negatively correlated with α-helix content, as the α-helix stabilized the molecular conformation and reduced the exposure of hydrophobic groups (McLauchlan et al., 2024). The order of α-helix content among the three proteins was NADES-SSP > AEAP-SSP > SPI, which aligned with the findings for surface hydrophobicity. These observations indicated that the extraction method exerted a significant influence on the modulation of both structural and interfacial properties of the proteins.

Fig. 5.

Functional properties of proteins. (A) Bromophenol blue binding capacity at different pH values; (B—C) Solubility and water-holding capacity of proteins at different pH values; (D) Oil-holding capacity of proteins at different standing times; (E-F) Emulsifying activity index, emulsifying stability index, foaming capacity, and foam stability of proteins at different pH values (bar graphs refer to the left Y-axis, line graphs refer to the right Y-axis). (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

3.12. Functional analysis of safflower seed protein

3.12.1. Solubility

Protein solubility was regarded as an important indicator reflecting the degree of denaturation and aggregation, and was modulated by intrinsic factors such as amino acid composition and spatial conformation, as well as external environmental conditions such as pH. Fig. 5B illustrated the solubility changes of the three proteins over the pH range of 3.0–8.0. As the pH increased, the solubility of all three proteins was observed to first decline and then increase, with the minimum value recorded at pH 5.0. This phenomenon was attributed to the proximity to the isoelectric point, where the net surface charge of the protein molecules approached zero, electrostatic repulsion between molecules was weakened, and aggregation and precipitation readily occurred, leading to a decrease in solubility. At pH 3.0, the solubility of NADES-SSP was 85.00%, considerably higher than that of SPI (63.11%) and AEAP-SSP (50.85%). Overall, NADES-SSP consistently exhibited higher solubility than AEAP-SSP across all tested pH conditions. Such a phenomenon may be attributed to the elevated proportion of hydrophilic amino acid residues—notably glutamic acid—within the NADES-SSP fraction. The marked pH sensitivity of protein solubility documented herein corroborates the findings of Tanyitiku et al., who similarly reported minimal solubility in proximity to the isoelectric point for leaf protein extracted from African Solanum scabrum. Furthermore, their work established that extraction methodology exerts a substantial influence on the solubility behavior of plant proteins. (Tanyitiku et al., 2026). These results indicated that the NADES extraction process contributed to improving the solubility characteristics of safflower seed protein, thereby providing favorable conditions for its application in food systems.

3.12.2. WHC and OHC analysis

The WHC and OHC of proteins were recognized as critical functional properties that influenced food texture, mouthfeel, flavor retention, and nutritional stability. The WHC of proteins was susceptible to environmental factors such as pH. As shown in Fig. 5C, different pH conditions exerted certain effects on the water-holding capacity of the proteins. Among them, SPI exhibited the lowest WHC at pH 5.0, with a value of 1.80 g/g, which was primarily attributed to enhanced intermolecular interactions near the isoelectric point of the protein, leading to protein aggregation and consequently reducing the ability to bind water molecules. NADES-SSP and AEAP-SSP showed relatively minor variations in WHC across the pH range of 3.0–8.0 and consistently exhibited lower WHC values than SPI. This difference was mainly associated with the distinct amino acid compositions and spatial conformations of safflower seed protein compared with soy protein isolate.

The OHC of proteins is governed by multiple determinants, encompassing protein concentration, specific surface area, as well as the abundance of hydrophobic amino acid residues. As shown in Fig. 5D, the oil-holding capacity of the three proteins gradually increased with extended standing time, indicating that the adsorption and binding of oils by proteins required a certain period to reach a stable state. Although NADES-SSP exhibited the lowest surface hydrophobicity among the three proteins, it displayed the highest OHC, reaching 1.98 g/g at 120 min. This finding suggested that the oil-binding mechanism of NADES-SSP might involve synergistic effects of multiple factors. From the perspective of protein secondary structure, NADES-SSP contained a lower β-sheet content and higher random coil and α-helix contents, which were considered to facilitate the formation of a more loosely organized network structure, thereby increasing the specific surface area of the molecules and providing more oil-binding sites, thus enhancing oil-holding capacity. Thongkong et al. also reported that the random coil structure of proteins was highly correlated with oil absorption capacity (Thongkong et al., 2025). The favorable OHC of NADES-SSP indicated its potential for application in meat analogues or flavor enhancers to restore meat flavor and improve mouthfeel.

3.12.3. Emulsifying properties and emulsion stability analysis

Protein emulsification performance was characterized via two complementary metrics: the emulsifying activity index (EAI), quantifying interfacial adsorption capacity at the oil–water boundary, and the emulsifying stability index (ESI), assessing the resilience of the interfacial film throughout manufacturing and shelf-life periods. Fig. 5E illustrated the variations in EAI and ESI of SPI, AEAP-SSP, and NADES-SSP under different pH conditions. The results showed that for all three proteins, both EAI and ESI initially decreased and then increased with changes in pH, with the minimum values observed at pH 5.0. This phenomenon was attributed to the lowest solubility of the proteins near the isoelectric point, which led to protein aggregation and reduced the number of proteins adsorbed at the oil-water interface, thereby decreasing EAI and ESI. Under all tested pH conditions, NADES-SSP exhibited the highest EAI, particularly under acidic conditions, which was likely associated with its favorable solubility. Tirgar et al. pointed out that an increase in EAI activity was related to decreased surface hydrophobicity and increased solubility of proteins (Tirgar et al., 2017). Furthermore, the three-phase contact angle results showed that NADES-SSP had a contact angle close to 90°, demonstrating its unique advantage in stabilizing emulsions. In contrast, the ESI values of the three proteins showed relatively smaller variations with pH but still exhibited a certain pH dependence. At pH 3.0, NADES-SSP also demonstrated excellent emulsifying stability. In the pH range of 5.0–8.0, although its emulsifying stability was slightly lower than that of SPI, it remained higher than that of AEAP-SSP, indicating that under these conditions, NADES improved the emulsifying stability of safflower seed protein, but the ability of the formed emulsions to inhibit droplet aggregation and flocculation during long-term storage still required further improvement.

3.12.4. Foaming capacity and foam stability analysis

The foaming capacity of proteins was recognized as one of the key functional properties determining their applicability in foaming and aerated food systems. This property was influenced by multiple intrinsic factors, including protein structure, surface hydrophobicity, solubility, and structural flexibility. The pH-dependent foaming characteristics of the protein isolates are illustrated in Fig. 5F, wherein both the foaming activity (FA) and the temporal stability of the generated foams (FS) were systematically assessed across the experimental pH spectrum. Consistent with the trend observed for emulsifying properties, the FA and FS of all three proteins were found to be lowest near the isoelectric point (pH 5.0), and both foaming capacity and foam stability improved when the pH deviated from the isoelectric point. SPI exhibited relatively stable foaming capacity and foam stability across the entire tested pH range. In contrast, the foaming capacity and foam stability of AEAP-SSP and NADES-SSP were more significantly affected by pH fluctuations. Overall, NADES-SSP demonstrated superior foaming capacity compared with AEAP-SSP, and under acidic conditions (pH 3.0–6.0), NADES extraction significantly improved the foam stability of safflower seed protein. At pH 3.0, NADES-SSP exhibited excellent foaming performance. It was reported in a previous study that white lupin (Lupinus albus) protein extracted using a choline chloride-glycerol system exhibited the highest foaming capacity at pH 3.0, which was speculated to be due to the increased net charge of the protein, weakened hydrophobic interactions, and enhanced structural flexibility under such conditions, thereby facilitating rapid adsorption at the air-water interface and promoting foam formation and stabilization (Nadeeshani et al., 2026). In summary, compared with AEAP-SSP, NADES-SSP exhibited superior foaming capacity and foam stability under low pH conditions. This characteristic suggested its potential applicability in the food industry under acidic environments (such as acidic beverages, mayonnaise, and salad dressings), providing a new technological approach for the functional utilization of safflower seed protein.

3.13. Correlation analysis

Principal component analysis (PCA) was performed on the standardized data of the 12 indicators, as was shown in Fig. 6A. PC1 and PC2 accounted for 60.0% and 34.6% of the total variance, respectively, with a cumulative contribution rate of 94.6%, indicating that the first two principal components adequately reflected the differences among samples and the correlations among indicators. NADES-SSP and AEAP-SSP were located in the second and third quadrants, respectively, suggesting that NADES extraction significantly influenced the structural and functional properties of safflower seed protein. The correlation heatmap further revealed the relationships between protein structure and functionality (Fig. 6B). The color intensity reflected the strength of the correlations (Shi et al., 2024). The results indicated that the secondary structure of the proteins was associated with their functional properties. α-Helix was found to be significantly negatively correlated with ESI, WHC, and surface hydrophobicity, whereas β-sheet was significantly positively correlated with ESI, WHC, and surface hydrophobicity. Random coil showed a significant positive correlation with EAI and OHC. Overall, variations in secondary structure composition were identified as the primary cause of differences in functionality, suggesting that the functional properties of the protein could be modulated by regulating the extraction method.

Fig. 6.

Principal component analysis (A) and correlation analysis (B) of the main indicators of SPI, AEAP-SSP, and NADES-SSP.

4. Conclusions

In this study, a series of NADESs with betaine as the hydrogen bond acceptor was constructed, and the effects of different hydrogen bond donors on the extraction efficiency of safflower seed protein were systematically investigated. The extraction process of the optimal Bet-Gly system was subsequently optimized, and finally, the structural characteristics and functional properties of NADES-SSP were compared with those of AEAP-SSP and SPI. The results indicated that the type of hydrogen bond donor significantly influenced the extraction performance of NADESs, among which the Bet-Gly system exhibited the highest protein purity (85.66%) and extraction yield (56.66%) among the five HBDs, with the extracted product showing a lighter color (L^⁎ 80.51) and a uniform protein powder morphology. The optimal extraction conditions were obtained through response surface methodology optimization, which increased the extraction yield to 66.45% ± 0.43%, and the model was validated to possess good predictive capability. Structural characterization revealed that, compared with the AEAP method, NADES extraction was mild, and the obtained protein retained higher contents of hydrophilic amino acids and a more intact subunit composition. In the secondary structure, the contents of α-helix, random coil, and β-turn were increased, while the β-sheet content was decreased, which was closely associated with the improved solubility, emulsifying properties, and oil-holding capacity of the protein. Correlation analysis further confirmed that alterations in protein secondary structure were a key factor influencing functional properties. In conclusion, the betaine-glycerol NADES system was established as a green and efficient method for the extraction of safflower seed protein, which preserved the native conformation of the protein while enhancing its functional properties, particularly demonstrating promising application potential in acidic food systems. This study provided a novel technological approach for the high-value utilization of safflower seed meal and laid a theoretical foundation for the development of functional plant-based protein ingredients.

However, limitations remain in the selection strategy of NADES for this study. Specifically, betaine was fixed as the sole HBA to evaluate only five HBDs, a scope that might have missed donor-acceptor combinations with superior biocompatibility for safflower seed protein. Furthermore, the screening process lacked a molecular-level understanding of the interaction mechanisms between NADES and the protein, leading to lower screening efficiency and making it difficult to predict the optimal system fundamentally. Future studies could expand the diversity of HBAs to combine with a broader range of polyols, amides, and carbohydrates as HBDs. Additionally, a combined theoretical calculation and experimental screening strategy is recommended, utilizing molecular dynamics (MD) simulations to elucidate the non-covalent interaction patterns between NADES components and the protein surface, thereby efficiently discovering novel, food-grade NADES systems with both high extraction efficiency and low cost.

CRediT authorship contribution statement

Mengmeng Wei: Writing – review & editing, Writing – original draft, Visualization, Validation, Software, Methodology, Investigation, Formal analysis, Data curation. Chunyan Wang: Writing – review & editing, Writing – original draft, Visualization, Validation, Software, Methodology, Investigation, Formal analysis, Data curation. Sheng Geng: Writing – review & editing, Writing – original draft, Methodology, Investigation, Formal analysis. Benguo Liu: Writing – review & editing, Writing – original draft, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Data availability

Data will be made available on request.