Functional cookies with improved flavor, digestibility and shelf life via application of Camellia seed oil-based emulsion gel for grape seed polyphenol delivery

Abstract

To address the instability of grape seed polyphenols (GSP) and the lipid composition of traditional butter cookies, this study employed a camellia seed oil-based emulsion gel loaded with GSP as a butter substitute. Optimal conditions were established at an oil-to-water ratio of 7:3 and a gelatin concentration of 3%, yielding an oil-holding capacity of 89.5% and a uniform microstructure. Incorporating 0.1% GSP enhanced the gel network through hydrogen bonding, conferring more robust shear-thinning properties and excellent thermal processing tolerance. When applied to cookies, this gel produced optimal sensory ratings. This formulation reduced rapidly digestible starch by approximately 4.7% and increased resistant starch by about 7.9%, significantly delaying starch digestion rates. Its antioxidant properties extended shelf life to 1.6–1.9 times that of the control group. This system offers a novel strategy for developing functional baked goods with enhanced flavor, digestive properties, and shelf life.

Highlights

• •A novel grape seed polyphenol-loaded camellia oil emulsion gel was developed.
• •Revealed the synergistic interface stabilization mechanism between polyphenols and gelatin.
• •Butter substitution enhanced cookie flavor, aroma, and oxidative stability.
• •Starch digestion was delayed and resistant starch content increased.
• •Cookie shelf life was extended by up to 1.92 times.

1. Introduction

Grape seed polyphenols (GSP) are natural bioactive compounds derived from grape seeds and have attracted considerable attention because of their strong antioxidant activity, cardiovascular protective effects, and antibacterial properties. These functional characteristics make GSP promising ingredients for the development of functional foods and nutritionally enhanced products (Caponio et al., 2022; Chatziharalambous et al., 2024; Yang et al., 2022). However, the practical application of GSP in food systems remains restricted by several intrinsic limitations. GSP generally exhibit poor water solubility and are susceptible to degradation under adverse environmental conditions, including heat, alkaline pH, light exposure, and the presence of metal ions (Chen, Chen, et al., 2024; Dai et al., 2020). In addition, their low bioavailability in the gastrointestinal tract and pronounced bitterness further hinder their direct incorporation into food matrices (Khodaei et al., 2023). To address these limitations, a variety of encapsulation and delivery strategies have been developed, including spray drying, spray cooling, extrusion, solvent evaporation, coacervation, complexation, emulsification, nanoencapsulation, and cocrystallization (Kalita et al., 2025). Nevertheless, these approaches still present important drawbacks. For example, the elevated temperatures involved in spray drying may accelerate the thermal degradation of GSP (George et al., 2025). Liposomes and nanoemulsions are often vulnerable to aggregation and Ostwald ripening during storage (Han, Zhu, et al., 2025). Hydrogels may undergo premature destabilization in complex food environments because of ion exchange or matrix interference (Zhang, Tang, et al., 2025). Cyclodextrin-based inclusion systems may also exhibit limited encapsulation efficiency for polyphenols with relatively large molecular structures (Pinho et al., 2014). Therefore, the development of an effective food-grade delivery system capable of improving the encapsulation efficiency, physicochemical stability, and delivery performance of GSP remains highly necessary.

Emulsion gels have emerged as promising carriers for bioactive compounds because they integrate the multiphase structural characteristics of emulsions with the three-dimensional network properties of gels. This hierarchical architecture imparts desirable rheological attributes, including hardness, elasticity, and spreadability, while also enhancing resistance to droplet aggregation and Ostwald ripening. As a result, emulsion gels can facilitate the efficient encapsulation, stabilization, and controlled release of functional ingredients such as lipophilic nutrients, flavor compounds, probiotics, and other bioactives (Farjami & Madadlou, 2019; Torres et al., 2016). Owing to these advantages, emulsion gels have shown broad potential in the development of low-fat foods, plant-based alternatives, and advanced delivery systems designed to improve nutritional quality, sensory performance, and storage stability. Recent studies have demonstrated that gel-based delivery systems can effectively enhance the loading capacity, structural stability, and release behavior of polyphenolic compounds (Cen et al., 2024). Ma, Zhang, et al. (2025) reported that a ternary composite gel composed of chickpea protein, grape seed proanthocyanidins, and konjac gum enabled efficient polyphenol encapsulation and improved structural stability through hydrogen bonding and hydrophobic interactions. These studies suggest that emulsion gels possess substantial structural flexibility and functional tunability, which make them attractive platforms for overcoming the major challenges associated with polyphenol delivery.

Butter is an important ingredient in baked products because it contributes to characteristic plasticity, crisp texture, and a rich creamy flavor. However, its high levels of saturated fat and cholesterol are inconsistent with the increasing consumer demand for healthier dietary patterns. In this context, the replacement of butter with vegetable oils rich in unsaturated fatty acids has become an effective strategy for improving the lipid nutritional profile of bakery products. Camellia seed oil is a natural edible oil extracted from mature camellia seeds and is rich in monounsaturated fatty acids, squalene, and other endogenous bioactive compounds. It exhibits favorable oxidative stability and has been associated with beneficial effects on cardiovascular health, antioxidant defense, and lipid metabolism. Recent evidence has indicated that camellia seed oil can be structured for use as a substitute for solid fats, thereby improving the fatty acid composition of food products (Jia-Wei et al., 2025). However, the direct substitution of butter with liquid camellia seed oil is technically challenging because the liquid nature of the oil is not compatible with the structural and processing requirements of baked goods. Structuring camellia seed oil into an emulsion gel provides a feasible solution because it converts the liquid oil into a semi-solid system with butter-like spreadability and plasticity, which may help preserve the desirable textural characteristics of baked products. Furthermore, the incorporation of GSP into such an emulsion gel system may further enhance its functional value through potential synergistic effects with the endogenous active constituents of camellia seed oil. Despite these advantages, studies that simultaneously integrate polyphenol delivery and butter replacement in bakery products using camellia seed oil-based emulsion gels remain limited.

Therefore, the present study aimed to develop a GSP-loaded camellia seed oil emulsion gel and evaluate its potential as a partial or complete butter substitute in cookies. The stability, microstructure, physicochemical properties, and rheological behavior of the developed emulsion gel were systematically characterized. In addition, the effects of replacing butter with the prepared emulsion gel on the textural properties, quality attributes, in vitro digestibility, and storage stability of cookies were comprehensively investigated. This study is expected to provide both theoretical support and practical guidance for the design of multifunctional emulsion gel-based delivery systems for polyphenolic compounds and the development of healthier bakery products.

2. Methods

2.1. Materials

GSP, with proanthocyanidin content ≥95%, was purchased from Tianjin Jianfeng Natural Product R&D Co., Ltd. (Tianjin, China). Gelatin, 250 Bloom, was purchased from Shangshi Fuyuan Gelatin Co., Ltd. (Henan, China). Monoglyceride (99% purity) was purchased from Guangzhou Guangtai Food Technology Co., Ltd. (Guangzhou, China). Camellia seed oil, which contains over 90% unsaturated fatty acids, with oleic acid accounting for 80–83% and linoleic acid for 7–13%, was sourced from Guizhou Bouyei Liji Camellia Oil Industry Co., Ltd. (Guizhou, China). 1,1-Diphenyl-2-trinitrophenylhydrazine (DPPH) (0.2 mmol/L), simulated salivary fluid (SSF, containing 75 U/mL α-amylase, NaCl, KCl, KSCN, KH₂PO₄, urea), simulated gastric fluid (SGF, containing 2000 U/mL pepsin, HCl, water), simulated intestinal fluid (SIF, containing 8 mg/mL bile salts and 3 mg/mL trypsin, KH₂PO₄, NaOH, water), and DNS working solution were purchased from FTY. Phygene Life Sciences Co., Ltd. (Fuzhou, China). Distilled water and analytical-grade chemicals were used in all experiments unless specified otherwise.

2.2. Preparation of GSP-loaded emulsion gel system

Aqueous phases were prepared by dissolving GSP and gelatin in deionized water, with final GSP concentrations of 0%, 0.1%, 0.2%, and 0.3% (w/w) (Song et al., 2025), paired with corresponding gelatin concentrations of 1%, 2%, 3%, and 4% (w/w), respectively. All mixtures were stirred at 25 °C and 800 rpm for 15 min to ensure complete and homogeneous dissolution. The oil phase was formulated by dispersing 6% (w/w) monoglyceride in 94% (w/w) camellia seed oil, followed by constant stirring at 80 °C and 1000 rpm for 20 min. Emulsion gels were fabricated by adding the aqueous phase to the oil phase at a series of mass ratios (5:5, 6:4, 7:3, 8:2, 9:1), followed by emulsification under stirring at 25 °C and 1500 rpm for 30 min.

2.3. Characterization of emulsion gels

2.3.1. Observation of emulsion gel microstructure

A droplet of the freshly prepared emulsion gel was placed on a microscope slide, covered with a coverslip, and immediately observed under an optical microscope (XSP-2C, Shanghai Optical Instruments Sixth Factory, China) equipped with a 40× objective lens. The resulting micrographs were analyzed using ImageJ 1.54 g software to measure the droplet size, following the methodology of Wu et al. (2024). The mean droplet diameter was determined by randomly selecting and measuring at least 300 individual droplets from multiple images.

2.3.2. Determination of oil-holding capacity

The oil-holding capacity was determined according to the method of Lee et al. (2025). Briefly, approximately 3 g of the emulsion gel sample was placed into a pre-weighed 10 mL centrifuge tube, and the total mass was recorded. The tube was then centrifuged at 9000 r/min for 10 min at 25 °C. After centrifugation, the tube was inverted to drain the exuded oil, and the mass was measured again. This procedure was repeated in triplicate, and the average value was used for calculation. The oil-holding capacity was calculated using the following formula:

• •
  $$\text{Oil}-\text{holding capacity}\left(\%\right)=\frac{m_3-m_1}{m_2-m_1}\times 100\%$$
• •where m₁ is the mass of the empty centrifuge tube (g), m₂ is the total mass of the tube and sample before centrifugation (g), and m₃ is the total mass after centrifugation and drainage (g).

2.3.3. Determination of emulsion gel strength

Based on the method of Zhou et al. (2025) with minor modifications, a cylindrical non-metallic probe P/0.5 with a diameter of 12.7 mm was used to perform puncture tests on a texture analyzer (TA-XT plus12591, Xiamen Chaotech Instrument Co., Ltd., China). The sample was placed in a 50 mL plastic beaker with its height kept consistent across tests. The pre-test, mid-test, and post-test speeds were set to 1 mm/s, 1 mm/s, and 5 mm/s, respectively. A trigger force of 5 g was applied, with the target mode set to strain and the target value set to 50%. The force recorded at the first rupture point was defined as the gel rupture strength, and the corresponding deformation was recorded as the gel rupture distance. Three replicate tests were performed for each sample.

2.4. Determination of DPPH radical scavenging activity

The DPPH radical scavenging activity of emulsion gels containing different concentrations of GSP was evaluated according to the method described by Habtegebriel et al. (2024). Briefly, 1 mL of the GSP-loaded emulsion gel was thoroughly mixed with 2 mL of DPPH-ethanol solution. The mixture was incubated in the dark for 30 min. After incubation, the absorbance (A) of the sample was measured at 517 nm. Anhydrous ethanol was used as the control, and its absorbance was recorded as A₀. The DPPH radical scavenging rate (%) was calculated using the following formula:

• •
  $$\text{DPPH radical scavenging rate}\left(\%\right)=\left(1-\frac{A-A_1}{A_0}\right)\times 100\%$$
• •where A is the absorbance of the sample mixed with DPPH-ethanol solution, A₁ is the absorbance of the sample mixed with ethanol (without DPPH), and A₀ is the absorbance of the DPPH-ethanol solution mixed with distilled water (without sample).

2.5. Determination of moisture distribution

The water distribution in GSP-loaded emulsion gels was analyzed using a low-field nuclear magnetic resonance (LF-NMR, NM2012, Suzhou Newmax Analytical Instruments Co., Ltd., China) imaging analyzer, following the method of Zhang, Li, et al. (2025). Approximately 1.5 mL of emulsion gel containing different concentrations of GSP was weighed and transferred into a 2 mL NMR tube, which was then inserted into the NMR system. The Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence was applied to determine the transverse relaxation time (T₂) of the sample. The instrument parameters were set as follows: sampling frequency set to 200 kHz, analog gain RG1 set to 20, P1 set to 15 μs, P2 set to 28 μs, digital gain DRG1 set to 3, repeat sampling interval TW set to 1500 ms, cumulative acquisition count set to 8, and echo time TE set to 0.298 ms, echo count set to 10,000. After data acquisition, the experimental results were saved and subsequently inverted using dedicated relaxation analysis software.

2.6. Measurement of thermodynamic properties

The thermal properties of GSP-loaded emulsion gels with varying concentrations were analyzed using differential scanning calorimetry (DSC, 200F3A01, Mettler Toedo Instruments, CH, Switzerland), following the method of Carvalho et al. (2025) with minor modifications. Approximately 10 mg of each sample was weighed and subjected to the following temperature program: equilibrated at 25 °C, heated to 80 °C at a rate of 10 °C·min⁻¹, held at 80 °C for 10 min, cooled to 0 °C at 10 °C·min⁻¹ and maintained for 10 min, and finally reheated to 80 °C at 10 °C·min⁻¹ for thermal characterization.

2.7. Fourier transform infrared spectroscopy (FTIR)

FTIR analysis was conducted to investigate the intermolecular interactions within the emulsion gel samples, following the method of Chen, Ai, et al. (2024) with minor modifications. The analysis was performed using an FTIR spectrometer (INVENIO, Bruker Corporation, Germany). After background spectrum acquisition, emulsion gels containing different concentrations of GSP (0%, 0.1%, 0.2%, 0.3%) were measured in the wavenumber range of 4000–400 cm⁻¹.

2.8. Measurement of rheological properties

Utilizing the methodology outlined by Goo et al. (2025), with minor modifications, each emulsion gel sample weighing approximately 3 g was placed on the rheometer platform, equipped with a PP50 rotor, to conduct subsequent analyses. For the frequency sweep test, the initial temperature was set at 25 °C, and the strain value was maintained within the linear viscoelastic region at 0.1%. The oscillation frequency was varied from 0.1 to 10 Hz to assess the variations in the storage modulus (G') and loss modulus (G") of the sample as a function of angular frequency. In the shear viscosity test, the initial temperature was similarly set at 25 °C, and measurements were conducted over a shear rate range of 0.1 to 100 s⁻¹.

2.9. Preparation of cookies with GSP-loaded emulsion gel

The cookie formulation comprised 40 g of corn oil, 10 g of enzymatically hydrolyzed beef tallow (homemade in the laboratory), 3.5 g of butter, 10.5 g of emulsion gel (maintaining a butter to emulsion gel ratio of 1:3), 3 g of sesame oil, and 30 g of granulated sugar, which were combined in a mixing bowl and thoroughly homogenized. Subsequently, 8 g of whole egg liquid was incorporated and mixed until fully integrated, followed by the addition of 2 g of baking soda and 125 g of low-gluten flour to achieve a homogeneous dough. The dough was then portioned into 15 g segments, shaped into cookies, and baked in a preheated oven set to 170 °C for the top heat and 150 °C for the bottom heat for a duration of 10 min. Post-baking, the cookies were allowed to cool at ambient temperature for 30 min. The study categorized the cookie samples into four distinct groups based on the concentration of GSP incorporated into the camellia seed oil-based emulsion gel (0.1%, 0.2%, 0.3%), specifically designated as KBQ (no emulsion gel added), 0.1SQ, 0.2SQ, and 0.3SQ.

2.10. Determination of cookie quality

2.10.1. Sensory evaluation

Sensory evaluation was conducted by 10 trained panelists (5 males and 5 females, aged 23–28 years) recruited from the Food Sensory Panel group. All panelists had prior sensory analysis experience and received training before evaluation to familiarize themselves with the assessed attributes, including appearance, color, texture, aroma, and taste, as well as the use of the 9-point hedonic scale. Only those showing consistent scoring in preliminary tests were included. Samples were evaluated using a 9-point hedonic scale, where 1 = dislike extremely and 9 = like extremely. Sensory analysis was performed in a controlled sensory laboratory under white light at ambient temperature. Samples were coded with random three-digit numbers and presented in randomized order. Each panelist evaluated three independent replicates, with water and unsalted crackers provided for palate cleansing between samples. Mean scores were used for statistical analysis.

Ethical compliance: All sensory procedures involving human participants were conducted in accordance with the Helsinki Declaration or comparable ethical standards. All participants provided informed written consent: “I confirm that I have read and understood the information provided. I voluntarily agree to participate in this sensory evaluation and consent to the anonymous use of my responses for research and publication purposes”. Participants were also made aware of the safety, confidentiality, and voluntary nature of their participation, including their right to withdraw at any time. A specific ethical approval to conduct a human sensory study was not a requirement at the institution where this study was conducted.

2.10.2. Determination of color

The surface color of the cookies was measured using a fully automatic handheld colorimeter (HP-2132, Shenzhen Hanpu Guangcai Technology Co., Ltd., China) following the method of Carvalho et al. (2023). The color coordinates L*, a*, and b* were recorded, where L* indicates lightness (higher values represent greater whiteness), a* represents the red-green axis (positive for red, negative for green), and b* represents the yellow-blue axis (positive for yellow, negative for blue). The instrument was calibrated prior to measurement using a standard white reflectance plate (L* = 87.7, a* = 0.308, b* = 0.315).

2.10.3. Moisture distribution determination of cookies

The moisture distribution in the cookies was analyzed following the procedure described in Section 2.5 with slight modifications. Cookie samples were cut into small cubes (2 cm × 2 cm × 2 cm), wrapped in polyethylene plastic film, and then placed in NMR tubes for testing.

2.11. Determination of volatile compounds

Volatile compounds were analyzed using gas chromatography–mass spectrometry (GC–MS, G7081C, Agilent Technologies (Shanghai) Co., Ltd., USA) based on the method of Giannetti et al. (2025) and Huang, Wang et al. (2025). Briefly, 2 g of the sample was placed in a 20 mL headspace vial. Volatiles were extracted using a pre-conditioned solid-phase microextraction (SPME) fiber at 60 °C for 45 min. GC–MS analysis was performed on an Agilent system equipped with a DB-WAX capillary column (30 m × 0.25 mm × 0.25 μm) with helium as the carrier gas at a constant flow rate of 0.7 mL/min. The injector temperature was set at 250 °C in splitless mode. The oven temperature program was as follows: held at 40 °C for 2 min, increased to 180 °C at 5 °C/min, then raised to 230 °C at 10 °C/min, and finally held for 2 min. The mass spectrometer conditions were ion source temperature at 220 °C, interface temperature at 240 °C, and full scan mode with a mass range of m/z 33–500. The obtained mass spectra were searched against the NIST23 database with a matching threshold set at ≥80%.

2.12. In vitro starch digestion assay

An in vitro simulation digestion was conducted following the method of Brodkorb et al. (2019). Briefly, 3 g of cookie powder was accurately weighed into a conical flask and mixed with 3 mL of SSF. The mixture was incubated at 37 °C with constant agitation at 200 rpm for 2 min to simulate oral digestion. Subsequently, 3 mL of SGF was added, and the pH was adjusted to 2.5. The sample was further incubated at 37 °C with agitation at 200 rpm for 2 h to mimic gastric digestion. Then, 3 mL of SIF was introduced, and the pH was adjusted to 7.0. The intestinal digestion phase was carried out at 37 °C with agitation at 200 rpm for 2 h. During this phase, 1 mL aliquots were collected at 0, 20, 40, 60, 80, 100, and 120 min into centrifuge tubes. Each aliquot was mixed with 4 mL of anhydrous ethanol to terminate enzyme activity, followed by centrifugation at 4000 rpm for 10 min. The supernatant was collected, and its absorbance at 540 nm was measured using the DNS method. The reducing sugar content was calculated based on a standard calibration curve and used to represent the extent of starch hydrolysis.

Starch fractions were classified as follows: rapidly digestible starch (RDS) corresponded to the fraction hydrolyzed within 20 min, slowly digestible starch (SDS) referred to the fraction hydrolyzed between 20 and 120 min, and resistant starch (RS) denoted the starch remaining undigested after 120 min. The content of each fraction was calculated using the following formula:

• •
  $$\mathrm{RDS}\left(\%\right)=\left(G_{\mathit{20}}-G_{\mathit{0}}\right)/TS\times 0.9\times 100\%$$
• •
  $$\mathrm{SDS}\left(\%\right)=\left(G_{\mathit{120}}-G_{\mathit{20}}\right)/TS\times 0.9\times 100\%$$
• •
  $$\mathrm{RS}\left(\%\right)=100\%-\mathrm{RDS}-\mathrm{SDS}$$
• •
  $$\text{Starch digestibility}\left(\%\right)=G_{\mathrm{n}}\times 0.9÷TS\times 100\%$$

where G_n represents the glucose content produced by the hydrolysis of samples at different sampling points, TS denotes the original total starch content, and 0.9 serves as the conversion factor for reducing sugars (expressed as glucose) back to starch.

2.13. Prediction of shelf life

According to the Arrhenius model, the oxidation kinetics of lipids accelerate at higher temperatures, allowing the use of elevated stress conditions to rapidly evaluate deterioration and predict shelf life under normal storage conditions (Ma, Liu, et al., 2025). Therefore, temperatures of 30 °C, 50 °C, and 70 °C were selected to establish an accelerated degradation model using the Schaal oven method, from which the shelf life at 25 °C can be extrapolated in conjunction with the Arrhenius equation. KBQ, 0.1SQ, 0.2SQ, and 0.3SQ cookies were sealed in glass bottles containing 90 g each. The bottles were placed separately in constant temperature incubators at 30 °C, 50 °C, and 70 °C for accelerated storage experiments. The determination intervals for peroxide value are as follows: at 30 °C, samples are taken every 10 d, at 50 °C, every 5 d, and at 70 °C, every 3 d. The degree of cookie deterioration was ultimately determined using the peroxide value, calculated with the following formula:

• •
  $$B=B_{\mathit{0}}{e}^{\mathit{k}}t$$

Taking the logarithm of both sides of the above equation yields the linear relationship between the cookie peroxide value and storage time as follows:

• •
  $$lnB=kt+ln\left(B_0\right)$$
• •where B represents the peroxide value of the cookies on the t-th day of storage, meq/kg, B₀ represents the initial peroxide value of the cookies, meq/kg, k represents the rate of quality change, t represents the storage duration in days.

The Arrhenius equation is used to reflect the functional relationship between food spoilage rate and temperature, as follows:

• •
  $$lnk=ln{k}_{\mathit{0}}-\frac{{\mathit{E}}_{\mathit{a}}}{\mathit{R}\mathit{T}}$$
• •where k₀ is the frequency factor, E_a is the activation energy, R is the gas constant, 8.31444 J/(mol·K), T is the thermodynamic temperature in units of K.

The formula for predicting the shelf life S of cookies based on the first-order kinetic reaction equation and the Arrhenius model is:

• •
  $$S=\frac{\mathit{l}\mathit{n}\left(B\right)\mathit{-}\mathit{l}\mathit{n}\left(B_0\right)}{{\mathit{e}}^{\left(ln{k}_0-\frac{E_a}{RT}\right)}}$$

2.14. Statistical analysis

Samples underwent three parallel experiments, with results shown as mean ± standard deviation (SD). Plots were created using Origin 2024, and analysis of variance (ANOVA) with Duncan's test (SPSS Inc., Chicago, IL) identified significant differences (P < 0.05), marked by different letters (a, b, c, m, n).

3. Results and discussion

3.1. Analysis of the structure and properties of emulsion gels

3.1.1. Effect of oil-to-water mass ratio on the properties of emulsion gel

The oil-to-water (O/W) mass ratio is a critical parameter in the preparation of emulsion gels, as it directly affects phase behavior, interfacial adsorption, and the eventual formation of the gel network (Liu, Liang, et al., 2025). Fig. 1 illustrated the microstructure, particle size, and oil-holding capacity of emulsion gels prepared at oil-to-water mass ratios ranging from 5:5 to 9:1. When the oil-to-water mass ratio increased from 5:5 to 7:3, the particle size decreased significantly, reaching a minimum at 7:3. This trend can be explained by the combined effects of interfacial availability and emulsifier coverage. At lower oil fractions, the total oil-water interfacial area is relatively small. Although the amount of emulsifier is sufficient relative to the oil phase, the limited interface restricts the efficient formation of small droplets during homogenization (Chóez-Guaranda et al., 2025). The excess emulsifier remains in the continuous phase without contributing to interfacial stabilization, and the low oil content reduces the frequency of droplet collisions and shear-induced breakup, leading to larger and more polydisperse droplets (Cai et al., 2025). As the oil fraction increases to 7:3, the expanded interfacial area allowed more emulsifier molecules to adsorb onto newly created oil-water interfaces, forming a dense, viscoelastic interfacial layer (Wang, Yuan, et al., 2025). This layer lowers the interfacial tension, enhances steric/electrostatic repulsion, and effectively prevents droplet coalescence during homogenization, thereby producing smaller and more uniformly distributed droplets (Hao et al., 2024). This mechanistic interpretation is consistent with the findings of Krstonošić et al. (2024), who reported that a moderate increase in the oil phase promotes the stability of composite interfaces. The resulting uniform droplet distribution and small particle size facilitate the formation of a compact three-dimensional gel network via droplet-droplet or droplet-matrix interactions, which physically entraps oil and maximizes oil-holding capacity (Han, Chen, et al., 2025). However, when the oil-to-water mass ratio was further increased to 8:2 and 9:1, the particle size increased markedly and the oil-holding capacity declined. At excessively high oil fractions, the total interfacial area generated during homogenization exceeds the emulsifier's capacity to adsorb and stabilize it. The limited emulsifier is insufficient to cover the continuously forming oil-water interfaces in a timely manner, leading to incomplete or thin interfacial films (Wu et al., 2025). These weak interfaces are prone to rupture, promoting droplet coalescence and flocculation, as evidenced by Fig. 1(d,e). Coalescence reduces the total number of droplets and increases average particle size, while also disrupting the gel network continuity. Moreover, excess oil droplets may act as “inactive fillers” or even cause “oil exudation”, where unencapsulated free oil separates from the gel matrix, directly lowering the measured oil-holding capacity. This mechanistic explanation aligns with the results reported by Guo et al. (2025), indicating that an excessive oil phase leads to interfacial saturation, membrane rupture, droplet aggregation, and consequent loss of oil-holding capacity.

Fig. 1.

Microstructure and physicochemical properties of emulsion gels with different oil-to-water ratios. (a-e) Light microscopy images of emulsion gels prepared at oil-to-water ratios of 5:5, 6:4, 7:3, 8:2, and 9:1 (scale bar = 50 μm for all panels) and (f) average particle size (orange squares, left y-axis) and oil-holding capacity (green squares, right y-axis) of the corresponding emulsion gels. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

3.1.2. Effect of gelatin concentration on the gel strength and oil-holding capacity of emulsion gel

As shown in Fig. 2(a), gelatin concentration significantly influenced both the gel strength and oil-holding capacity of emulsion gels, with the two properties exhibiting a similar trend of initially increasing and then decreasing as the gelatin content rose. When the gelatin concentration increased from 1% to 3%, the gel strength improved markedly. This enhancement may be attributed to the formation of a denser and more stable three-dimensional network through interactions such as hydrogen bonding or covalent cross-linking between gelatin molecules and GSP, which effectively reinforced the mechanical structure of the gel (Ma et al., 2024). Simultaneously, the oil-holding capacity peaked at the 3% gelatin concentration, where the continuous and uniform gel network more effectively encapsulated and immobilized oil droplets through physical entrapment, thereby inhibiting oil migration and leakage. These findings align with the conclusions reported by Aryanti et al. (2025). However, when the gelatin concentration was further increased to 4%, both the gel strength and oil-holding capacity declined. This decrease may be due to excessive gelatin causing molecular aggregation or over-entanglement, which disrupted the homogeneity of the gel network and potentially even induced phase separation. Consequently, the structural integrity and encapsulation efficiency of the gel were compromised, a phenomenon also documented by Huang, Zhang et al. (2025) and Xue et al. (2025).

Fig. 2.

(a) Effect of gelatin concentration on gel strength (green squares, left y-axis) and oil-holding capacity (orange squares, right y-axis). (b) Effect of GSP concentration on oil-holding capacity (blue squares, left y-axis) and DPPH radical scavenging rate (purple squares, right y-axis) of emulsion gels. Vitamin E (VE) served as a positive control for the DPPH assay. Samples including MS (emulsion gel with 0% GSP), 0.1S (0.1% GSP), 0.2S (0.2% GSP), and 0.3S (0.3% GSP). (c) Low-Field Nuclear Magnetic Resonance (LF-NMR) water distribution maps of emulsion gels loaded different GSP concentrations. (d) Fourier transform infrared spectra of MR, 0.1S, 0.2S, 0.3S, butter, and oil gel. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

3.2. Effect of GSP concentrations on the oil-holding capacity of emulsion gel

The oil-holding capacity of camellia seed oil-based emulsion gels was significantly affected by the concentration of GSP. As illustrated in Fig. 2(b), the oil-holding capacity demonstrated a pronounced decrease with increasing GSP concentration, with the highest retention observed at 0.1% GSP. This finding was consistent with the results of Fu et al. (2025), who reported that moderate levels of polyphenols can optimize the gel network via hydrogen bonding with gelatin, thereby improving its oil encapsulation stability. However, as the GSP concentration increased to 0.2% and 0.3%, the oil-holding capacity declined. This behavior aligns with the observations of Huang, Xu et al. (2025), which suggest that an excess of polyphenols may promote protein aggregation or introduce steric hindrance, leading to a looser or more heterogeneous gel network and consequently impairing oil retention.

3.3. Analysis of antioxidant capacity

The in vitro antioxidant activity of emulsion gels containing different concentrations of GSP was evaluated using the DPPH radical scavenging assay, as summarized in Fig. 2(b). All samples exhibited strong antioxidant properties, with DPPH scavenging rates of 88.53%, 87.24%, and 87.68% at GSP concentrations of 0.1%, 0.2%, and 0.3%, respectively. Although the GSP concentration increased, the scavenging rate did not rise significantly but remained consistently high. This trend may be attributed to a loading saturation effect within the emulsion gel carrier system. These results align with the report by Yi et al. (2021), which suggested that gel network structures have a finite capacity for encapsulating bioactive compounds. When the concentration of active substances exceeds a critical threshold, their dispersion and release efficiency may reach a plateau or even decline. The slight fluctuations in scavenging rates observed in this study could also result from localized aggregation of GSP molecules at higher concentrations (Fan et al., 2023), limiting their accessibility to DPPH radicals. This composite emulsion gel demonstrates promising potential as a functional lipid-based delivery system with sustained antioxidant performance, warranting further investigation for practical applications.

3.4. Analysis of water distribution in emulsion gels at different GSP concentrations

As shown in Fig. 2(c), as the GSP concentration increased from 0.1% to 0.3%, the T₂ relaxation spectrum exhibited a systematic rightward shift. This shift was characterized by a reduction in the signal intensity within the T₂₁ region, accompanied by a corresponding increase in intensity in the T₂₂ and T₂₃ regions. These changes clearly indicated that higher GSP concentrations partially weaken the moisture-binding capacity of the gel network, resulting in enhanced moisture mobility within the system. This observation was consistent with the findings of Li et al. (2025), who reported that at lower concentrations, polyphenols can reinforce protein or polysaccharide gel networks through non-covalent interactions such as hydrogen bonding. However, when the polyphenol concentration exceeds an optimal level, excessive molecular interactions may disrupt the uniformity and compactness of the gel network, impairing interfacial stability and ultimately affecting the gel microstructure and its ability to immobilize moisture (Zhao et al., 2021). The rightward shift in T₂ relaxation times and the increase in the proportion of more mobile moisture observed in this study provide direct evidence for such structural loosening of the gel network at higher GSP concentrations.

3.5. Analysis of thermal properties

The crystallization and melting behaviors of GSP-loaded emulsion gels were analyzed by DSC to assess their physical state and stability under temperature variations. As shown in Fig. 3(a), Fig. 3(b) and Table 1, compared to the butter sample (T_pc = 20.0 °C, ΔH_c = 17.73 J·g⁻¹, T_pm = 39.4 °C, ΔH_m = 31.42 J·g⁻¹), the thermal properties of emulsion gels loaded with different concentrations of GSP (0, 0.1%, 0.2%, 0.3%) exhibited significant concentration-dependent non-monotonic variations.

Fig. 3.

Thermodynamic and rheological properties of emulsion gels loaded with different GSP concentrations. (a) Melting curve, (b) crystallization curve, (c) frequency sweep curve, and (d) shear viscosity curve. Peak crystallization temperature (T_pc) and peak melting temperature (T_pm).

Table 1.

Thermal characteristics analysis of emulsion gels loaded with different GSP concentrations.

Sample	Crystallization curve		Melting curve
	Tpc/°C	ΔHc/J·g−1	Tpm/°C	ΔHm/J·g−1
Butter	20.0 ± 0.02c	17.73 ± 0.02a	39.4 ± 0.02c	31.42 ± 0.01d
MS	47.3 ± 0.02a	3.436 ± 0.02b	107.5 ± 0.02b	230.1 ± 0.02b
0.1S	46.8 ± 0.01b	3.303 ± 0.02b	109.2 ± 0.01a	265.1 ± 0.02b
0.2S	46.9 ± 0.01b	3.264 ± 0.01d	105.5 ± 0.02b	111.6 ± 0.01c
0.3S	47.1 ± 0.01a	2.574 ± 0.02c	110.8 ± 0.02a	339.2 ± 0.03a

Note: T_pc, peak crystallization temperature, ΔH_c, crystallization enthalpy, T_pm, peak melting temperature, ΔH_m, melting enthalpy.

Sample codes: Butter, control, MS, emulsion gel without GSP, 0.1S, 0.2S, 0.3S, emulsion gels containing 0.1%, 0.2%, and 0.3% (w/w) GSP, respectively.

Specifically, compared with the sample without GSP (MS), the 0.1% GSP sample showed increased melting temperature (T_pm) and melting enthalpy (ΔH_m), while the 0.2% GSP sample displayed a decrease, and the 0.3% GSP sample exhibited the highest values. This non-monotonic behavior may be attributed to a concentration-dependent molecular reorganization within the polyphenol-gel matrix. At 0.1% GSP, the polyphenols might act as molecular bridges, forming hydrogen bonds and hydrophobic interactions with the gel network (e.g., proteins or polysaccharides) (Hao et al., 2025). This moderate crosslinking could provide a more ordered interfacial template for fat crystallization, leading to higher melting temperature and enthalpy, possibly related to the formation of thermodynamically more stable crystal polymorphs (Duan et al., 2025). When the GSP concentration increased to 0.2%, excess polyphenol molecules may competitively adsorb onto fat-water interfaces and crystal growth sites, thereby hindering the ordered packing of lipid molecules, introducing lattice defects, and reducing crystallinity. This is suggested by the simultaneous decrease in both crystallization and melting enthalpies (Barroso et al., 2024). The reversal observed at 0.3% GSP might be explained by the GSP molecules could self-assemble via π-π stacking and additional hydrogen bonds into nano-aggregates. These aggregates may act as multivalent crosslinking hubs, generating a denser and more homogeneous composite network (Yu et al., 2025).

3.6. Analysis of FTIR

As shown in Fig. 2(d), the FTIR spectra of emulsion gels with different GSP concentrations exhibited notable changes primarily in the region of 3000–3500 cm⁻¹, which corresponds to the N—H stretching vibration in gelatin. Specifically, compared to the MR sample (without GSP), the 0.1R sample displayed a distinct increase in peak intensity and broadening of the peak area. In contrast, the 0.2R and 0.3R samples showed weaker peak intensities with broad, flattened shapes, gradually resembling the MR profile. Meanwhile, the characteristic peaks related to lipids (C—H stretching at 2918–2921 and 2851–2853 cm⁻¹, C O at 1742–1743 cm⁻¹, C—H bending at 1462–1465 cm⁻¹, and C—O stretching at 1159–1162 cm⁻¹) remained largely unchanged, indicating that the basic functional group structures of lipids were not disrupted, consistent with Wang et al. (2022).The concentration-dependent spectral variations in the N—H stretching region can be attributed to hydrogen bonding interactions between GSP and gelatin (Hao et al., 2022). Collectively, the FTIR, LF-NMR, and DSC data mutually confirmed that GSP modulates the emulsion gel structure primarily through hydrogen bonding interactions in a concentration-dependent manner.

3.7. Analysis of rheological properties

As shown in Fig. 3(c) and Fig. 3(d), emulsion gels loaded with different concentrations of GSP exhibited significantly enhanced rheological properties with increasing concentration during both dynamic oscillatory and steady-state shear tests. During dynamic frequency scanning (Fig. 3(c)), both the storage modulus (G′) and loss modulus (G′′) systematically increased with rising GSP concentration, with G′ consistently exceeding G′′, indicating the system maintained predominantly elastic, semi-solid gel behavior throughout. This is analogous to the rheological characteristics of the solid fat networks typically studied by Chen et al. (2025), such as butter. These networks exhibit a dominant elastic response coupled with good structural stability. This also indicated that GSP interacts with emulsion gel components via non-covalent forces such as hydrogen bonding, forming a denser and more stable gel network that significantly enhances the three-dimensional network structure of emulsion gel (Montes et al., 2024). In steady-state shear tests (Fig. 3(d)), the apparent viscosity also increased markedly with rising GSP concentration. Notably, all systems exhibited pronounced shear thinning behavior, particularly within the low shear rate range (Liu, Ruan, et al., 2025). This indicated that the network structure formed by GSP exhibits substantial steric hindrance under static or low-shear conditions while undergoing reversible disruption under high shear (Hao et al., 2023). Overall, GSP, as a natural polyphenolic compound, effectively constructs and enhances the solid-like structure and shear adaptability of emulsion gels. By regulating GSP concentration, products can be specifically engineered to replace traditional butter.

3.8. Analysis of cookie quality

3.8.1. Sensory evaluation

As shown in the sensory evaluation results (Fig. 4(a)), it demonstrated that lower GSP concentrations positively enhanced most sensory properties, whereas higher concentrations generally led to a decline in overall acceptability. At an appropriate GSP concentration, the cookie cross-section exhibited a uniform and fine porous structure (Fig. 4(b)), which corresponded to higher scores in texture and structural consistency. This improvement can be attributed to the ability of the emulsion gel to optimize dough rheology and promote a well-formed network during baking (Sereti et al., 2023). Moreover, the enhanced appearance scores may result from the facilitated Maillard reaction and the antioxidant effect of GSP, which help maintain an appealing color (Tumbas Šaponjac et al., 2016). However, when the GSP concentration increased to 0.2% and 0.3%, the internal structure became coarse and uneven, accompanied by a noticeable drop in sensory ratings, particularly in flavor and texture. This deterioration likely stems from excessive gelation interfering with gluten development, thus undermining the structural integrity of the cookies (Wang, Jiao, et al., 2025). In addition, the pronounced bitterness imparted by high polyphenol levels markedly compromised the original sweet and aromatic flavor profile.

Fig. 4.

Quality characteristics of cookies prepared with different formulations. (a) Sensory attribute, (b) cross-sectional view, (c) color change, and (d) LF-NMR moisture distribution map. KBQ refers to butter-based cookies (control group), and 0.1SQ, 0.2SQ, and 0.3SQ refer to cookies prepared with emulsion gels containing 0.1%, 0.2%, and 0.3% GSP, respectively.

3.8.2. Color analysis

As shown in Fig. 4(c), at lower GSP concentrations, the cookies exhibited favorable color properties, with a notably higher lightness value (L* = 21.13) compared to the control sample KBQ (L* = 18.33). This improvement can be attributed to the lipid components in the emulsion gel enhancing surface gloss and light reflectance, and the antioxidant activity of GSP moderately suppresses excessive advancement of the Maillard reaction in the later stages of baking, thereby limiting the over-accumulation of brown pigments and preventing premature darkening (Caponio et al., 2024). However, as the GSP concentration increased to 0.2% and 0.3%, the L* values gradually decreased, falling below that of the control. This is primarily due to the intrinsic dark hue of flavonoid pigments in GSP, which becomes dominant after high-temperature treatment and leads to noticeable darkening of the product (Tumbas Šaponjac et al., 2016). In addition, variations in the a* and b* values suggest complex interactions among GSP, Maillard reaction intermediates, and lipid oxidation products during baking (Liang et al., 2024).

3.8.3. Analysis of moisture distribution

As illustrated in Fig. 4(d), compared to the control sample, cookies with added emulsion gel showed a distinct rightward shift in moisture relaxation time, reflecting increased water mobility within the samples. Notably, the 0.1SQ sample exhibited the most favorable overall quality. This can be explained by the ability of an appropriate GSP concentration to promote moderate protein cross-linking, leading to a uniform network that effectively retains moisture and contributes to improved textural properties (Muntaha et al., 2025). In contrast, excessively high GSP levels may over-bind gluten proteins and compete for hydration sites, weakening the gel network, reducing moisture-holding capacity, and significantly compromising the storage stability (Mei et al., 2025).

3.9. Analysis of volatile compounds

As illustrated in Fig. 5, compared with the control group (KBQ), the volatile flavor compound profiles of cookies incorporated with GSP-loaded emulsion gel exhibited distinct concentration-dependent trends, which could be ascribed to the antioxidant activity of GSP and its modulatory effect on Maillard reaction pathways (Nooshkam et al., 2019). Notably, pyrazines, the core Maillard-derived flavor contributors in cookies, displayed pronounced dynamic changes. 2,3,5-trimethylpyrazine was not detected at high GSP concentrations, while 2-acetylpyrazine was exclusively present in GSP-supplemented samples, consistent with (Ren et al., 2024), who reported that polyphenols can selectively suppress or promote specific pyrazine formation pathways via scavenging reactive carbonyl intermediates or altering the local redox and pH environment. Furthermore, the three-dimensional network structure of the emulsion gel likely exerts a regulatory effect on the encapsulation and release behavior of volatile flavor compounds, aligning with the mechanism reported by Lei et al. (2025). Among other flavor categories, alcohols demonstrated relatively high stability across all GSP supplementation levels, whereas ketones and lactones were minimally affected by GSP addition, while aldehydes, phenolics, and esters showed obvious concentration-dependent fluctuations. Collectively, these findings demonstrate that different families of flavor compounds exhibit significant differential sensitivity to GSP intervention and emulsion gel matrix effects.

Fig. 5.

Volatile flavor compounds and their types in cookies prepared with different formulations. (a) Composition of volatile flavor compounds and (b) frequency distribution of individual compounds across nine volatile compound classes, including pyridines, pyrroles, pyrazines, alcohols, phenolics, aldehydes, acids, ketones, and esters.

3.10. Analysis of digestive characteristics

As shown in Fig. 6(a), the addition of GSP effectively reduced the starch digestion rate. Compared with the control group, the RDS content significantly decreased with increasing GSP concentration, while the RS level showed a corresponding upward trend. This observation aligns with findings reported by Fan et al. (2025), indicating that polyphenols can interact with starch through hydrogen bonding and hydrophobic interactions to form enzyme-resistant V-type inclusion complexes, thereby converting digestible starch into resistant forms. The dynamic digestion curve in Fig. 6(b) clearly demonstrated this structural modification, as samples containing GSP exhibited lower hydrolysis rates and a more gradual digestion profile compared to the control group, suggesting delayed enzymatic degradation. Further studies by Wang, Zhang, et al. (2025) confirmed that polyphenols not only competitively inhibit amylase activity but also physically block the enzyme active site by altering starch aggregation states. GSP-loaded emulsion gels regulate starch digestion in cookies through dual mechanisms of physical encapsulation and biochemical inhibition, offering a promising strategy for developing functional baked products with a low glycemic index.

Fig. 6.

In vitro digestion characteristics of cookies prepared with different formulations. (a) The percentages of rapidly digestible starch (RDS), slowly digestible starch (SDS), and resistant starch (RS) relative to total starch and (b) starch hydrolysis rate during simulated intestinal digestion.

3.11. Analysis of shelf life prediction

Lipid oxidation in food products adheres to first-order reaction kinetics. In this investigation, linear regression analysis was conducted by plotting the natural logarithm of peroxide values (ln(PV)) of cookies from various experimental groups against storage time (t), with the findings detailed in Fig. 7 and Table 2. The KBQ group, which lacked added functional ingredients, demonstrated the shortest shelf life of merely 244 days. Conversely, the incorporation of GSP-loaded camellia seed oil emulsion gels significantly prolonged the shelf life of the cookies. In addition to oxidative stability, moisture migration, texture evolution, and microbial stability may also influence the actual shelf life of baked products. Specifically, the shelf lives of the 0.1SQ, 0.2SQ, and 0.3SQ samples were extended to 390, 444, and 468 days, respectively, representing 1.60, 1.82, and 1.92 times that of the KBQ group. This trend clearly indicates that the addition of GSP effectively mitigates lipid oxidation in cookies. The potent antioxidant capacity of GSP is closely linked to its mechanism of action, wherein hydrogen atoms donated by the polyphenolic structure neutralize lipid free radicals, aligning with the findings reported by Le Tan et al. (2025). Meanwhile, the kinetic model indicates that the activation energies of the oxidation reactions of all samples increase systematically, suggesting that lipid oxidation requires higher energy. This theoretically confirms that emulsion gels can effectively enhance the oxidative stability of cookies (Shu et al., 2025). These findings further substantiate that the inclusion of GSP-loaded emulsion gels to augment the antioxidant properties of formulations constitutes an effective strategy for significantly prolonging the shelf life of cookies.

Fig. 7.

Changes in the peroxide value of cookies during storage at different temperatures. (a-c) Peroxide value of cookies versus storage time at 30 °C (a), 50 °C (b), and 70 °C (c), and (d) regression equations for the increase in peroxide value over time, where K is the oxidation rate constant and T is the storage temperature.

Table 2.

Predicted shelf life of cookies formulated with emulsion gels loaded with different GSP concentrations.

Sample	Prediction model	Shelf life prediction/d
KBQ	$\mathrm{S}=\frac{\ln \left({\mathrm{PV}}_{\mathrm{L}}\right)-\ln \left({\mathrm{PV}}_0\right)}{{\mathrm{e}}^{(3.8209-\frac{2490.7}{T})}}$	244
0.1SQ	$\mathrm{S}=\frac{\ln \left({\mathrm{PV}}_{\mathrm{L}}\right)-\ln \left({\mathrm{PV}}_0\right)}{{\mathrm{e}}^{(5.7001-\frac{3210.8}{T})}}$	390
0.2SQ	$\mathrm{S}=\frac{\ln \left({\mathrm{PV}}_{\mathrm{L}}\right)-\ln \left({\mathrm{PV}}_0\right)}{{\mathrm{e}}^{(5.8502-\frac{3285.4}{T})}}$	444
0.3SQ	$\mathrm{S}=\frac{\ln \left({\mathrm{PV}}_{\mathrm{L}}\right)-\ln \left({\mathrm{PV}}_0\right)}{{\mathrm{e}}^{(5.9503-\frac{3320.6}{T})}}$	468

Note: The shelf life (S) is estimated using an Arrhenius-type lipid oxidation kinetics model from peroxide value (PV) data assuming a constant temperature of 25 °C.

Sample codes: KBQ, control cookies prepared with butter, 0.1SQ, 0.2SQ, 0.3SQ, cookies containing emulsion gels with 0.1%, 0.2%, and 0.3% (w/w) GSP, respectively.

Model parameters: PV₀, initial PV (meq/kg), PV_L, limit PV (meq/kg) at the end of S, T, absolute storage temperature. The numerical constants (e.g., 3.8209, 2490.7) are pre-exponential and activation energy terms derived from regression analysis of experimental PV data at different temperatures.

4. Conclusion

This study successfully developed a GSP-loaded camellia seed oil-based emulsion gel. Under conditions of a 7:3 oil-to-water ratio and 3% gelatin concentration, the gel exhibited an oil-holding capacity of 89.5% with a uniform structure. The addition of 0.1% GSP enhanced the gel network via hydrogen bonding, resulting in an 88.53% DPPH radical scavenging rate. However, excessive addition increased water mobility while reducing water-holding capacity. Rheological analysis demonstrated that GSP significantly elevated the modulus and viscosity, conferring a more solid-like structure and shear-thinning behavior to the system. When this emulsion gel was used as a partial butter substitute in cookies, the formulation with 0.1% GSP yielded optimal sensory scores. In vitro digestion experiments revealed a 4.7% reduction in rapidly digestible starch (RDS) and a 7.9% increase in resistant starch (RS), indicating significantly delayed starch digestion. Furthermore, the antioxidant properties of GSP extended the shelf life of cookies to 1.6–1.9 times that of the control sample. In summary, this emulsion gel shows good potential for functional ingredient delivery and fat structure modification in cookies. Though further research is needed to evaluate its performance in other baked or processed food systems and to explore a broader range of GSP concentrations.

CRediT authorship contribution statement

ZongHai Huang: Writing – original draft, Visualization, Data curation. KaiYue Liu: Writing – original draft, Visualization, Data curation. XinYi He: Writing – review & editing, Visualization. Yun Li: Project administration, Funding acquisition. Hang Li: Supervision, Conceptualization. Jia Hao: Writing – review & editing, Formal analysis. BaiNing Lin: Supervision, Project administration, Funding acquisition, Conceptualization. ZhiHong Xiao: Supervision, Project administration, Funding acquisition, Conceptualization. LuYang Cai: Supervision, 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.