Physicochemical characteristics of cost-effective and high-quality plant-based meat analogues prepared from soybean meal and soybean powder

Abstract

The limited market adoption of plant-based meat analogues (PBMA) stems from high costs and suboptimal texture. Low-moisture extrusion, the dominant industrial-scale production method for PBMA, offers advantages in cost-efficiency and versatility but remains constrained by material-dependent texture limitations. We innovatively employed low-cost soybean meal (SM) and soybean powder (SP) for PBMA production. Optimizing SM:SP ratios (9:1–5:5) enhanced textural, structural, and cost attributes. Evaluated parameters included hardness, chewiness, fiber degree (FD), porosity, water absorption capacity (WA), water holding capacity (WHC), and protein secondary structures. The 7:3 ratio achieved optimal performance: maximal FD (1.53), balanced hardness, highest springiness (0.93), and uniform porosity (34.78 %). Excessive SP (>30 %) compromised structural integrity, increasing brittleness and reducing WHC. FTIR analysis revealed that the 7:3 ratio promoted α-helix formation enhancing elasticity, while β-sheet content (38.74 %) improved hardness. Quadratic polynomial predictive models demonstrated high accuracy (R² = 0.845–0.999) and effectively correlated SP ratios with quality attributes, enabling tailored PBMA formulations.

Highlights

• •Soybean meal (SM) and Soybean powder (SP) yield premium plant-based meat analogues (PBMA).
• •Adjusting the ratio of SM and SP improve the texture of PBMA.
• •PBMA achieves the best performance when the ratio of SM:SP is 7:3.
• •The prediction model related to SP ratio will be related to the quality characteristics of PBMA.

1. Introduction

Global population growth will drive a 30–50 % increase in protein demand by 2050, while traditional animal husbandry will fail to meet this demand (Jiang et al., 2024). In fact, the production process of meat protein consumes a lot of resources and damages the ecological environment. In addition, excessive intake of meat products will gradually increase the probability of human illness and cause health and ethical problems (Hashempour-Baltork et al., 2020). Therefore, the development of healthy, environmentally friendly and sustainable meat substitutes has become the focus of current research (Jiang et al., 2024; Wang et al., 2024). Plant-based meat analogues (PBMA) are an excellent substitute for animal meat (Singh et al., 2021). They are mainly made of plant protein and can effectively simulate the taste, texture and appearance of traditional meat with the help of modern food processing technologies such as extrusion (Zhang, Zhao, et al., 2023), spinning (Cui et al., 2023), shearing (Ryu et al., 2023) and 3D printing (Qiu et al., 2023). Compared with animal meat produced by traditional animal husbandry, plant protein not only greatly conserve water and land resources but also offer advantages in safety, health, and low carbon footprint (Rout and Srivastav, 2024b, Rout and Srivastav, 2024a). Based on these advantages, PBMA made from plant protein is increasingly attracting people's attention.

Extrusion technology currently represents the most mature and effective approach for achieving large-scale commercialization of PBMA (Bain et al., 2020). This technique performs sequential precision processing operations including hydration, conveyance, fragmentation, kneading, shearing, homogenization, thermal treatment, and molding within an enclosed chamber. Through the combined actions of high temperature, high pressure, high shear forces, and frictional forces generated by screw extrusion, it offers notable advantages such as low energy consumption, high production efficiency, user-friendly operation, and versatile functionality. Based on the moisture content of final extruded products, extrusion technologies are primarily categorized into low-moisture extrusion (20–40 % moisture) and high-moisture extrusion (40–80 % moisture) (Jiang et al., 2024; Zhao et al., 2024). However, the application of high-moisture extrusion in PBMA production has been limited by several drawbacks, including expensive equipment, limited product variety, bacterial susceptibility, and high storage/transportation costs (Dinali et al., 2024). In contrast to high-moisture extrusion, low-moisture extrusion offers multiple advantages such as mature technology, low production cost, diverse product range, simple post-processing, and reduced transportation expenses (Lazou, 2024). In recent years, low-moisture extrusion has been extensively investigated for optimizing the textural, nutritional, and sensory properties of PBMA (Jang & Lee, 2024). This technology enables precise control over protein denaturation and reorganization, facilitating the formation of anisotropic fibrous structures that mimic the mouthfeel of conventional meat (Ribeiro et al., 2024). Researchers have successfully utilized low-moisture extrusion to process diverse plant protein sources (e.g., soy, pea, rice) into layered or aligned fiber networks through tailored combinations of screw configuration, moisture gradients, and thermal-mechanical stress (Lee, Oh, et al., 2022). Currently, low-moisture extrusion technology serves as the dominant method for large-scale PBMA production (Lee, Choi, & Han, 2022).

Fiber structure plays an important role in maintaining the overall quality, juiciness and flavor of PBMA, serving as a critical indicator for evaluating their similarity to conventional animal meat (Jiang et al., 2024). Studies have demonstrated that PBMA produced from single protein plant proteins exhibit suboptimal texture and low structural resemblance to animal meat (Zhao et al., 2024). It is an effective way to improve the structure and quality of plant-based food by compounding plant proteins from different sources (Rout and Srivastav, 2023, Rout and Srivastav, 2025; Wang et al., 2024). Soybean protein isolate(SPI), zein, pea protein isolate(PPI), wheat gluten(WG), peanut protein isolate and other plant proteins can effectively enhance the fiber structure and texture characteristics of PBMA (da Trindade et al., 2024; R. Zhang, Yang, et al., 2023). However, the relatively high prices of these plant proteins lead to the final selling price of PBMA being at a disadvantageous position compared with animal meat. Our collaborative research with industry partners has revealed that elevated production costs constitute the primary limiting factor impeding the widespread commercialization of PBMA. Soybean meal (SM) and soybean powder (SP), as commercially available plant protein sources, demonstrate advantages such as simple preparation processes, rich nutrition, easy accessibility, balanced amino acid composition, high bioavailability, and low cost (Wang et al., 2024). Notably, these soybean processing byproducts are priced at merely 20 %–40 % of SPI. Our prior research revealed that PPI-SM composite systems and SPI-WG-SP hybrid systems could fabricate PBMA with highly fibrous structures while achieving approximately 10 % reduction in production costs (Jiang et al., 2024; Wang et al., 2024). This study demonstrates that compared to using high-cost plant proteins (such as SPI, PPI, WG, etc.), employing a 7:3 ratio of SM to SP can reduce production costs by over 30 % (Jiang et al., 2024; Wang et al., 2024). Furthermore, synergistic interactions between SM and SP may optimize the textural properties and fibrous structure of PBMA through complementary effects. However, inherent differences in their physicochemical properties and interaction mechanisms necessitate systematic investigation into the SM/SP ratio optimization during low-moisture extrusion processing. This critical parameter requires comprehensive characterization to elucidate its impact on PBMA texture and fiber structure development.

Therefore, in this study, SM and SP were blended at varying ratios (9:1, 8:2, 7:3, 6:4, 5:5) based on our preliminary experimental results. PBMA was prepared via low-moisture extrusion. The fibrous structure of PBMA was observed using scanning electron microscopy (SEM), and changes in protein secondary structure were analyzed via Fourier transform infrared (FTIR) spectroscopy. By evaluating hardness, chewiness, springiness, fiber degree, apparent density, true density, porosity, water absorption capacity, and water holding capacity, the effects of SM/SP blending ratios on PBMA quality attributes were systematically investigated. In addition, a set of equations with a mixing ratio of SP was established using model-fitting results to predict the values for the quality characteristics of the PBMA. Furthermore, these derived equations allow the prediction of quality attribute values for PBMA formulated with varying SP ratios (10–50 %).

2. Materials and methods

2.1. Materials

SM and SP were provided by Shandong Yuwang Ecological Food Industry Co., Ltd. (Shandong, China). Specifically, SM contained approximately 51.3 % protein, 30 % carbohydrate, 7.6 % dietary fiber, 3.3 % fat, and 11 % moisture. SP contained about 44.2 % protein, 30 % carbohydrate, 6.0 % dietary fiber, 7.9 % fat, and 8.0 % moisture. All other chemicals and reagents used in the experiments were analytically pure.

2.2. PBMA preparation by low-moisture extrusion

The preparation method of SM-SP composite extrudates was determined by appropriately modifying our previous research methods (Jiang et al., 2024; Wang et al., 2024). Extrusion experiments were performed using an ETT65-20D twin-screw extruder (Jinan Zhennuo Machinery Co., Ltd., Jinan, China). SM and SP were mixed at ratios of 9:1, 8:2, 7:3, 6:4, and 5:5 (w/w), respectively. Appropriate deionized water was added, and the mixtures were uniformly blended in a mixer. The moisture content of the preliminarily mixed raw materials was approximately 30 % (w/w). Before the extrusion experiment, the twin-screw extruder was preheated for 1.5 h. The preheating temperatures of the four heating zones along the extrusion direction were set as 190, 210, 270, and 270 °C in sequence. After preheating, the preliminarily mixed raw materials were added into the barrel of a low-moisture extruder for secondary mixing, followed by the extrusion experiment. The temperatures of the four zones along the extrusion direction were set as 165, 200, 220, and 210 °C in sequence, with a screw speed of 320 r/min and a feeding rate of 12 kg/h. Part of the extrudates were dried in a dryer for 30 min, while another part was subjected to vacuum freeze-drying, crushed, and passed through a 100-mesh standard sieve for subsequent analytical experiments.

2.3. Morphological characterization

2.3.1. Visual appearance

Surface and cross-sectional morphologies of PBMA samples were observed using a Canon EOS R50 digital camera (Canon Inc., Tokyo, Japan). All samples were photographed under standardized conditions with identical background panels to ensure consistency.

2.3.2. Microstructure

The microstructure of PBMA was examined via scanning electron microscopy (SEM) based on previous research methods (Peng et al., 2022) with appropriate modifications. Briefly, PBMA samples were sectioned into small fragments using a surgical blade and fixed in 2.5 % (v/v) glutaraldehyde solution for 12 h at 4 °C. The fixed samples were rinsed three times with phosphate-buffered saline (PBS, 0.1 M, pH 7.2) at room temperature. Sequential dehydration was performed using graded ethanol solutions (30 %, 50 %, 70 %, 80 %, 90 %, and 100 %) with three 12-min washes per concentration. Subsequently, the samples were stabilized in acetone for 15 min and freeze-dried (Labconco FreeZone, USA) for 48 h. Prior to SEM imaging, freeze-dried samples were mounted on aluminum stubs, sputter-coated with gold, and observed under high vacuum at an accelerating voltage of 5 kV.

2.4. Texture properties

The method for detecting the textural properties of SM-SP composite extrudate samples was determined by modifying the previous research methods (Nakagawa et al., 2024; Zhang, Zhao, et al., 2023). The texture properties of PBMA were analyzed by Brookfield CT3 texture analyzer (Brookfield, WI, USA). Specifically, extrudate samples were mounted on a platform, and their textural properties were analyzed using a Texture Analyzer. The TPA (Texture Profile Analysis) mode was selected for detection, with the probe descending speed set at 2.0 mm/s, testing speed at 1.0 mm/s, ascending speed at 2.0 mm/s, compression ratio set at 40 %, and interval between two compressions set at 4.0 s. Hardness, springiness, chewiness, and cohesiveness were recorded respectively to analyze the textural characteristics of the samples.

2.5. Fiber degree

The method of determining the sample fiber degree (FD) refers to the research of Deng et al. (2023) and has been modified appropriately. Specifically, PBMA samples were cut into rectangular pieces with a length of 10 mm, width of 10 mm, and height of 5 mm. Then, the samples were compressed to 75 % of their original thickness at a speed of 1.0 mm/s along vertical and parallel directions, respectively. The lengthwise shear force (FL) and crosswise shear force (FC) were defined as the maximum force required to cut the samples in the vertical and parallel directions, respectively. The FD was shown as the ratio of FL to FC.

2.6. Color

A quantitative analysis protocol for the color characteristics of SM-SP composite extrudates was successfully established by modifying existing methodologies (Nakagawa et al., 2024). The color changes of PBMA were detected using an NR60CP+ handheld color difference meter manufactured by Shenzhen Sanenshi Technology Co., Ltd. (China). The L* (lightness), a* (+: redness/−: greenness), and b* (+: yellowness/−: blueness) values were recorded and compared with initial readings to quantify color variation. Measurements were performed in triplicate, and mean values were calculated. Prior to analysis, the instrument was calibrated against a standard white tile (L*₀ = 97.85, a*₀ = −0.01, b*₀ = 1.43) under standardized background conditions. The total color difference (ΔE) was calculated using the following formula:

$$\mathit{\Delta E}=\sqrt{\left(L^{\ast }-L_0^{\ast }\right)+\left(a^{\ast }-a_0^{\ast }\right)+\left(b^{\ast }-b_{)}^{\ast }\right)}$$ (1)

2.7. Apparent density

The method for determining the apparent density of PBMA was established based on the method previously described by Lee, Oh, et al. (2022) with some modifications. PBMA was cut into small pieces approximately 1.5 cm in length. The apparent density (ρₐ) of PBMA was determined by dividing the mass of a PBMA by its volume, as calculated by the following formula:

$$\begin{array}{c}{\rho }_a\left(g/{\mathit{cm}}^3\right)=\frac{\mathit{Mass\; of\; PBMA}\left(g\right)}{\mathit{Volume\; of\; PBMA}\left({\mathit{cm}}^3\right)}\end{array}$$ (2)

In this study, PBMA samples were cylindrical in shape. Thus, the volume of PBMA was calculated using the formula for the volume of a cylinder, as follows:

$$\begin{array}{c}\mathit{Volume\; of\; PBMA}\left({\mathit{cm}}^3\right)=\pi r^{2}h\end{array}$$ (3)

where r (cm) and h (cm) are the diameter and length of the TBMA, respectively.

2.8. True density

The method for measuring the true density of PBMA samples was modified from the approach described by Sakai et al. (2025). Specifically, the lyophilized PBMA powder was loaded into a cylinder, and the outer wall of the cylinder was gently tapped to remove air gaps between the debris. The volume and weight of the sample were then recorded. The true density (ρ_b) was calculated as the ratio of weight to volume (g/cm³), as calculated by the following formula:

$$\begin{array}{c}{\rho }_b\left(g/{\mathit{cm}}^3\right)=\frac{\mathit{Mass\; of\; PBMA\; powder}\left(g\right)}{\mathit{Volume\; of\; PBMA\; powder}\left({\mathit{cm}}^3\right)}\end{array}$$ (4)

2.9. Porosity

The porosity of PBMA is related to ρ_a and ρ_b (Lee, Oh, et al., 2022), with the specific calculation formula as follows:

$$\begin{array}{c}\text{Porosity}\left(\%\right)=\frac{{\rho }_b-{\rho }_a}{{\rho }_b}\times 100\end{array}$$ (5)

2.10. Water absorption capacity and water holding capacity

The water absorption capacity (WA) and water holding capacity (WHC) of PBMA were determined with appropriate modifications based on methods described in previous studies (Lee, Choi, & Han, 2022). Specifically, oven-dried PBMA samples were sectioned into 3 cm-length pieces and weighed to obtain the initial mass (recorded as W₁). The samples were then immersed in 500 mL of ultrapure water at room temperature for 1 h. After immersion, the hydrated samples were gently blotted with filter paper to remove surface moisture and reweighed to record the saturated mass (W₂). The WA was calculated using the following formula:

$$\begin{array}{c}\mathit{WA}\left(\%\right)=\frac{W_2-W_1}{W_1}\times 100\end{array}$$ (6)

For WHC determination, the hydrated samples (W₂) were subjected to centrifugation using an industrial centrifuge at 4000 rpm for 2 min to remove excess water. The the weight of the samples was measured and recorded as W₃. The WHC was calculated as follows:

$$\begin{array}{c}\mathit{WHC}\left(\%\right)=\frac{W_3-W_1}{W_1}\end{array}$$ (7)

2.11. Low-field nuclear magnetic resonance (LF-NMR)

The moisture distribution state of PBMA was evaluated using low-field nuclear magnetic resonance (LF-NMR). The detection method established based on previous studies following appropriate parameter adjustments (Kang et al., 2023). PBMA samples were placed in cylindrical glass tubes, and transverse relaxation time (T2) signals were acquired using the Carr-Purcell-Meiboom-Gill (CPMG) pulse sequence. The collected signals were subjected to inversion fitting to generate T2 relaxation spectra. The relative proportions of water populations were quantified by calculating the integral area ratios of distinct peaks in the T2 spectrum, thereby characterizing water distribution and migration dynamics.

2.12. Protein secondary structure

Changes in the protein secondary structure of PBMA were determined and analyzed using Fourier transform infrared spectroscopy (FTIR) following a method adapted from our previous study with minor modifications (Jiang et al., 2024). The infrared spectra of the samples were obtained with a STA-6000 FT-IR spectrometer (PerkinElmer, Shelton, USA). Briefly, freeze-dried PBMA powder (1 mg) was thoroughly mixed with dried potassium bromide (KBr, 100 mg) in an agate mortar and pressed into translucent pellets (∼1 mm thickness) using a hydraulic press. The pellets were loaded into the sample holder, and FTIR spectra were acquired under nitrogen purge after background subtraction. Spectral acquisition parameters included a resolution of 4 cm⁻¹, scan range of 400–4000 cm⁻¹, and accumulation of 64 scans. The amide I band (1600–1700 cm⁻¹) was deconvoluted and analyzed using second-derivative spectroscopy in PeakFit software (v4.12, Systat Software Inc., USA). Gaussian/Lorentzian peak fitting was applied to resolve overlapping bands, and the relative proportions of secondary structure components (α-helix, β-sheet, β-turn, random coil) were quantified based on integrated peak areas.

2.13. Predictive modeling of PBMA quality attributes based on SM/SP mixing ratios

A predictive model for PBMA quality attributes was established based on SM (soy meal) and SP (soy protein) mixing ratios, following a modified methodology derived from previous studies (Lee, Choi, & Han, 2022). Nine key quality attributes were evaluated: hardness, chewiness, springiness, FD, ρ_a, ρ_b, porosity, WA, and WHC. The quadratic polynomial model (Eq. 8) was employed for analysis using OriginPro 2024 (v10.0, OriginLab Corporation, USA).

$$\begin{array}{c}y=a{x}^2+\mathit{bx}+c\end{array}$$ (8)

where y (unit varies by quality attribute) is the predicted value of PBMA quality attributes, and x represents the percentage content of SP (%, w/w).

2.14. Statistical analysis

All statistical analyses were performed using IBM SPSS Statistics (Version 27.0; IBM Corp., Armonk, NY, USA). Data normality and homogeneity of variances were verified using Shapiro-Wilk and Levene's tests, respectively. Significant differences among experimental groups were assessed via one-way analysis of variance (ANOVA), followed by Duncan's multiple range test for post hoc pairwise comparisons. A significance threshold of P < 0.05 was applied for all statistical interpretations. To ensure reproducibility, each treatment was independently replicated three times (biological replicates, n = 3). Quantitative results are presented as means ± standard deviation (SD).

3. Results and discussions

3.1. Morphological analysis

Figs. 1(A) and 1(B) illustrate the surface and cross-sectional morphological structures of PBMA with different SM to SP ratios. The results demonstrate that the SM:SP ratio significantly influences the macroscopic structure of PBMA. At an SM:SP ratio of 9:1, visible cracks were observed on the PBMA surface. These cracks gradually diminished as the SP proportion increased from 9:1 to 7:3. Notably, at the 7:3 ratio, the PBMA surface exhibited almost no significant cracks. The high lipid content in SP (7.9 %) acted as a plasticizer, reducing intermolecular friction between SM-derived proteins. This enhanced protein chain mobility during extrusion, enabling homogeneous reorganization into a cohesive network. Simultaneously, lipids occupied hydrophobic pockets in soy proteins, mitigating stress concentration at interfacial regions and suppressing microcrack initiation (Sun et al., 2022). However, further increasing the SP proportion (6:4 and 5:5 ratios) led to the reappearance of surface cracks. Excessive SP fat may coat protein cross-linking sites, weakening the interaction strength between SM and SP proteins. This disruption, combined with localized drying shrinkage during processing, promoted the formation of microcracks. Fig. 1(B) shows that at the SM:SP ratio of 9:1, the cross-sectional porosity of PBMA was minimal. As the SP proportion increased, porosity gradually rose, reaching the most uniform pore distribution at the 7:3 ratio. These uniformly distributed pores can absorb local stress and suppress crack propagation (Cheng et al., 2024). These results further corroborate the underlying mechanism for the minimal surface cracks in PBMA at a 7:3 SM:SP ratio.

Fig. 1.

Effect of SM and SP ratio on the surface (A), cross-sectional (B), and microstructure (C) of PBMA.

The microstructure of PBMA is a critical indicator reflecting their physicochemical properties and provides insights into their composition and unique characteristics (Dekkers et al., 2018). Fig. 1(C) displays the microstructural images of PBMA at 300× magnification, revealing distinct changes in pore morphology with increasing SP proportions. These observations align with the cross-sectional porosity trends shown in Fig. 1(B). At an SM:SP ratio of 9:1, PBMA exhibited few air pores. As the ratio shifted from 9:1 to 7:3, the number of air pores increased progressively, accompanied by an expansion in pore area. At the 7:3 ratio, the number of air pores reached the maximum within the visual field, with the most uniform distribution, and no obvious structural collapse was observed. This optimal microstructure can be attributed to the formation of a continuous three-dimensional gel network through synergistic interactions between SP and SM. The network effectively trapped water vapor during extrusion, generating uniformly distributed micro-pores without structural collapse (Lee, Oh, et al., 2022). When the SP proportion further increased to 6:4 and 5:5, the pore area in PBMA significantly enlarged, while the number of pores decreased remarkably, and the uniformity of pore distribution declined. This phenomenon may stem from excessive protein cross-linking density, which rigidified the gel network and reduced elasticity. During high-pressure extrusion, the brittle protein walls between adjacent pores fractured, causing small pores to merge into larger, irregular voids. Such structural defects may compromise the juiciness and textural authenticity of the final product.

3.2. Texture properties analysis

The textural properties of PBMA are critical determinants of sensory quality, directly influencing consumer acceptance (Bakhsh et al., 2021). As shown in Table 1, the hardness of PBMA exhibited an overall upward trend with increasing SP proportion, albeit with intermediate fluctuations. At an SM:SP ratio of 9:1, PBMA displayed the lowest hardness (6126.24 g). When the SM:SP ratio shifted from 9:1 to 7:3, hardness significantly increased (P < 0.05) to 13,668.75 g, likely due to enhanced protein cross-linking facilitated by the higher SP content. Further increasing the SP proportion to 5:5 resulted in peak hardness (22,552.68 g). These results indicated that SP could enhance hardness by strengthening protein interactions; however, excessive amounts disrupt structural balance (Giron et al., 2025). Chewiness reflected the energy required to fragment PBMA in the oral cavity, closely correlated with hardness and springiness (Giron et al., 2025). Data in Table 1 indicate that chewiness increased significantly (P < 0.05) from 4158.59 (SM:SP 9:1) to 9415.95 (SM:SP 7:3), aligning with the hardness trend. The highest chewiness (14,788.50) was observed at an SM:SP ratio of 5:5. Springiness, representing the ability to recover from deformation (critical for juiciness and palatability), peaked at 0.93 for the 7:3 ratio (P < 0.05). However, lower springiness values were recorded at 5:5 (0.87) and 6:4 (0.81), likely due to rigid structures induced by high SP proportions, which impair rebound capacity. Notably, the highest chewiness at 5:5 could be attributed to the excessive cross-linking of SM and SP, which leads to the increased rigidity of PBMA network structure and unexpected hardness. Thus, while SP enhances chewiness, a balanced interplay between springiness and hardness is pivotal for optimizing PBMA texture.

Table 1.

Textural properties of PBMA with different proportions of SM and SP.

SM:SP	Hardness/g	Chewiness	Springiness
9:1	6126.24 ± 287d	4158.59 ± 479d	0.87 ± 0.01bc
8:2	10,825.73 ± 413c	6912.38 ± 314c	0.88 ± 0.02b
7:3	13,668.75 ± 352b	9415.95 ± 375b	0.93 ± 0.02a
6:4	13,083.01 ± 421b	6957.67 ± 486c	0.81 ± 0.01c
5:5	22,552.68 ± 420a	14,788.50 ± 527a	0.87 ± 0.01bc

Note: Different lowercase letters represent significant differences (P < 0.05).

3.3. Fiber degree analysis

The fiber degree (FD) of PBMA is a key indicator reflecting its fibrous mimicry, determining the sensory quality and functional properties of PBMA products (Sun et al., 2022). According to the results shown in Fig. 2, the SM:SP ratio significantly influenced the formation of PBMA fibrous structures. As the SP proportion increased (from 9:1 to 5:5), FD exhibited a nonlinear trend, initially rising and then declining. At an SM:SP ratio of 9:1, PBMA displayed the lowest FD (0.83). This might be attributed to insufficient fat content due to the low SP proportion (10 %), where the lack of fat lubrication hindered protein molecular rearrangement, resulting in discontinuous fibrous networks (Du et al., 2023). Although SM contained a high protein content (51.3 %), excessive SM proportion led to increased intermolecular friction and disordered fiber alignment, as the absence of fat plasticization compromised structural coherence (Jang & Lee, 2024). The FD reached its peak (1.53) at an SM:SP ratio of 7:3, comparable to that of the 6:4 ratio and significantly higher than other groups (P < 0.05), indicating that this ratio achieved fibrous structures closest to real meat (Dekkers et al., 2018). The optimal FD at 30 % SP (7:3 ratio) was primarily attributed to the balanced interplay between protein cross-linking intensity and fat plasticization. Specifically, the moderate fat content (7.9 % in SP) facilitated protein alignment and lubrication, while SM-derived proteins formed a dense, continuous network. This synergy enabled the formation of layered fiber bundles resembling natural meat textures. However, further increasing the SP proportion to 5:5 caused a significant decline in FD, approaching levels similar to the 9:1 group. Fiber formation depended on ordered protein alignment. At 7:3, moderate SP fat lubricated protein rearrangement, allowing SM dense proteins to form layered bundles. Excess SP (>30 %) introduced excess fat, creating a hydrophobic barrier that inhibited protein-protein interactions (Dekkers et al., 2018). This suggested that excessive SP proportion disrupts structural integrity.

Fig. 2.

Effect of SM and SP ratio on the fiber degree of PBMA.

3.4. Color analysis

Color is a critical property of PBMA, directly influencing consumer acceptance of the product (Xia, Shen, Ma, et al., 2023). The color of PBMA is primarily associated with reactions of plant proteins during the extrusion process. The effects of different SM:SP ratios on PBMA color were shown in Table 2. In the table, L* represents lightness, where higher L* values indicated brighter samples (Wang et al., 2024). The results in Table 2 showed no significant difference in L* values of PBMA with increasing SP proportion, suggesting that higher SP ratios did not substantially affect the lightness of PBMA. The parameter a* represented the red-green chroma of the samples, where positive values indicate the sample was redder than the standard, and negative values indicated greener (Wang et al., 2024). Table 2 shows that all PBMA samples had positive a* values, meaning PBMA was redder than the standard. As the SP proportion gradually increased, the a* value of PBMA rose from 6.17 to 7.46. This may be attributed to intensified Maillard reactions between proteins and polysaccharides in the raw materials during processing, leading to enhanced browning at high temperatures and the formation of reddish-brown products (Jiang et al., 2024). The b* value represents the yellow-blue degree, where positive b* values indicate the sample is yellower than the standard, and negative values indicate bluer. Table 2 shows that as the SP proportion increased (SM:SP ratio changed from 9:1 to 5:5), the b* value of PBMA gradually increased from 23.49 to 33.36, likely due to the inherent yellow color of SP itself. Previous studies by Wang et al. (2024) found that the yellow color change of PBMA may be related to the natural color of raw materials. Table 2 also showed that the color difference ΔE followed the same trend as the a* and b* values, increasing gradually with the SP proportion. The enhanced color characteristics could be applied to foods expecting richer appearances and could improve consumer acceptance of PBMA.

Table 2.

Color change of PBMA with different proportions of SM and SP.

SM:SP	L*	a*	b*	ΔE
9:1	65.43 ± 3.15a	6.17 ± 0.23c	23.49 ± 1.01d	9.33 ± 0.21c
8:2	67.08 ± 2.31a	6.56 ± 0.14b	26.91 ± 1.12c	9.91 ± 0.33b
7:3	66.89 ± 3.08a	6.83 ± 0.29b	29.09 ± 1.54bc	10.40 ± 0.21ab
6:4	65.74 ± 2.57a	7.39 ± 0.19a	32.34 ± 2.16ab	10.61 ± 0.31a
5:5	65.45 ± 2.83a	7.46 ± 0.15a	33.36 ± 1.92a	10.72 ± 0.34a

Note: Different lowercase letters represent significant differences (P < 0.05).

3.5. Apparent density analysis

Apparent density, a key indicator of expansion degree, reflects the structural changes in materials when transitioning from a confined mold under high pressure and temperature to ambient atmospheric conditions (Brishti et al., 2021). As illustrated in Fig. 3 (A), varying ratios of SM to SP significantly influenced the apparent density of PBMA. With an increase in SP proportion from 9:1 to 5:5, the apparent density of PBMA gradually decreased from 0.61 g/cm³ to 0.34 g/cm³. At an SM:SP ratio of 7:3, the apparent density was 0.45 g/cm³. The decrease in apparent density was directly correlated with the increase in porosity (Fig. 3-C), indicating an increase in the internal pore volume of PBMA. These results were consistent with those shown in Fig. 1(B) and Fig. 1(C). Excessively low apparent density could result in the lack of meat simulation when the prepared PBMA was chewed. Moderate apparent density in PBMA was more conducive to simulating the elasticity and juiciness of animal meat.

Fig. 3.

Effect of SM and SP ratio on the apparent density (A), true density (B), and porosity (C) of PBMA.

3.6. True density analysis

True density reflects the intrinsic compactness of materials, independent of internal pores (Lee, Choi, & Han, 2022). Fig. 3 (B) displayed the effects of different SM:SP blending ratios on the true density of PBMA. Experimental data showed that as the SP proportion gradually increased from 9:1 to 5:5, the true density of PBMA progressively rose (from 0.65 g/cm³to 0.72 ± 0.02 g/cm³). This trend could be attributed to the finer particle size and higher oil content of SP, which inherently exhibited greater density compared to SM powder. Furthermore, previous studies had indicated that partial substitution of low-density plant protein ingredients with high-density counterparts during extrusion processes elevated the true density of PBMA (Lee, Choi, & Han, 2022; Lee, Oh, et al., 2022), aligning with the observed results.

3.7. Porosity analysis

As shown in Fig. 3 (C), the porosity of PBMA increased sharply from 6.15 % to 52.78 % with a rise in SP proportion (from 9:1 to 5:5). This trend could be attributed to the superior foaming capacity of SP compared to SM. Previous studies had demonstrated that proteins with higher foamability promoted the formation of water vapor nucleation sites during extrusion, thereby enhancing porosity (Hu et al., 2025). To a certain extent, higher porosity in PBMA may endow it with the ability to retain more moisture after processing, better simulating the juiciness and chewiness of real meat (Bakhsh et al., 2021). However, excessively high porosity (e.g., 52.78 % at 5:5) is not ideal for practical applications, as it complicates extrusion molding and increases the risk of internal structural fractures, ultimately compromising water holding capacity, texture, and juiciness. Notably, at the SM:SP ratio of 7:3, the porosity (34.78 %) was not the highest, but the synergistic interaction between fibers and proteins in this formulation resulted in a more uniform pore distribution, effectively preventing localized structural collapse. Additionally, the highly elastic network of PBMA at this ratio could absorb mechanical stress through deformation, mitigating the negative impacts of pores on chewing sensation.

3.8. Water absorption capacity and water holding capacity analysis

Water absorption capacity (WA) and water holding capacity (WHC) are critical indicators determining the texture, mouthfeel, and processing performance of PBMA. WA reflects the material's ability to absorb water, while WHC represents its capacity to retain water and prevent leakage (Sakai et al., 2023). As shown in Fig. 4 (A), the WA of PBMA initially increased and then stabilized with increasing SP proportions. When the SM:SP ratio shifted from 9:1 to 7:3, WA significantly rose from 3.52 g/g to 4.76 g/g (P < 0.05). Further increasing the SP ratio (7:3 to 5:5) resulted in stable WA values without significant changes. At a low SP proportion (9:1), PBMA exhibited a dense structure with extremely low porosity (6.15 %), which hindered water penetration into the interior. Increasing the SP proportion to 7:3 formed a more uniform open-pore structure (porosity: 34.78 %), enhancing capillary action and promoting water infiltration into PBMA, thus significantly improving WA. Excessive SP (5:5 ratio) likely caused excessive protein cross-linking, which hindered further water penetration.

Fig. 4.

Effect of SM and SP ratio on the water absorption capacity (A), and water holding capacity (B) of PBMA.

Compared with WA, WHC more effectively reflects PBMA ability to lock water molecules. As shown in Fig. 4 (B), WHC initially increased and then declined with rising SP proportions. When the SM:SP ratio shifted from 9:1 to 7:3, WHC increased from 2.03 g/g to 2.93 g/g. However, further increasing SP (7:3 to 5:5) reduced WHC to 2.73 g/g. Increasing the SP proportion from 9:1 to 7:3 enhanced protein interactions between SP and SM, improving the continuity and strength of the PBMA gel network. This effectively locked water through physical entrapment (pore water retention) and chemical bonding (hydrogen bonding, hydrophobic interactions). At the 7:3 ratio, PBMA formed uniformly distributed micro-pores (porosity: 34.78 %), which not only absorbed water but also inhibited water loss through capillary action, achieving the optimal water-locking state. Excess SP (>30 %) elevated hydrophobic protein cross-linking, rigidifying the gel matrix. This reduced conformational flexibility of the protein network, diminishing its capacity to entrap water via capillary forces. Concurrently, enlarged pores (52.78 % porosity at 5:5) created interconnected channels that facilitate water drainage under centrifugal stress, explaining the WHC decline (Lee, Choi, & Han, 2022).

3.9. Moisture distribution analysis

LF-NMR is a critical technique for characterizing water distribution and migration in PBMA (Wang et al., 2024). The relaxation time T₂, an indicator of water molecule mobility, reflects the time required for excited spin protons to exchange energy with adjacent protons (Xia, Shen, Song, et al., 2023). The length of the relaxation time characterizes the degree of freedom of water molecules in PBMA samples. Fig. 5 showed the effects of SM:SP blending ratios on the relaxation times of PBMA. In the Fig. 5, T₂₁ represented the relaxation time of bound water, T₂₂ represented that of immobilized water, and T₂₃ represents that of free water in PBMA (Jiang et al., 2024). As shown in Fig. 5, the three relaxation clusters of PBMA are concentrated at 0–1 ms (T₂₁), 1–30 ms (T₂₂), and 50–200 ms (T₂₃). In Table 3, P₂₁, P₂₂, and P₂₃ represent the peak area percentages of bound water (T₂₁), immobilized water (T₂₂), and free water (T₂₃) in PBMA, respectively. Data in Table 3 show that P₂₂ exhibited the highest proportion in all PBMA samples, far exceeding P₂₁ and P₂₃. This indicates that water in PBMA exists predominantly in the form of immobilized water, with most water molecules bound to proteins and located within the internal voids of PBMA (Z. Guo et al., 2020). With increasing SP proportion, the proportion of P₂₁ decreased, while those of P₂₂ and P₂₃ increased. This suggests that SP promotes the conversion of bound water to immobilized and free water. This phenomenon may be related to the interference of hydrophobic components in SP (such as fat) with the binding of water molecules to the PBMA matrix, as well as the reduction in dietary fiber caused by the decrease in SM proportion, which releases bound water originally fixed by fibers into free water. SP hydrophobic lipids compete with water for binding sites on SM proteins, disrupting hydrogen-bonded hydration layers. Additionally, reduced SM proportion decreased dietary fiber (6.0 % in SP vs. 7.6 % in SM), weakening the polysaccharide matrix's ability to immobilize water via hydrogen bonding. Overall, the SM:SP ratio significantly influences water distribution in PBMA, providing insights into the moisture behavior of PBMA at the molecular level.

Fig. 5.

Effect of SM and SP ratio on the T₂ relaxation time of PBMA.

Table 3.

Effect of SM and SP ratio on the peak area ratio of PBMA relaxation time.

SM:SP	P21(%)	P22(%)	P23(%)
9:1	6.84 ± 0.47a	90.95 ± 0.41c	2.21 ± 0.06d
8:2	5.53 ± 0.34b	91.20 ± 0.35c	3.26 ± 0.02c
7:3	4.21 ± 0.28c	91.57 ± 0.27bc	4.22 ± 0.05b
6:4	3.47 ± 0.25d	92.06 ± 0.39b	4.47 ± 0.04a
5:5	2.60 ± 0.24e	92.93 ± 0.18a	4.45 ± 0.03a

Note: Different lowercase letters represent significant differences (P < 0.05).

3.10. Protein secondary structure analysis

FTIR spectroscopy reflects intermolecular interactions and measures vibrational states of protein chemical bonds, enabling the determination of protein secondary structures (T. Tian et al., 2023; Y. Tian et al., 2022). Fig. 6 showed the FTIR spectra of PBMA samples, with secondary structure information of proteins primarily contained in the amide I band (1700–1600 cm⁻¹) of the FT-IR spectrum. The distribution ranges for α-helix, β-sheet, β-turn, and random coil in the amide I band are 1646–1664 cm⁻¹, 1615–1637 cm⁻¹, 1682–1700 cm⁻¹, 1664–1681 cm⁻¹, and 1637–1645 cm⁻¹, respectively (T. Tian et al., 2023). The secondary structure of proteins in PBMA was obtained through second derivative fitting and deconvolution of the amide I band, with the proportion of each secondary structure represented by the percentage of the specified peak area to the total area of the amide I band.

Fig. 6.

Effect of SM and SP ratio on the FTIR spectra of PBMA.

Table 4 showed the content changes in the secondary structure of PBMA under different SM:SP blending ratios. As shown in Table 4, the α-helix content of proteins initially increased and then decreased with increasing SP proportion, reaching a maximum of 30.09 % at the SM:SP ratio of 7:3. This result directly supported the observed springiness (0.93) and FD (1.53) for this ratio. The α-helix structure formed an elastic network through intermolecular hydrogen bonds, mimicking the rebound resilience of animal muscle tissue (A. Guo & Xiong, 2021). The β-sheet content continuously increased with the SP proportion (from 36.37 % to 40.45 %). The increase in β-sheet content enhanced PBMA hardness through stronger hydrophobic interactions and cross-linking density, supporting the texture results showing that PBMA hardness increased with increasing SP proportion. However, excessive β-sheets could lead to overly rigid structures, reducing elasticity and inducing brittleness. Random coils were closely related to the structural order of PBMA. Their content initially decreased and then increased with rising SP proportions, reaching a minimum of 16.07 % at the SM:SP ratio of 7:3. This indicated optimal structural order at this ratio, explaining why PBMA achieved the highest FD here. Further increased in SP proportion disrupted this order, increasing random coil content and reducing structural coherence. These findings aligned with SEM observations, where excessive SP caused fragmented PBMA structures, enlarged pores, and reduced pore density. The SM:SP ratio of 7:3 emerged as the optimal formulation, combining balanced α-helix/β-sheet ratios, minimized disordered structures, and uniform pore networks. This configuration exhibited superior comprehensive performance in texture, mechanical properties, and structural integrity.

Table 4.

Secondary structure content change of PBMA with different proportions of SM and SP.

SM:SP	α-Helix(%)	β-Sheet(%)	β-Turns(%)	Random coil(%)
9:1	25.24 ± 0.81c	36.37 ± 0.23c	19.68 ± 0.49a	18.71 ± 1.04a
8:2	27.18 ± 0.67b	36.73 ± 0.47bc	18.85 ± 0.37a	17.22 ± 0.82ab
7:3	29.09 ± 1.13a	38.74 ± 0.64b	16.30 ± 0.32b	16.07 ± 0.75b
6:4	24.83 ± 0.73c	38.03 ± 0.96b	19.34 ± 0.56a	17.80 ± 0.87a
5:5	20.52 ± 0.45d	40.45 ± 0.54a	20.03 ± 1.17a	19.01 ± 1.13a

Note: Different lowercase letters represent significant differences (P < 0.05).

3.11. Predictive modeling of PBMA quality attributes based on SM/SP mixing ratios analysis

Nine quadratic polynomial equations were established using experimental data, with the SP blending ratio (10–50 %) as the variable, to predict the quality characteristics of PBMA. The results are shown in Fig. 7 and Eqs. (9–17). All predictive equations exhibited high correlation coefficients (R² = 0.84537–0.99935), indicating a strong fit between the quadratic polynomial models and the experimental data. Notably, the R²values for the predictive equations of chewiness, apparent density, true density, porosity, and WA all exceeded 0.94, demonstrating the exceptional predictive capability of the developed models for these PBMA quality indicators. The developed predictive equations can be used to estimate the values of the quality characteristics of the meat analogues created by substituting the mixing ratio of the added SP (10–50 %) as a variable without separate experimental analyses (Lee, Choi, & Han, 2022). Furthermore, the models enable precise customization of PBMA formulations to meet diverse consumer preferences or functional requirements, such as mimicking specific meat textures or enhancing juiciness.

$$\begin{array}{c}\mathit{Hardness}\left(g\right)=8509.98602-14.04354X+4.68157X^2\end{array}$$ (9)

Fig. 7.

Quadratic polynomial correlation between SP mixing ratio and quality characteristics (A) Hardness, (B) Chewiness, (C) Springiness, (D) Fiber degree, (E) Apparent density, (F) True density, (G) Porosity, (H) Water absorption capacity, and (I) Water holding capacity of PBMA.

(R² = 0.89323)

$$\begin{array}{c}\mathit{Chewiness}=5142.856-90.245X+5.46465X^2\end{array}$$ (10)

(R² = 0.94593)

$$\begin{array}{c}\mathit{Springiness}=0.786+0.00941X-1.78571E^{-4}{X}^2\end{array}$$ (11)

(R² = 0.84537)

$$\begin{array}{c}\mathit{FD}=-0.012+0.09493X-0.00151X^2\end{array}$$ (12)

(R² = 0.8775)

$$\begin{array}{c}\mathit{Apparent\; density}\left(g/{\mathit{cm}}^3\right)=0.714-0.01076X+6.42857E^{-5}{X}^2\end{array}$$ (13)

(R² = 0.99811)

$$\begin{array}{c}\mathit{True\; density}\left(g/{\mathit{cm}}^3\right)=0.63+0.00213X-7.14286E^{-6}{X}^2\end{array}$$ (14)

(R² = 0.99217)

$$\begin{array}{c}\mathit{Porosity}\left(\%\right)=-12.512+1.96509X-0.01307X^2\end{array}$$ (15)

(R² = 0.99935)

$$\begin{array}{c}\mathit{WAC}\left(g/g\right)=2.564+0.10837X-0.00124X^2\end{array}$$ (16)

(R² = 0.98508)

$$\begin{array}{c}\mathit{WHC}\left(g/g\right)=1.262+0.08026X-0.00101X^2\end{array}$$ (17)

(R² = 0.87737)where X: SP mixing ratio (10–50 %); FD: fiber degree; WA: water absorption capacity; WHC: water holding capacity.

4. Conclusions

This work validated SM and SP as cost-effective protein sources for high-quality PBMA production and further demonstrates that fine-tuning the SM:SP ratio served as a critical lever to optimize PBMA quality attributes. The study conclusively identified a 7:3 SM:SP ratio as optimal for producing PBMA with meat-like texture, fibrous structure, and functional properties. This ratio balanced protein interactions, fat plasticization, and porosity, achieving superior hardness, springiness, and WHC. Excessive SP (>30 %) compromised structural coherence, highlighting the necessity of balanced formulations. Predictive models further enabled efficient customization of PBMA attributes, supporting industrial scalability. By utilizing low-cost SM and SP, the production cost could be reduced by more than 30 %, and the market competitiveness of PBMA could be greatly improved. Future research should explore synergies with other plant proteins and optimize extrusion parameters for diverse consumer preferences, advancing the sustainability and acceptance of plant-based meat alternatives.

CRediT authorship contribution statement

Zhongjiang Wang: Writing – original draft, Software, Project administration, Methodology, Investigation, Funding acquisition, Data curation, Conceptualization. Yachao Tian: Writing – original draft, Software, Resources, Methodology, Investigation, Data curation, Conceptualization. Chunfang Ma: Supervision, Software, Resources. Chaojiang Dong: Visualization, Project administration, Methodology, Formal analysis. Yunfeng Zeng: Software, Resources, Methodology, Investigation. Shuo Zhang: Visualization, Validation, Conceptualization. Qingfeng Ban: Project administration, Methodology. Zengwang Guo: Supervision, Resources, Project administration, Investigation, Funding acquisition. Hongbo Sun: Visualization, Supervision, Project administration, Methodology, Investigation.

Funding

This work was supported by the Major Project of Agricultural Science and Technology, Key Research and Development Program of Shandong Province (2024CXPT023), Youth Top Talent Program of the National Food and Strategic Reserves (QN2024510), and Northeast Agricultural University 2023 Young Leading Talent Support Program (NEAU2023QNLJ-007).

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

No data was used for the research described in the article.