Physicochemical and compositional properties of blended beef patties formulated with pea and faba bean protein isolates and texturized pea protein

Abstract

This study investigated the physicochemical characteristics of blended beef patties formulated with pea and faba bean protein isolates (PPI and FPI, respectively) and hydrated texturized pea protein (HTPP, 1 part TPP: 2 parts water). Minced beef was combined with nothing (control) or 4.25% PPI/FPI and 0%, 8.5%, 21.3%, or 42.5% HTPP. The pH, Warner‐Bratzler shear force (WBSF), texture profile analysis (TPA), compression juiciness, cooking loss, color, and chemical composition were determined. In general, plant proteins increased pH values and ash content, and decreased cooking loss and fat content of blended meat patties. The addition of PPI/FPI did not lead to substantial changes in texture or color but resulted in lower cooking loss. HTPP resulted in decreased WBSF, hardness, and other TPA attributes. The combination of PPI/FPI as binders/gelling agents and HTPP as a meat extender resulted in a softer texture than conventional beef patties. This study provides an indication of PPI, FPI, and HTPP functionality in blended meat product formulation.

INTRODUCTION

Blended meat is created by partial replacement of meat ingredients with plant-based material. Blended meat products fill the gap between conventional meat and plant-based products, and could be a pathway to help steadfast meat-eaters reduce their meat intake (Schösler et al., 2012). Blended meat products are targeted toward flexitarian consumers who are likely interested in using blended meat products instead of 100% meat-based products. Blended meat products, such as burgers and nuggets, provide a convenient alternative allowing consumers to swap directly with conventional 100% meat products (Neville et al., 2017). Meat is a valuable food that provides protein, iron, and B group vitamins in the human diet, but meat consumption has also been associated with obesity, heart disease, and specific cancers due to the high saturated fat and cholesterol content (Abete et al., 2014; Tucker, 2004). Plant-based protein is an ideal ingredient in blended meat products as it contains a similar protein level and low fat (Neacsu et al., 2017). There are however challenges when formulating blended meat products, as plant-based ingredients do not have the same functional properties as meat. For example, protein structures differ markedly between meat and plant protein; meat consists of fibrous and globular proteins such as myosin, actin, and myoglobin while plant protein consists of only globular proteins such as globin and albumin (Xiong, 2017; Yang & Sagis, 2021). Due to the differences between plant- and meat-based protein structures, product texture and appearance attributes are intrinsically different and present a challenge to the blended product developer (Sha & Xiong, 2020). Meat naturally has a firm texture due to its structural attributes and in minced meat products, the intrinsic proteins such as myosin act as binders, allowing products such as burgers to retain their shape (Weiss et al., 2010). When formulating blended meat products, both a binder ingredient or gelling agent (usually a plant protein isolate) and an ingredient that will enhance texture, such as hydrated texturized protein, are required (Asgar et al., 2010; Baune et al., 2022).

Plant-based proteins such as texturized protein and protein isolate are added as extenders and binders, respectively, to improve the texture and nutrition of blended meat products. Texturized plant protein is a commonly used meat extender in blended meat products (Vatansever et al., 2020). After rehydration, texturized plant protein has a texture with some similarity to meat with a fibrous-like structure due to the extrusion process used in its production. Texturized soy protein has been the most prevalent texturized plant protein ingredient used by the food industry. Recently, texturized pea protein (TPP) was developed as an alternative ingredient due to its advantages as non-GMO and hypo-allergenic with the potential as a fibrous meat analogue (Maningat et al., 2022). Previous studies have found that texturized soy protein added at >15% reduces the structural integrity of blended burgers compared with conventional meat patties, primarily due to the lack of binding between meat and plant proteins (Bakhsh et al., 2021). Thus, when formulating blended meat products with texturized protein, an ingredient needs to be added as a binder (usually a plant protein isolate) to try to achieve similar structural integrity and firmness as conventional meat products. Pea and faba bean protein isolates have been recognized as effective binders due to their high water-holding, emulsifying, and gelling properties (Cai et al., 2002; Karaca et al., 2011; Lam et al., 2018; Shanthakumar et al., 2022). These newly developed plant protein isolates also have the benefit of low allergenicity and good nutritional value (Boukid et al., 2021; Multari et al., 2015).

For meat products, texture, nutrient content, and visual appearance are all attributes that heavily affect consumer liking and purchase intention and this also holds true for blended meat products which target the meat-loving consumer (Font-I-Furnols & Guerrero, 2014). Tenderness and juiciness are two of the most significant eating quality attributes among all texture parameters, which influence consumers' purchase intentions (Acebron & Dopico, 2000; Lee et al., 2018). Furthermore, consumers have also shown positive attitudes toward meat products with healthy attributes, such as lower fat content or sodium reduction (Guàrdia et al., 2006). However, they are unwilling to compromise sensory traits to achieve health benefits from food products (Ares & Varela, 2017; Tuorila & Cardello, 2002). Adding plant-based material may change the texture characteristics, nutritional values and color of blended meat products depending on the functionality of the added materials (Shoaib et al., 2018; Zhao et al., 2020). However, there are few studies investigating the quality changes of blended meat products formulated with emerging pea and faba bean-derived plant protein ingredients. This study investigated the physicochemical properties and composition of a range of meat and hydrated texturized pea protein patty formulations incorporating pea or faba bean protein isolate and compared them with a conventional beef patty as a control.

MATERIALS AND METHODS

Treatments and cooking procedure

Pea protein isolate (catalogue number PPI 85C), faba bean protein isolate (catalogue number FPI 90C), and texturized pea protein (TPP 67C) were purchased from Agri-Food Ingredients (N. G. Alexander & Co Pty Ltd, Melbourne, Australia). The TPP granule size was not homogenous, hence using the method of Cardello et al. (1983), with modifications; the TPP granules were sorted into large (>4 mm), medium (2.5–4 mm), and small (<2.5 mm) granules by sifting through two sieves (2.5 and 4 mm). The TPP ingredient was then prepared as a mixture of 45% large granules, 45% medium granules, and 10% small granules, all by weight. This method ensures consistency of particle size profiles across formulations and batches. The TPP was then rehydrated by mixing with water (90°C) for 5 min at a 1:2 ratio (TPP: water, by weight), and then cooled to room temperature (23 ± 1°C); the hydrated TPP is subsequently referred to as HTPP in this manuscript. The pH values were measured using a pH electrode (HI1131B) and a pH meter (Hanna Instruments, HI5221, Melbourne, Australia) and pH was determined in a slurry of 1 g of protein ingredient added to 9 mL of water. The pH values for PPI, FPI, and HTPP were 6.53, 6.22, and 7.10 respectively. The salt was purchased in a local market.

Fresh beef chuck (not frozen) was purchased, transported to the meat laboratory in chilled conditions, and then trimmed to remove visual fat and connective tissue. Four batches of samples were made over four separate days, and nine treatments were prepared for each batch. Formulations are shown in Table 1. All treatments contained the same amount of water (excluding the water used for hydrating TPP) and salt. The beef was coarsely ground in a mincer with a 4 mm diameter plate. A bench mixer (Target TARBM18 Bench Mixer – P60393906, China) was used to mix ground beef and other ingredients. The beef mince was mixed with salt and water, PPI or FPI, and HTPP in sequential order, for 1 min each. The batter was refrigerated at 4°C for 30 min. After refrigeration, the meat patties were formed into 150 g patties using a 10 cm patty maker (FED Patty Press Moulds 602201, APEX Co Pty Ltd, Melbourne, Australia). The meat patties were then vacuum-packed and stored at −20°C until further evaluation.

TABLE 1 Amount (%) of each ingredient for the nine treatments for the beef patties containing differing levels of beef, pea protein isolate (PPI), faba bean protein isolate (FPI), and hydrated texturized pea protein (HTPP), and a constant amount of salt and water.

Ingredients (%)	Control	4.25PPI	4.25PPI-8.5HTPPa	4.25PPI-21.3 HTPPa	4.25PPI-42.5HTPPa	4.25FPI	4.25FPI-8.5HTPPa	4.5FPI-21.3HTPPa	4.5FPI-42.5HTPPa
Beef	85	80.75	72.25	59.5	38.25	80.75	72.25	59.5	38.25
Pea protein isolate (PPI)	0	4.25	4.25	4.25	4.25	0	0	0	0
Faba bean protein isolate (FPI)	0	0	0	0	0	4.25	4.25	4.25	4.25
Hydrated texturized pea protein (HTPP)	0	0	8.5	21.25	42.5	0	8.5	21.25	42.5
Water	14.5	14.5	14.5	14.5	14.5	14.5	14.5	14.5	14.5
Salt	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5	0.5

Raw beef patties were thawed at 4°C overnight before cooking. Samples were cooked in a commercial oven (Convotherm, C4BD10.10C, Germany) at 180°C to reach an internal temperature of 75°C. A thermometer (William Klein, XT300, Melbourne, Australia) was used to determine the internal temperature of the patty. After cooking, the samples were covered loosely and cooled to room temperature (23 ± 1°C) prior to the following analyses below.

Physicochemical analyses

pH measurement

The determination of pH values for raw and cooked patties followed the method of Mena et al. (2020) with some modifications as described. The pH of the raw patties was measured with a dual pH and temperature meter (Ionode IJ44 electrode, WP-80 Waterproof pH-mV-Temperature Meter, TPS, Brendale, Australia) before cooking by inserting the pH probe directly into the patty. Cooked patty samples (10 g) were homogenized with 40 mL distilled water using an Ultra Turrax T25 homogenizer (Staufen, Germany) at 10,000 rpm for 1 min. The pH values were determined by testing the suspension using a pH electrode (HI1131B) and a pH meter (Hanna Instruments, HI5221, Melbourne, Australia). Three patties for each formulation within each batch were used for pH determination.

Proximate analysis

Proximate analysis (moisture, fat, ash, and protein) was conducted on raw and cooked patties. Three patties from each treatment per batch were selected randomly to test their chemical composition. Moisture content was measured by placing 10 g of raw or cooked sample in a hot air oven (Qualtex Solid State Laboratory oven model QM24S, Watson Victor Ltd, QLD, Australia) at 100°C for about 48 h until the weight became constant (AOAC 950.46, 2005). Crude fat was measured by following the AOAC 960.39 method that uses semi-continuous Soxhlet Extraction with diethyl ether as the solvent. A direct method (AOAC 923.03, 2005) was used to determine the ash content. Samples were carbonized by burning using a Bunsen burner. They were then placed at 550°C in a muffle furnace, and the results were recorded when the weight was constant. Determination of crude protein followed the Leco Dumas method described in AOAC 992.15 (2005) and 6.25 was used as the nitrogen conversion factors according to Food Standards Australia and New Zealand (FSANZ) (2022).

Compression juiciness

Compression juiciness was measured by the press method, which was modified from Gujral et al. (2002). A sample was taken from the center of the cooked patty, cut into a cylinder of 35 mm diameter and 100 mm height, and then weighed. The cylindrical piece was placed between a pair of pre-weighed Whatman filter paper (No. 40), covered with aluminum foil, and pressed between two 116 mm diameter round plates (Round Compression Plates, 01/4006, 116 mm diameter, Berwyn, PA, USA) attached to a Lloyd texture analyser with a load cell of 500 N (AMETEK®, LS5, Largo, FL, USA) to 50% compression with 200 mm/min speed. The weight of the filter paper after pressing was recorded. The same machine was used for the TPA measurement (see below). Compression juiciness (CJ) was calculated as the following equation: $\text{Compression juiciness}\left(\%\right)=\begin{array}{l}\frac{\text{Weight of juice absorbed}\mathrm{by}\text{filter paper}\left(\mathrm{g}\right)}{\text{Weight of patty sample}\left(\mathrm{g}\right)}\\ \times 100\end{array}$

Cooking loss

Patty samples were weighed before cooking. Cooked meat patties were cooled at room temperature (23 ± 1°C) and wiped gently to remove visible exudates using a paper towel. The weight of three samples was measured for each treatment within each batch. The ratio of cooked weight was expressed as a percentage according to the following equation: $\text{Cooking loss}\left(\%\right)=\left(1-\frac{\text{Cooked weight}}{\mathrm{Raw}\text{weight}}\right)\times 100$

Warner-Bratzler shear force (WBSF)

For each treatment within each batch, the three patties cooked for cooking loss as described above were sampled for WBSF. There were five strips (5.0 cm × 1.0 cm × 1.0 cm) cut from each patty. Each strip was sheared three times in different locations with a V-Notch blade with a 60° angle based on modifications of the methods of Berry and Leddy (1989) and Possidónio et al. (2021). The blade was attached to the crosshead of Lloyd texture analyser (Lloyd Materials Testing, AMETEK®, LS5, Berwyn, PA, USA) with a 500 N load cell and crosshead speed of 250 mm/min. Shear force was expressed in Newtons (N), and the results were obtained from the Nexygen software (Version 3; Bestech, Dingley, VIC, Australia). The average of the 15 measurements within each formula and batch was used as the value of WBSF.

Texture profile analysis (TPA)

Each patty was cut into three cylinders (35 mm diameter, 100 mm height) and then subjected to a two-fold compression test using a Loyd texture analyser (Lloyd Materials Testing, AMETEK®, LS5, Berwyn, PA, USA). The samples were placed on the fixed plate center with a 20 mm diameter steel cylinder probe (AMETEK®, PBT/0047/00, Berwyn, PA, USA) that performed about 50% compression of the sample's original height. A load cell of 500 N at a 200 mm/min speed with a 1-s delay descent was used (Bourne, 2002). The parameters hardness, springiness, cohesiveness, chewiness, and gumminess were obtained and quantified using Nexygen v.3.3.2013. The above parameters obtained were the mean value of three patties from each treatment for every batch.

Color determination

The color of raw and cooked patties was evaluated by measuring L*, a*, and b* with a Minolta Chroma Meter CR-400 (Minolta Pty Ltd., Tokyo Japan, pulsed xenon lamp, illuminant D65, observer angle 2°, 8 mm aperture diameter). Three fresh samples were analyzed for each treatment from each of the four batches. After cooking, the samples were exposed to room temperature (23 ± 1°C) with loose aluminum foil covering the sample. Then, three different locations on the surface of a sample were measured, and the average of the measurements was used. Chroma values were calculated as $\sqrt{a^{*2}+b^{*2}}$ and hue was calculated as tan⁻¹ (b*/a*).

Statistical analysis

Statistical analyses were conducted using GenStat (19th edition, 64-bit edition, VSN International Ltd, Hemel Hempstead, UK). The data were analyzed using Restricted Maximum Likelihood (REML). The physicochemical data WBSF, TPA, and juiciness were analyzed in REML using “Formula” as the fixed effect and batch number and sample number as random effects in REML. Subsequently, all data for blended samples, except for proximate data, were evaluated using the main effects of plant protein isolate (PPI and FPI), HTPP level, and interactions as fixed effects in the model. Batch number, formula number, and sample number were included in the random model. The same procedure was conducted with proximate data, but the random model included batch number and treatment number only. In addition, the effect of HTPP level was applied in the model as a variate, instead of as a factor, to determine linear effects, and the standard error of the slope was determined. The least significant difference (LSD) test at the 5% level of probability was used to separate mean values. A PCA graph including pH, WBSF, texture profile including hardness, cohesiveness, springiness, chewiness and gumminess, and compression juiciness was generated using R (4.3.0) and RStudio (2023.03.1, Build 446).

RESULTS

pH and proximate analysis

In Table 2, blended patties had a higher pH than beef patties and PPI resulted in higher pH values in blended raw (p < 0.01) samples than FPI. Increasing the HTPP content also resulted in greater pH values; pH values increased, for instance from 5.9 to 6.26 for 4.25% PPI with an enhancement in HTPP content from 0 to approximately 42.5% in raw patties. Based on the coefficients, the pH value of treatments increased by 0.09 when an additional 10% HTPP extender was mixed in the raw batter. For cooked samples, PPI/FPI and the level of HTPP content significantly impacted the pH of cooked samples (p < 0.001). PPI led to higher pH than FPI in cooked blended samples (p < 0.001). The coefficient shows that with a 10% HTPP content increase in the formula, there was a 0.075 increase in the pH values of cooked blended patties compared to the cooked control patties.

TABLE 2 Effect of formula (F; control and 8 blended patty formulations), plant protein (PP; PPI, pea protein isolate; FPI, faba bean protein isolate), hydrated texturized pea protein level (HTPP; 0%, 8.5%, 21.3%, 42.5%) on proximate analysis and pH of raw and cooked patties.

	Control		HTPP level	LSD	Significancec	Linear coefficient for HTPP levelc,d (SE)
Type of PP	0	8.5	21.3	42.5
Raw
pH	5.82	4.25PPI	5.90	5.97	6.10	6.26	0.034a	F***, PP**, HTPP***	0.0089*** (0.00025)
4.25FPI	5.86	5.93	6.08	6.25	0.031b
Moisture (%)	77.3	4.25PPI	74.7	74.0	73.0	71.7	0.55a	F***, HTPP***	−0.0702*** (0.00392)
4.25FPI	74.6	73.9	72.9	71.7	0.56b
Ash (%)	1.23	4.25PPI	1.36	1.42	1.36	1.41	0.106a	F**, PP*	0.00024 (0.000745)
4.25FPI	1.34	1.31	1.33	1.35	0.108b
Fat (%)	2.57	4.25PPI	2.07	2.27	1.95	1.67	0.303a	F*, HTPP***	−0.015*** (0.0022)
4.25FPI	2.26	2.16	2.00	1.45	0.312b
Protein (%)	20.6	4.25PPI	23.1	23.1	22.9	22.7	0.41a	F***, HTPP*	−0.014** (0.0048)
4.25FPI	23.2	23.4	23.2	22.7	0.46b
Cooked
pH	5.96	4.25PPI	6.05	6.14	6.23	6.38	0.036a	F***, PP***, HTPP***	0.0075*** (0.00024)
4.25FPI	6.01	6.08	6.20	6.33	0.030b
Moisture (%)	69.0	4.25PPI	67.9	68.4	68.5	68.1	0.76a		−0.0043 (0.00550)
4.25FPI	68.2	68.5	67.9	68.0	0.73b
Ash (%)	1.17	4.25PPI	1.35	1.34	1.40	1.42	0.091a	F***, HTPP*	0.0021** (0.00077)
4.25FPI	1.31	1.31	1.36	1.38	0.097b
Fat (%)	3.34	4.25PPI	3.06	2.42	2.00	1.62	0.477a	F***, HTPP***	−0.028*** (0.0036)
4.25FPI	2.66	2.43	2.08	1.84	0.505b
Protein (%)	27.8	4.25PPI	27.6	26.5	26.8	26.9	1.63a	F**	−0.023 (0.0238)
4.25FPI	28.9	27.7	28.0	27.6	2.26b

Table 2 shows the nutritional composition of the control and eight plant protein treatments, including two types of protein isolates, PPI and FPI, and four levels of HTPP content. All raw blended patties had a lower moisture content (p < 0.001) and greater ash content (p < 0.05) than control meat patties. For fat content, PPI/FPI and HTPP led to decreased fat content compared to controls (p < 0.05). Adding 4.25% PPI/FPI resulted in increased protein content, but HTPP addition resulted in a trend in protein content reduction (p < 0.05). Linear associations were found between HTPP level and moisture (p < 0.001), fat (p < 0.001) and protein (p < 0.01) content in blended patties. Substitution of 10% of meat with the same amount of HTPP reduced moisture, fat, and protein by 0.70%, 0.15%, and 0.14% respectively. In cooked patties, blended patties with PPI/FPI had similar moisture and protein content and greater ash content compared with controls. Adding HTPP increased ash content (p < 0.05) and reduced fat content (p < 0.001) of blended patties. Based on the linear coefficient results, there was 0.02% increase in ash content and 0.28% reduction in fat for each 10% replacement of HTPP in the formula.

Texture parameters

Table 3 shows the Warner-Bratzler shear force (WBSF) values that indicate the firmness of meat products, and texture profile analysis (TPA). Both PPI and FPI did not change the hardness, springiness, cohesiveness, chewiness, and gumminess of the patties but led to decreased WBSF. HTPP played a prominent role in texture parameters. HTPP substitution influenced (p < 0.001) WBSF and TPA results in which all parameters decreased (except cohesiveness) as HTPP quantity increased. Blended samples with 8.5% HTPP and 4.25% PPI/FPI had similar TPA results to controls (p > 0.05) but reduced WBSF. When HTPP addition reached 21.5% and 42.5%, patties had decreased TPA values, which means the blended patties become softer than controls. The coefficients show that in blended samples, every 10% increase in HTPP lead to a decrease in WBSF (1.7 N), hardness (5.1 N), springiness (0.022), cohesiveness (0.102%), gumminess (3.7 N) and chewiness (3.5 N).

TABLE 3 Effect of formula (F; control and 8 blended patty formulations), plant protein (4.25% PP; PPI, pea protein isolate; FPI, faba bean protein isolate), hydrated texturized pea protein level (HTPP; 0%, 8.5%, 21.3%, 42.5%) on cooking loss, Warner-Bratzler shear force (WBSF), texture profile analysis (TPA) and compression juiciness of cooked patties.

	Control	Type of PP	HTPP level	LSD	Significancec	Coefficient for HTPP levelc,d (SE)
0	8.5	21.3	42.5
WBSF (N)	16.5	4.25PPI	14.3	12.4	9.5	6.5	1.12a	F***, HTPP***	−0.173*** (0.0087)
4.25FPI	14.1	12.4	9.8	7.3	1.10b
Hardness (N)	61.2	4.25PPI	65.6	61.2	55.4	43.9	7.63a	F***, HTPP***	−0.507*** (0.0460)
4.25FPI	66.8	64.3	57.4	46.6	6.78b
Springiness	0.23	4.25PPI	0.24	0.23	0.20	0.16	0.024a	F***, HTPP***	−0.00219*** (0.000161)
4.25FPI	0.26	0.23	0.20	0.16	0.024b
Cohesiveness (%)	1.89	4.25PPI	1.89	1.95	2.04	2.29	0.094a	F***, HTPP***	0.0102*** (0.00069)
4.25FPI	1.84	1.92	2.03	2.30	0.096b
Gumminess (N)	32.3	4.25PPI	35.4	31.6	27.4	19.4	4.68a	F***, HTPP***	−0.373*** (0.0295)
4.25FPI	36.6	33.6	28.4	20.7	4.39b
Chewiness (N)	26.8	4.25PPI	30.3	26.9	22.9	15.5	4.65a	F***, HTPP***	−0.346*** (0.0295)
4.25FPI	31.6	28.5	23.7	16.8	4.39b
Cooking loss (%)	32.2	4.25PPI	23.0	20.9	17.9	11.6	2.41a	F***, HTPP***	−0.237*** (0.0189)
4.25FPI	22.6	20.8	16.7	14.1	2.46b
Compression juiciness (%)	8.04	4.25PPI	7.18	6.13	5.39	3.62	0.389a	F***, HTPP***	−0.084*** (0.0036)
4.25FPI	7.63	6.27	5.11	3.61	0.388b

Cooking loss and compression juiciness

Table 3 shows the results of cooking loss and compression juiciness for the control and eight blended meat patties. Blended patties had lower cooking loss than control (p < 0.001) and no difference was found between blended patties with PPI and FPI (p > 0.05). Furthermore, as HTPP content increased, the cooking loss was reduced (p < 0.001). Each 10% addition of HTPP replacement reduced the cooking loss by ~2.4%. The instrumental juiciness measurement was used to simulate the release of moisture during the chewing process. The control sample had higher compression juiciness than all blended patties (8% vs. 7.6%–3.6% respectively) (p < 0.001) indicating that combining plant protein resulted in reduced juiciness. Addition of both 4.25% PPI and FPI resulted in a decrease in juiciness. HTPP content also affected the juiciness, as an increase in HTPP percentage resulted in a decrease in juiciness and 10% HTPP replacement resulted in about 0.84% less juiciness.

PCA

The PCA graph shown in Figure 1 explained 94% of the variation in Dimension 1 and 5.4% in Dimension 2. The pH levels of both raw and cooked samples had a negative relationship with cooking loss, WBSF, and compression juiciness. The formulations with 4.25% PPI/FPI and 0%–8.5% HTPP (4.25PPI, 4.25FPI, 4.25PPI-8.5HTPP, and 4.25FPI-8.5HTPP) had similar texture profile, including hardness, chewiness, gumminess, and springiness. However, blended patties with a high level (42.5%) of HTPP had a negative relationship to these texture attributes due to the location in opposing quadrants. Overall, the instrumentally measured texture of the blended patties was quite different from the controls as they were distributed in different quadrants.

[IMAGE OMITTED. SEE PDF]

Visual appearance and color properties

Figure 2 and Table 4 show the images and color parameters of control (beef only) and blended beef patties with various formulae in both raw and cooked conditions. Significant variations in colorimetrics of L* (lightness), a* (redness), b* (yellowness), chroma, and hue values were found between control and blended patties in raw patties. FPI had greater effect than PPI in a* (p < 0.001), chroma (p < 0.05), and hue (p < 0.01). PPI led to reduced redness (p < 0.05) only and FPI caused less redness and chroma, and increased hue compared with controls. As the proportion of HTPP was increased, the patties became lighter (p < 0.001), less red (p < 0.001), and more yellow (p < 0.001). HTPP addition also resulted in a drop in chroma (p < 0.001) and an increase in hue values (p < 0.001), implying reduced saturation and more vividness. HTPP addition affected the color of raw patties where the coefficients show that for every 10% additional HTPP in raw samples, values would increase by 2.4, 0.90, and 0.08 in the lightness, yellowness, and hue values respectively. HTPP addition also resulted in a decrease of 2.3 and 0.81 in redness and chroma respectively. For cooked blended patties, both PPI and FPI resulted in increased hue values in which FPI patties had greater hue values than PPI patties (p < 0.05). FPI caused greater lightness and less redness than control patties. After adding HTPP, there was a substantial decrease in redness and increased hue values in cooked patties (p < 0.001) and a considerable increase in b*, chroma, and hue values. In cooked patties, each 10% increase in HTPP induced about 1.22, 1.07, and 0.024 increases in yellowness, chroma and hue values respectively.

[IMAGE OMITTED. SEE PDF]

TABLE 4 Effect of formula (F; control and 8 blended patty formulations), plant protein (4.25% PP; PPI, pea protein isolate; FPI, faba bean protein isolate), hydrated texturized pea protein level (HTPP; 0%, 8.5%, 21.3%, 42.5%) on the pH and color parameters of raw and cooked patties.

	Control	Type of PP	HTPP level	LSD	Significancec	Coefficient for HTPP levelc,d (SE)
0	8.5	21.3	42.5
Raw
L*	43.4	4.25PPI	44.1	44.8	47.9	55.1	1.91a	F***, HTPP***	0.245*** (0.0153)
4.25FPI	44.5	47.2	48.5	54.3	1.24b
a*	26.2	4.25PPI	24.2	21.9	20.2	13.6	1.51a	F***, PP***, HTPP***	−0.228*** (0.0107)
4.25FPI	22.6	20.4	18.4	13.4	1.30b
b*	18.9	4.25PPI	18.7	18.5	19.6	22.7	1.23a	F***, HTPP***	0.0998*** (0.00924)
4.25FPI	18.5	19.0	19.8	21.9	1.16b
Chroma	32.3	4.25PPI	30.6	28.7	28.3	26.6	1.93a	F***, PP*, HTPP***	−0.0813*** (0.01117)
4.25FPI	29.3	28.0	27.1	25.8	1.60b
Hue	0.63	4.25PPI	0.66	0.70	0.77	1.03	0.040a	F***, PP**, HTPP***	0.00828*** (0.000424)
4.25FPI	0.69	0.75	0.82	1.02	0.042b
Cooked
L*	47.7	4.25PPI	47.9	48.5	50.7	50.0	2.67a	F***	0.0307 (0.01727)
4.25FPI	51.0	49.8	49.7	51.1	2.45b
a*	8.00	4.25PPI	7.38	7.30	7.00	7.07	0.871a	F***	−0.00931 (0.005974)
4.25FPI	6.68	6.99	6.72	6.43	0.826b
b*	15.3	4.25PPI	16.1	17.0	18.4	20.6	0.91a	F***, HTPP***	0.122*** (0.0067)
4.25FPI	15.6	17.2	18.6	21.5	0.88b
Chroma	17.3	4.25PPI	17.8	18.6	19.7	21.6	1.14a	F***, HTPP***	0.107*** (0.0079)
4.25FPI	17.3	18.6	19.8	22.5	1.09b
Hue	1.09	4.25PPI	1.14	1.16	1.20	1.23	0.045a	F***, PP*, HTPP***	0.00248*** (0.0003)
4.25FPI	1.17	1.18	1.22	1.28	0.046b

DISCUSSION

The most important results from the study were that increasing HTPP levels increased patty softness as indicated by a decrease in WBSF, hardness, springiness, gumminess, and chewiness. This finding agrees with previous studies which have shown that adding texturized soy protein to beef or goat meatballs reduced the hardness and chewiness of blended meat products (Grasso et al., 2019; Gujral et al., 2002). In addition, the positive relationship in the PCA graph between cooking loss and WBSF of patties confirmed that the plant proteins in the matrix contributed to the soft texture of blended patties, likely due to more water being held in the matrix and disruption of the fibrous nature of meat proteins (Hong et al., 2022). As ingredients by themselves, PPI and FPI had a small effect on WBSF and had similar binding functionality, which is discussed further below in terms of water-holding capacity. The intrinsic differences between muscle and plant materials, such as protein structure and chemical composition, mean that plant-based material alone will not generate a similar matrix structure to animal meat products, thus other ingredients are needed in the formulation to achieve meat-like texture (Sha & Xiong, 2020). Even when plant-based materials/analogues are subjected to shear and extrusion, the three-dimensional structure formed is dissimilar to the fibrous anisotropic structure of a muscle fiber. To decrease the crumbliness of blended meat products, the use of other binding agents such as transglutaminase or egg white, which are both known to bind meat and plant protein, may be required, (Egbert & Borders, 2006). In terms of consumer acceptance, a range of consumers have been shown to prefer soft patties to medium or hard patties (Mena et al., 2022). Petrat-Melin and Dam (2023) used consumer sensory evaluation to demonstrate the softer texture of blended burgers compared with beef burgers and also showed that ~30% of consumers chose “Soft” as an attribute of the ideal burger. Hence, future studies could investigate the optimal texture profile for beef burgers from consumer feedback and relate it to instrumental measurement.

The strong water-binding functionality of PPI and FPI is most apparent in the cooking loss results where cooking loss is reduced by nearly a third when the protein isolates are added. HTPP does not exhibit the same binding capacity as the protein isolates. The reduction of cooking loss due to adding plant protein isolate is in agreement with previous studies (Baugreet et al., 2016; Keivaninahr et al., 2021; Kilic et al., 2010; Shoaib et al., 2018). The observed reduction in cooking loss with increasing plant protein content is associated with the increase in the pH of patties (see PCA graph) due to the addition of the plant proteins PPI, FPI, and HTPP. This effect is not unexpected given the pH of the raw control patties was 5.8, the pH of the plant protein ingredients was 6.2–7.1 and the blended patties pH was between 6.0 and 6.2. It is widely acknowledged in meat science and plant-based protein literature that the gelation properties and water-holding capacity of meat proteins, particularly myofibrillar protein, are influenced by the pH levels (Warner, 2023). We hypothesize that the reduced cooking loss (increased water holding capacity) is due to (i) the water fraction held by the plant protein ingredients remaining in the structure during cooking and (ii) the added water also remaining in the meat protein fraction due to the well-known increased gelling property and water-holding capacity of myofibrillar meat proteins at higher pH, further away from the isoelectric point of meat proteins at pH 5.0–5.2 (Sun & Holley, 2011; Warner, 2023) and (iii) plant protein, especially protein isolates have increased gel formation and water holding capacity at pH values closer to 7 (Ge et al., 2023). Compression juiciness was lower with the addition of plant proteins with increased pH values as previously reported by Gujral et al. (2002) and Shen et al. (2022) and again we hypothesize that the water is more tightly held in the structure by plant proteins with the higher pH values (Ge et al., 2023). This explains why the reduced cooking loss, when more water is retained in the structure post-cooking, does not result in higher compression juiciness in the cooked product. Thus, PPI, FPI, and HTPP are potential ingredients to improve the cooking loss but we also observed reduced compression juiciness. In contrast, Petrat-Melin and Dam (2023) reported increased consumer scores for juiciness for blended burgers with 4% texturized pea and faba bean proteins, relative to beef burgers, likely due to lower cooking loss. In their study, the greater juiciness with the addition of extruded pea starch was attributed to the high water-holding capacity of the plant protein and the reduced content of collagen in the blended burgers. It should be noted that although instrumental juiciness has a relationship with trained sensory panel evaluations of the juiciness of meat products, it does not explain all the variation in juiciness scores obtained during sensory evaluation. Future studies are recommended to evaluate the consumer's responses to the juiciness of the products with plant protein addition, compared with instrumental results.

Given blended meat products aim to replace meat products in consumer diets it is important to establish their nutritive value compared to meat-only products. We found that after cooking, the protein content overall is similar for meat (control) and blended patties ranging from 26.50% to 28.86% (Table 2). However, it should be noted the protein content reported in this study aligns with the FSANZ (Food Standards Australia and New Zealand) guidelines for composite food nutritional labels, with a total N to protein conversion factor of 6.25 used for all calculations. According to the Food and Agriculture Organization of the United Nations (FAO) (2003), the protein conversion factor for legumes such as soy and mung bean are 5.7 and 6.25 respectively. Mariotti et al. (2008) recommended using updated data for conversion where the conversion factor for PPI is about 5.4, although not available for FPI. The conversion factor we used (6.25) was selected due to the specified blending of meat and plant proteins. Therefore, it is worth noting that as the conversion factor for PPI, and maybe for FPI are lower than 6.25 we may be overestimating the protein contribution for the plant-based ingredients.

Apart from the changes in protein quantity, the type of plant protein used may also differ in quality, particularly in the essential amino acids (Marinangeli et al., 2021; Nosworthy et al., 2017). Gorissen et al. (2018) compared the amino acid profile of animal-based proteins such as egg, milk and muscle, and plant proteins such as soy, lupin, and pea and reported that the plant-based proteins had lower essential amino acids such as lysine and methionine. Plant-based protein products generally have lower digestibility than meat in vitro (Yang et al., 2023). Therefore, blended meat products require further attention regarding nutritional profile and digestibility.

In addition, as the plant protein contents increased to ~47% in blended meat patties, there was a ~50% decrease in fat content and this will have health benefits for consumers in terms of reducing fat and cholesterol intake (Asgar et al., 2010) but may also decrease flavor acceptability. The reduction of fat content caused by plant protein addition is in agreement with previous studies of Grasso et al. (2019) and Danowska-Oziewicz (2014). There is a lack of data on the fat profile of blended meat although for plant-based meat analogues, Yang et al. (2023) reported a lower cholesterol and greater polyunsaturated fat compared with meat. Kilic et al. (2010) reported meatballs with texturized soy protein had greater ratios of polyunsaturated fatty acids to saturated fatty acids than 100% beef meatballs. Therefore, it is likely that blended meat products have a lower cholesterol and fat content and higher PUFA's, but studies are needed to confirm this across a variety of plant protein additives.

Ash content (including minerals and vitamins) also showed a small increase with increasing plant protein content which may indicate an increase in vitamin and mineral content for blended burgers. However, it is worth noting that according to the regulation of the Food and Nutrition Service (1999) of USDA, vegetable protein products should not exceed 30% of the raw or cooked meat products due to the reduced bioavailability of iron and zinc in plant-based ingredients. Overall, the nutritive value of the blended burgers in this study has parity with meat burgers for protein content and may be considered superior in terms of reduced fat content and possible increased mineral and vitamin content. Further study on the bioavailability of plant-derived nutrients [protein, and inorganics (vitamin and mineral)] is warranted.

There were no color differences between conventional and blended meat patties for control versus FPI or PPI, but the yellowness of the patties increased at high levels of HTTP (21.3% and 42.5%). In general, the control products were darker and much more red and less yellow than all other formulations. The color differences were less obvious after cooking except for products where the HTPP content was high (42.5%) and in this case, the patties were lighter, redder, and more yellow. The color of our blended raw patties is in agreement with other studies of PPI and texturized plant protein (Bakhsh et al., 2021; Baugreet et al., 2016; Deliza et al., 2002). Deliza et al. (2002) pointed out that adding color can improve the appearance of both raw and cooked blended patties by rectifying the pale color of texturized soy protein, thereby making the product more appealing to the consumer. Therefore, consideration of the color of the texturized protein used or the addition of color additives to blended patties is recommended if the blended products are to have a similar appearance to conventional meat. Selling cooked products, or using packaging for raw blended meat products which hides the appearance, would also minimize any consumer bias caused by the product's appearance (Stella et al., 2018).

CONCLUSIONS

Adding plant proteins, such as PPI, FPI, and HTPP, had variable effects on the physicochemical traits and composition of blended meat patties. The use of plant protein decreased cooking loss, compression juiciness, and increased nutritional characteristics of blended meat products, as exemplified by reduced fat content and similar protein levels compared with conventional meat. FPI and PPI were similar in their effects on water-binding capacity in blended meat matrices without significant effects on texture. HTPP resulted in softer patties with lower shear force, hardness, springiness, chewiness, and gumminess, especially when its content exceeded 8.5%. The blended patties were less red and lighter and more yellow than the control patties in both raw and cooked conditions. The results of this study confirm that natural binders and texturized plant proteins alone cannot achieve the same structural integrity and texture as conventional meat. In summary, PPI, FPI, and HTPP have potential as plant-based ingredients for blended meat products although the texture is different to meat products. Further study could involve consumers in the evaluation of the visual appearance, flavor, and texture of blended meat products and a more detailed nutrient profile investigation could be conducted.

AUTHOR CONTRIBUTIONS

Xinyu Miao: Conceptualization, Investigation, Methodology, Data curation, Formal analysis, Writing – original draft, Visualization. Melindee Hastie: Supervision, Writing – review & editing. Minh Ha: Visualization, Supervision. Phyllis J. Shand: Writing – review & editing. Robyn D. Warner: Conceptualization, Resources, Writing – review & editing, Visualization, Supervision, Funding acquisition.

ACKNOWLEDGMENTS

The authors acknowledge Dr. Graham Hepworth from the Melbourne Statistical Consulting Centre for the support of statistical analysis and Rozita Spirovska Vaskoska and Zhenzhao Li for assisting in preparation of samples. Open access publishing facilitated by The University of Melbourne, as part of the Wiley - The University of Melbourne agreement via the Council of Australian University Librarians.

FUNDING INFORMATION

This research was supported by the Future Food project of Hallmark Research Initiatives at the University of Melbourne and the funding source had no role in the design, interpretation of data or writing of manuscript.

CONFLICT OF INTEREST STATEMENT

The authors declare that they have no conflict of interest.

ETHICS STATEMENT

No human or animal subjects were used in the research for this paper.

References

Abete I, Romaguera D, Vieira AR, Munain DE, AL, Norat T. Association between total, processed, red and white meat consumption and all‐cause, CVD and IHD mortality: a meta‐analysis of cohort studies. Br J Nutr. 2014;112:762–775.

Acebron LB, Dopico DC. The importance of intrinsic and extrinsic cues to expected and experienced quality: an empirical application for beef. Food Qual Prefer. 2000;11:229–238.

Ares G, Varela P. Trained vs. consumer panels for analytical testing: fueling a long lasting debate in the field. Food Qual Prefer. 2017;61:79–86.

Asgar M, Fazilah A, Huda N, Bhat R, Karim A. Nonmeat protein alternatives as meat extenders and meat analogs. Compr Rev Food Sci Food Saf. 2010;9:513–529.

Bakhsh A, Lee SJ, Lee EY, Hwang YH, Joo ST. Characteristics of beef patties substituted by different levels of textured Vegetable protein and taste traits assessed by electronic tongue system. Foods. 2021;10:2811.

Baugreet S, Kerry JP, Botinestean C, Allen P, Hamill RM. Development of novel fortified beef patties with added functional protein ingredients for the elderly. Meat Sci. 2016;122:40–47.

Baune M‐C, Terjung N, Tülbek MÇ, Boukid F. Textured vegetable proteins (TVP): future foods standing on their merits as meat alternatives. Future Foods. 2022;6: [eLocator: 100181].

Berry B, Leddy K. Effects of freezing rate frozen storage temperature and storage time on tenderness values of beef patties. J Food Sci. 1989;54:291–296.

Boukid F, Rosell CM, Castellari M. Pea protein ingredients: a mainstream ingredient to (re) formulate innovative foods and beverages. Trends Food Sci Technol. 2021;110:729–742.

Bourne M. Principles of objective texture measurement. In: Bourne M, editor. Food texture and viscosity: concept and measurement. Food Science and Technology, International Series. New York: Academic press; 2002;107–188.

Cai R, Mccurdy A, Baik BK. Textural property of 6 legume curds in relation to their protein constituents. J Food Sci. 2002;67:1725–1730.

Cardello AV, Secrist J, Smith J. Effects of soy particle size and color on the sensory properties of ground beef patties. J Food Qual. 1983;6:139–151.

Danowska‐Oziewicz M. Effect of soy protein isolate on physicochemical properties, lipid oxidation and sensory quality of low‐fat pork patties stored in vacuum, MAP and frozen state. J Food Process Preserv. 2014;38:641–654.

Deliza R, Saldivar SS, Germani R, Benassi V, Cabral L. The effects of colored textured soybean protein (TSP) on sensory and physical attributes of ground beef patties. J Sens Stud. 2002;17:121–132.

Egbert R, Borders C. Achieving success with meat analogs. Food Technol (Chicago). 2006;60:28–34.

Font‐I‐Furnols M, Guerrero L. Consumer preference, behavior and perception about meat and meat products: an overview. Meat Sci. 2014;98:361–371.

Food and Agriculture Organization of the United Nations. Food energy – methods of analysis and conversion factors. 2003 Available: https://www.fao.org/3/y5022e/y5022e00.htm [Accessed 2003].

Food and Nutrition Service. Modification of the “Vegetable Protein Products” Requirements for the National School Lunch Program, School Breakfast Program, Summer Food Service Program and Child and Adult Care Food Program. USDA (ed.). Federal Register: The Daily Journal of the United States Government. 1999.

Food Standards Australia New Zealand. Australian food composition database. Food Details. 2022.

Ge J, Sun C, Chang Y, Li S, Zhang Y, Fang Y. Understanding the differences in heat‐induced gel properties of twelve legume proteins: a comparative study. Food Res Int. 2023;163: [eLocator: 112134].

Gorissen SHM, Crombag JJR, Senden JMG, Waterval WAH, Bierau J, Verdijk LB, et al. Protein content and amino acid composition of commercially available plant‐based protein isolates. Amino Acids. 2018;50:1685–1695.

Grasso S, Smith G, Bowers S, Ajayi OM, Swainson M. Effect of texturised soy protein and yeast on the instrumental and sensory quality of hybrid beef meatballs. J Food Sci Technol. 2019;56:3126–3135.

Guàrdia M, Guerrero L, Gelabert J, Gou P, Arnau J. Consumer attitude towards sodium reduction in meat products and acceptability of fermented sausages with reduced sodium content. Meat Sci. 2006;73:484–490.

Gujral HS, Kaur A, Singh N, Sodhi NS. Effect of liquid whole egg, fat and textured soy protein on the textural and cooking properties of raw and baked patties from goat meat. J Food Eng. 2002;53:377–385.

Hong S, Shen Y, Li Y. Physicochemical and functional properties of texturized vegetable proteins and cooked patty textures: comprehensive characterization and correlation analysis. Foods. 2022;11:2619.

Karaca AC, Low N, Nickerson M. Emulsifying properties of chickpea, faba bean, lentil and pea proteins produced by isoelectric precipitation and salt extraction. Food Res Int. 2011;44:2742–2750.

Keivaninahr F, Gadkari P, Benis KZ, Tulbek M, Ghosh S. Prediction of emulsification behaviour of pea and faba bean protein concentrates and isolates from structure–functionality analysis. RSC Adv. 2021;11:12117–12135.

Kilic B, Kankaya T, Ekici Y, Orhan H. Effect of textured soy protein on quality characteristics of low fat cooked kofte (Turkish meatball). J Anim Vet Adv. 2010;9:3048–3054.

Lam A, Can Karaca A, Tyler R, Nickerson M. Pea protein isolates: structure, extraction, and functionality. Food Rev Intl. 2018;34:126–147.

Lee N, Kwak HS, Joo J‐Y, Kang J, Lee Y. Effects of partial replacement of pork meat with chicken or duck meat on the texture, flavor, and consumer acceptance of sausage. J Food Qual. 2018;2018:1–9.

Maningat CC, Jeradechachai T, Buttshaw MR. Textured wheat and pea proteins for meat alternative applications. Cereal Chem. 2022;99:37–66.

Marinangeli CP, Fabek H, Ahmed M, Sanchez‐Hernandez D, Foisy S, House JD. The effect of increasing intakes of plant protein on the protein quality of Canadian diets. Appl Physiol Nutr Metab. 2021;46:771–780.

Mariotti F, Tomé D, Mirand PP. Converting nitrogen into protein—beyond 6.25 and Jones' factors. Crit Rev Food Sci Nutr. 2008;48:177–184.

Mena B, Fang Z, Ashman H, Hutchings S, Ha M, Shand PJ, et al. Influence of cooking method, fat content and food additives on physicochemical and nutritional properties of beef meatballs fortified with sugarcane fibre. Int J Food Sci Technol. 2020;55:2381–2390.

Mena B, Hutchings SC, Ha M, Ashman H, Shand PJ, Warner RD. Effect of age on sensory perception of beef patties with varying firmness. Meat Sci. 2022;192: [eLocator: 108869].

Multari S, Stewart D, Russell WR. Potential of fava bean as future protein supply to partially replace meat intake in the human diet. Compr Rev Food Sci Food Saf. 2015;14:511–522.

Neacsu M, Mcbey D, Johnstone A. Meat reduction and plant‐based food: replacement of meat: nutritional, health, and social aspects. In: Nadathur SR, Wanasundara JPD, Scanlin L, editors. Sustainable protein sources. Amsterdam: Academic Press; 2017;359–375.

Neville M, Tarrega A, Hewson L, Foster T. Consumer‐orientated development of hybrid beef burger and sausage analogues. Food Sci Nutr. 2017;5:852–864.

Nosworthy MG, Neufeld J, Frohlich P, Young G, Malcolmson L, House JD. Determination of the protein quality of cooked Canadian pulses. Food Sci Nutr. 2017;5:896–903.

Petrat‐Melin B, Dam S. Textural and consumer‐aided characterisation and acceptability of a hybrid meat and plant‐based burger patty. Foods. 2023;12:2246.

Possidónio C, Prada M, Graça J, Piazza J. Consumer perceptions of conventional and alternative protein sources: a mixed‐methods approach with meal and product framing. Appetite. 2021;156: [eLocator: 104860].

Schösler H, DE Boer J, Boersema JJ. Can we cut out the meat of the dish? Constructing consumer‐oriented pathways towards meat substitution. Appetite. 2012;58:39–47.

Sha L, Xiong YL. Plant protein‐based alternatives of reconstructed meat: science, technology, and challenges. Trends Food Sci Technol. 2020;102:51–61.

Shanthakumar P, Klepacka J, Bains A, Chawla P, Dhull SB, Najda A. The current situation of pea protein and its application in the food industry. Molecules. 2022;27:5354.

Shen Y, Hong S, Du Z, Chao M, O'quinn T, Li Y. Effect of adding modified pea protein as functional extender on the physical and sensory properties of beef patties. LWT. 2022;154: [eLocator: 112774].

Shoaib A, Sahar A, Sameen A, Saleem A, Tahir AT. Use of pea and rice protein isolates as source of meat extenders in the development of chicken nuggets. J Food Process Preserv. 2018;42: [eLocator: e13763].

Stella S, Bernardi C, Tirloni E. Influence of skin packaging on raw beef quality: a review. J Food Qual. 2018;2018:1–9.

Sun XD, Holley RA. Factors influencing gel formation by myofibrillar proteins in muscle foods. Compr Rev Food Sci Food Saf. 2011;10:33–51.

Tucker KL. Dietary intake and coronary heart disease: a variety of nutrients and phytochemicals are important. Curr Treat Options Cardiovasc Med. 2004;6:291–302.

Tuorila H, Cardello AV. Consumer responses to an off‐flavor in juice in the presence of specific health claims. Food Qual Prefer. 2002;13:561–569.

Vatansever S, Tulbek MC, Riaz MN. Low‐and high‐moisture extrusion of pulse proteins as plant‐based meat ingredients: a review. Cereal Foods World. 2020;65:12–14.

Warner RD. The eating quality of meat: IV—Water holding capacity and juiciness. In: Toldrá F, editor. Lawrie's meat science: Technology and Nutrition. Cambridge: Woodhead Publishing Series in Food Science; 2023;457–508.

Weiss J, Gibis M, Schuh V, Salminen H. Advances in ingredient and processing systems for meat and meat products. Meat Sci. 2010;86:196–213.

Xiong YL. Structure‐function relationships of muscle proteins. Food proteins and their applications. Boca Raton, Florida: CRC Press; 2017.

Yang J, Sagis LMC. Interfacial behavior of plant proteins—novel sources and extraction methods. Curr Opin Colloid Interface Sci. 2021;56: [eLocator: 101499].

Yang Y, Zheng Y, Ma W, Zhang Y, Sun C, Fang Y. Meat and plant‐based meat analogs: nutritional profile and in vitro digestion comparison. Food Hydrocoll. 2023;143: [eLocator: 108886].

Zhao H, Shen C, Wu Z, Zhang Z, Xu C. Comparison of wheat, soybean, rice, and pea protein properties for effective applications in food products. J Food Biochem. 2020;44: [eLocator: e13157].