Zamorano University 

Food Science and Technology Department 

B.S. in Food Science and Technology 

 

 

 

 

 

 

 

 

 

 

Special Graduation Project 

Evaluation of the nutritional components and physicochemical 

properties of plant-based foods: beef patty analogues 

 

 

 

Student 

Gracia Maria Chiguila Rodriguez 

Advisors 

Adela M. Acosta, D.Sc. 

Damir Dennis Torrico, Ph.D. 

 

 

 

Honduras, November 2025 



2 

 

 

Authorities 

 

 

 

KEITH L. ANDREWS 

President i.a. 

 

 

 

 

ANA M. MAIER ACOSTA 

Vice President and Academic Dean 

 

 

 

 

ADELA ACOSTA MARCHETTI  

Director of Food Science and Technology Department 

 

 

 

 

JULIO NAVARRO 

Secretary General 

 

  



3 

 

 

Aknowledgments 

I would like to thank Dr. Damir Torrico for opening the doors of his laboratory and 

for his guidance during the development of this project. I am also grateful to Dr. Acosta 

from Zamorano University for her support and valuable feedback throughout this wor k. 

Finally, I appreciate the University of Illinois at Urbana-Champaign for providing the 

facilities and equipment needed to conduct this research.  

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



4 

 

 

Table of Contents 

Aknowledgments .................................................................................................................................... 3 

List of Tables ........................................................................................................................................... 6 

List of Appendices ................................................................................................................................... 7 

Abstract ................................................................................................................................................... 8 

Resumen ................................................................................................................................................. 9 

Introduction .......................................................................................................................................... 10 

Materials and Methods ......................................................................................................................... 13 

Study Location ....................................................................................................................................... 13 

Collection of Materials .......................................................................................................................... 13 

Preliminary Trials .................................................................................................................................. 13 

Preparation of Burger Patties ............................................................................................................... 14 

Cooking Method ................................................................................................................................... 15 

Physicochemical Analysis ...................................................................................................................... 15 

Water Activity Analysis ......................................................................................................................... 16 

Moisture Content .................................................................................................................................. 16 

Cooking Loss .......................................................................................................................................... 16 

Shrinkage............................................................................................................................................... 16 

Color Analysis ........................................................................................................................................ 17 

Texture Profile Analysis......................................................................................................................... 17 

Proximal Analysis .................................................................................................................................. 17 

Protein Content ..................................................................................................................................... 17 

Total Fat ................................................................................................................................................ 18 

Experimental Design & Statistical Analysis ........................................................................................... 18 

Results and Discussion .......................................................................................................................... 19 



5 

 

 

Physicochemical Analysis ...................................................................................................................... 19 

Water Activity Analysis (Aw) ................................................................................................................. 19 

Moisture Content .................................................................................................................................. 20 

Cooking Loss .......................................................................................................................................... 21 

Shrinkage............................................................................................................................................... 22 

Color Analysis ........................................................................................................................................ 24 

Texture Profile Analysis......................................................................................................................... 25 

Hardness ............................................................................................................................................... 26 

Springiness ............................................................................................................................................ 26 

Proximal Analysis .................................................................................................................................. 28 

Total Fat ................................................................................................................................................ 29 

Total Protein ......................................................................................................................................... 30 

Correlation Analysis .............................................................................................................................. 31 

Conclusions ........................................................................................................................................... 34 

Recommendations ................................................................................................................................ 35 

References ............................................................................................................................................ 36 

Appendices ............................................................................................................................................ 41 

 

 

 

 

 

 

 



6 

 

 

List of Tables  

Table 1 Composition of individual 110 g burger patties. ...................................................................... 15 

Table 2 Water activity analysis results of plant-based and animal-based patties. ............................... 19 

Table 3 Moisture content results of plant-based and animal-based patties. ....................................... 21 

Table 4 Cooking loss results of plant-based and animal-based patties. ............................................... 22 

Table 5 Shrinkage results of plant-based and animal-based patties. ................................................... 24 

Table 6 Percentage shrinkage (height, area, and volume reduction) of plant-based and animal-based 

patties. .................................................................................................................................................. 24 

Table 7 Color analysis results of plant-based and animal-based patties. ............................................. 25 

Table 8 Hardness results of plant-based and animal-based patties. .................................................... 26 

Table 9 Springiness results of plant-based and animal-based patties. ................................................. 27 

Table 10 Compression rate results of plant-based and animal-based patties. .................................... 28 

Table 11 Fat content results of plant-based and animal-based patties. .............................................. 29 

Table 12 Protein content results of plant-based and animal-based patties. ........................................ 30 

Table 13 Pearson correlation analysis of physicochemical, proximal, and textural parameters of plant-

based and animal-based patties. .......................................................................................................... 32 

 

 

 

 

 

 

 

 

 



7 

 

 

List of Appendices 

Appendices A Correlation analysis ........................................................................................................ 41 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 



8 

 

 

Abstract 

The rising demand for plant-based alternatives has driven the development of meat analogs intended 

to resemble animal-based products in nutritional composition and physicochemical properties. This 

study compared the nutritional and physicochemical characteristics of lentil-based and textured 

vegetable protein (TVP)-based patties with traditional beef patties. The formulations were optimized 

through preliminary trials and evaluated for water activity, moisture content, cooking loss, shrinkage, 

color, texture profile, fat, and protein content. Beef patties showed the highest protein levels, along 

with greater cooking loss, shrinkage, hardness, and springiness, attributed to protein denaturation 

during cooking. Lentil-based patties had the lowest protein values but reached fat levels comparable 

to beef due to the addition of canola oil. In contrast, TVP-based patties presented intermediate 

protein levels and lower fat values. They also had lower hardness, springiness, and compression rate 

values. Significant positive correlations were observed between protein content and moisture, 

cooking loss, and textural parameters, highlighting the role of protein concentration in overall patty 

performance. These results indicate that TVP-based formulations offer a promising alternative to 

animal-based products, while both lentil- and TVP-based patties demonstrated distinct physical and 

textural properties compared to beef, reinforcing their unique identities as plant-based products. 

However, further adjustments in formulation are recommended to improve textural quality and 

better replicate the physicochemical behavior of meat. 

Keywords: ground beef, lentils, plant-based patties, sustainability, texture, textured vegetable 

protein 



9 

 

 

Resumen 

La creciente demanda de alternativas de origen vegetal ha impulsado el desarrollo de análogos 

cárnicos destinados a asemejarse a los productos de origen animal en su composición nutricional y 

propiedades fisicoquímicas. Este estudio comparó las características nutricionales y fisicoquímicas de 

hamburguesas elaboradas a base de lentejas y de proteína vegetal texturizada (TVP) con 

hamburguesas tradicionales de res. Las formulaciones fueron optimizadas mediante pruebas 

preliminares y evaluadas en cuanto a actividad de agua, contenido de humedad, pérdida por cocción, 

encogimiento, color, perfil de textura, grasa y proteína. Las hamburguesas de res mostraron el mayor 

contenido de proteína, además de presentar mayor pérdida por cocción, encogimiento, dureza y 

elasticidad, atribuidos a la desnaturalización de proteínas durante la cocción. Las hamburguesas de 

lentejas tuvieron los valores más bajos de proteína, pero alcanzaron niveles de grasa comparables a 

la res debido a la adición de aceite de canola. En contraste, las hamburguesas de TVP presentaron 

niveles intermedios de proteína y menores valores de grasa. También mostraron menor dureza, 

elasticidad y tasa de compresión. Se observaron correlaciones positivas significativas entre el 

contenido de proteína y la humedad, la pérdida por cocción y los parámetros texturales, lo que resalta 

el papel de la concentración proteica en el desempeño general de las hamburguesas. Estos resultados 

indican que las formulaciones a base de soya ofrecen una alternativa prometedora a los productos de 

origen animal, mientras que tanto las hamburguesas de lentejas como las de TVP demostraron 

propiedades físicas y texturales distintas a las de res, reforzando su identidad como productos de 

origen vegetal. Sin embargo, se recomiendan ajustes adicionales en la formulación para mejorar la 

calidad textural y replicar con mayor precisión el comportamiento fisicoquímico de la carne. 

Palabras clave: carne molida, hamburguesas vegetales, lentejas, proteína vegetal texturizada, 

sostenibilidad, textura 

 

 



10 

 

 

Introduction 

The constant changes in consumer needs and preferences make the food industry transform 

continually, by adapting to new consumer trends and behaviors. In recent years, the demand for plant-

based products has rapidly grown, driven by health, environment, sustainability, and animal welfare 

concerns. Plant-based alternatives are products that aim to imitate animal-based foods in terms of 

their appearance, flavor, functionality, and other characteristics (Bryant, 2022). These alternatives are 

typically formulated using plant-based ingredients, including legumes, grains, and other sources. The 

origin of plant-based meat analogues dates back several decades; however, a key development in 

their evolution was marked by the introduction of new-generation products from companies such as 

Beyond Meat (2009) and Impossible Foods (2011), which brought innovation by employing 

biotechnologies to improve the structural and flavor characteristics of these substitutes (Ali & Bharali, 

2025). 

People around the world are increasingly interested in adopting diets that reduce the 

consumption of certain animal-based foods such as meat and dairy. A global survey reported that in 

2019, 40% of consumers were trying to reduce their consumption of animal proteins (Aschemann-

Witzel et al., 2020). Currently, 39% of US consumers attempt to consume more plant-based foods 

(Ohr, 2020). According to the Plant Based Foods Association (2022), plant-based food sales grew 6.6% 

from 2021 to 2022 in the US. Other countries, such as the UK, have shown a significant increase in 

consumption of plant-based products (6.7% in 2008 to 13.1% in 2019) (Alae-Carew et al., 2022). 

Furthermore, reports indicate that regions such as Asia and the Pacific play a significant role in the 

plant-based alternatives markets, particularly in the plant-based meat and milk sectors (Wunsch, 

2024), demonstrating the increasing popularity of this eating habit and its expanded market presence 

globally. 

The growth in the consumption of plant-based foods is supported by several factors. 

Researchers have found that a plant-based diet can improve the health and well-being of consumers 



11 

 

 

through the effects of its bioactive compounds (Peña-Jorquera et al., 2023). Likewise, these products 

are known as good sources of dietary fiber and are lower in calories, cholesterol, and saturated fat 

than animal-based products (El Sadig & Wu, 2024). Furthermore, they are associated with the 

prevention of chronic diseases such as cardiovascular diseases, cancer, and others (Thompson et al., 

2023). Additionally, the production and consumption of animal-based products are related to 

significant contributions to various environmental challenges that endanger sustainability, including 

greenhouse gas emissions, land use, and degradation, among others (Espinosa-Marrón et al., 2022). 

Studies have also shown that all food production systems have detrimental effects on bionetworks, 

with most of the harm affecting wildlife (Hampton et al., 2021). Consequently, animal-based diets 

have a greater environmental impact compared to plant-based alternatives (Nelson et al., 2016). This 

has led many individuals to reconsider their dietary choices in pursuit of environmental sustainability 

and improved animal welfare. 

Among plant-based alternatives, burger patties have emerged as a particularly popular 

product due to their convenience and versatility. They aim to recreate the nutritional value and 

sensory attributes of animal-based burgers, including their distinct bites, chewiness, succulence, and 

firmness (Kyriakopoulou et al., 2021). Some common raw materials that are used for this purpose 

comprise soy protein, which has been recognized as an ideal option due to its good processing 

characteristics, balanced nutritional value, and relatively low price (Wang et al., 2023); and lentils, 

which are known as good sources of complex carbohydrates, protein, fiber, vitamins, and minerals 

(Durgapal, 2020). 

However, even though these ingredients are growing in popularity due to their potential 

benefits, doubts persist regarding their capacity to provide nutritional content for human diets 

comparable to that of animal-based foods, since they are not similar in composition or structure 

(Nolden & Forde, 2023; van Vliet et al., 2020).  



12 

 

 

Moreover, beyond nutritional value, for plant-based alternatives, replicating the 

physicochemical properties of their animal-based counterparts remains a challenge, since these 

characteristics significantly impact consumer acceptance and overall quality. Among these, one of the 

most complex attributes to replicate is texture, due to the unique functional properties of animal 

proteins (Giacalone et al., 2022). Also, parameters such as moisture content, water activity, color, 

cooking loss, and shrinkage are crucial indicators of the product’s performance during preparation 

and consumption, which not only affect sensory attributes but also affect their shelf life and consumer 

perception (McClements & Grossmann, 2022). Some studies have mentioned that plant-based 

alternatives often face challenges in mimicking properties such as juiciness and tenderness of 

traditional meat products. These difficulties are mainly attributed to the structural and functional 

differences of plant proteins, which lack the same binding and emulsifying capacity of animal proteins, 

leading to undesirable textures (Dekkers et al., 2018; Sha & Xiong, 2020). 

Given the increasing demand for plant-based foods and ongoing concerns regarding their 

nutritional value and the ability to replicate physicochemical properties compared to animal-based 

products, even though they have been promoted as a sustainable option, it is essential to conduct 

studies that contribute to more information about these alternatives. For this reason, this research 

aimed to evaluate the nutritional components and physicochemical properties of plant-based foods 

compared to their animal-based counterparts. In addition, the following objectives were considered: 

To formulate plant-based burger patties for comparative analysis with an animal-based 

equivalent. 

To compare the nutritional content of plant-based and beef burger patties in terms of protein 

and fats. 

To analyze the physicochemical properties of plant-based and beef burger patties. 



13 

 

 

Materials and Methods  

Study Location 

The processing of animal-based and plant-based burger patties, their physicochemical 

properties, texture, and proximal analysis were conducted at the University of Illinois Urbana-

Champaign, Urbana, Illinois, in the United States of America. 

Collection of Materials 

The primary raw materials used for the preparation of plant-based burger patties included 

Great Value® (Bentonville, AR, USA) brand lentils and NOW Real Food® (Bloomingdale, IL, USA) brand 

organic textured vegetable protein, as well as Cargill Meat Solutions (Wichita, KS, USA) brand all 

natural ground beef chuck (80% lean, 20% fat), which was utilized to elaborate animal-based burger 

patties as the control group in the experiment. Ground beef was stored at −18 °C before use. 

Additionally, Meijer® (Grand Rapids, MI, USA) brand salt, Great Value (Bentonville, AR, USA) brand 

canola oil, and Great Value (Bentonville, AR, USA) brand all-purpose flour were used not only to 

improve the structural integrity and cohesiveness of the patties. These ingredients were selected 

based on their availability, as well as their reliability and results from preliminary trials. All the 

ingredients were purchased from local markets in Urbana-Champaign, IL, USA. 

Preliminary Trials 

 Preliminary focus groups were conducted in the sensory facilities of the University of Illinois 

to evaluate and adjust sensory attributes such as texture and taste. Panelists participated in tasting 

different formulations of plant-based patties and provided feedback on flavor and textural 

characteristics. The methodology followed an open discussion format, and the main responses from 

consumers were recorded to guide the refinement of the formulations. The feedback obtained from 

these sessions supported the optimization of the final recipes used in the study. 

For the formulation of the plant-based burger patties, the recipe proposed by Samard et al. 

(2021) was used as a reference, excluding all additives mentioned in the original formulation except 



14 

 

 

for salt. Based on this, the recipe was adapted to contain around 85% plant-based raw materials and 

15% oil. However, during preliminary trials, some inconsistencies were observed in terms of texture, 

as the burgers made from both plant matrices lacked cohesiveness. Furthermore, the initial amount 

of salt used was insufficient to provide a comparable taste to beef (based on preliminary focus group 

panels). As part of the optimization process, several adjustments were made to the formulation, 

including increasing the salt content to enhance flavor and increasing the oil content to improve 

texture. However, even with the increased oil concentration, the desired improvement was not 

achieved compared to that of beef patties (based on preliminary focus panels), so a binding agent 

(flour) was incorporated, which enhanced the cohesiveness and resulted in a firmer burger structure. 

Preparation of Burger Patties 

The methods used to prepare the burger patties and their formulations were selected based 

on preliminary tests. Two types of plant-based burger patties were prepared using lentils and textured 

vegetable protein (TVP, derived from soy). These ingredients were selected due to their high protein 

content and their ability to provide a texture that resembles that of conventional meat patties 

(Chelladurai & Erkinbaev, 2020; Riaz, 2001). For lentil patties, lentils were boiled in water for 25 

minutes to obtain soft grains. A water-to-lentil ratio of approximately 2.5:1 was applied based on 

preliminary trials to ensure adequate hydration without excessive residual moisture. After boiling, 

lentils were passed through a sieve and left to rest for 20 minutes, then they were blended using a 

Proctor Silex® brand immersion blender and mixed with salt, all-purpose flour, and canola oil (Table 

1) until the mixture was well-combined but still had a granular texture. 

In the case of TVP burger patties, textured vegetable protein was used as the main ingredient. TVP 

was hydrated with boiling water in a bowl for 25 minutes; after hydration, it was passed through a 

sieve and squeezed until the excess water was removed. Subsequently, TVP was mixed with salt, all-

purpose flour, and canola oil (Table 1) until all the ingredients were integrated. For the preparation of 



15 

 

 

animal-based burger patties (control group), ground beef was mixed with salt until a homogeneous 

mixture was obtained. The composition of individual 110 g patties is presented in Table 1. 

Table 1 

Composition of individual 110 g burger patties. 

Ingredients (%) 
Treatments 

Ground beef burger patty (%) Lentil burger patty (%) TVP burger patty (%) 

Ground beef 99.73 - - 

Lentils** - 72.45 - 

TVP* - - 72.45 

Canola oil - 18.18 18.18 

Flour - 9.09 9.09 

Salt 0.27 0.27 0.27 

TOTAL 100 100 100 
Note. TVP= Textured Vegetable Protein; *TVP was already hydrated before incorporation; **Lentils were already cooked before 

incorporation 

All the mixtures were subjected to a molding process. They were placed into a non-stick 

HOULIME brand burger press and molded to achieve a uniform and desirable shape. Finally, burger 

patties were frozen at -18 °C for at least one day before being cooked in order to retain their quality 

(Rajaretnam & Malik, 2023). 

Cooking Method 

Burger patties were cooked in a PRESTO® brand electric griddle to control the temperature 

throughout the process. An internal temperature of 71 °C (160 °F) was used to ensure that they were 

properly cooked and to prevent microbial contamination (United States Department of Agriculture, 

2020). For this purpose, a cooking time of 12 minutes (6 minutes per side) at 177 °C (350 °F) was used 

to reach the internal temperature of 71 °C for all patties. 

Physicochemical Analysis 

Physicochemical analyses were conducted on both the plant-based burger patties and the 

animal-based patties (control). Water activity (Aw), moisture content, color, and texture profile 

analysis (TPA) were measured after cooking. Shrinkage and cooking loss were evaluated by comparing 

the samples before and after cooking. 



16 

 

 

Water Activity Analysis 

Water activity was determined using an HD-4B Smart Water Activity Meter (Measuring 

Instrument) with a WSC-4 water activity sensor. All the samples were ground in advance to be placed 

in the equipment's measuring sensor. 

Moisture Content 

A U.S. Solid moisture analyzer (5SS-HMA01) was used to assess the moisture content of the 

burger patties. All the samples were ground, and 1 gram of each was placed into the equipment. 

Cooking Loss 

The cooking loss (Eq. 1) was determined as the percentage of weight loss that occurred after 

cooking. This value was obtained by weighing the samples before and after cooking. To calculate this, 

the following equation was used: 

                       𝐶𝑜𝑜𝑘𝑖𝑛𝑔 𝐿𝑜𝑠𝑠 (%) =
𝐼𝑛𝑖𝑡𝑖𝑎𝑙 𝑊𝑒𝑖𝑔ℎ𝑡−𝑊𝑒𝑖𝑔ℎ𝑡 𝑎𝑓𝑡𝑒𝑟 𝑐𝑜𝑜𝑘𝑖𝑛𝑔 

𝐼𝑛𝑖𝑡𝑖𝑎𝑙 𝑊𝑒𝑖𝑔ℎ𝑡
 𝑥 100                                [1] 

Where: 

Initial Weight is the raw weight of the sample before cooking (g). 

Weight after cooking is the final weight of the sample after the cooking process (g). 

Shrinkage 

The shrinkage (Eq. 2) of the patties was estimated by measuring the changes in their volume 

after cooking. Both diameter and height were measured using a 200 mm Digital Vernier Caliper 

Micrometer Gauge at three different and random points of each patty. The volume of the samples 

was calculated based on the following equation, assuming a cylindrical geometry: 

                                                𝑉𝑜𝑙𝑢𝑚𝑒 =  𝜋 𝑥
𝐷𝑖𝑎𝑚𝑒𝑡𝑒𝑟2

4
 𝑥 𝐻𝑒𝑖𝑔ℎ𝑡                                                    [2] 

Where: 

π (pi) is a mathematical constant approximately equal to 3.1416. 

Diameter is the straight-line distance across the circular base of the patty (cm). 

Height is the thickness of the patty measured vertically (cm). 



17 

 

 

Finally, the percentage of shrinkage was calculated using the following equation (Eq. 3): 

                                   𝑆ℎ𝑟𝑖𝑛𝑘𝑎𝑔𝑒 (%) =
𝐼𝑛𝑖𝑡𝑖𝑎𝑙 𝑉𝑜𝑙𝑢𝑚𝑒−𝐹𝑖𝑛𝑎𝑙 𝑉𝑜𝑙𝑢𝑚𝑒

𝐼𝑛𝑖𝑡𝑖𝑎𝑙 𝑉𝑜𝑙𝑢𝑚𝑒
𝑥 100                                   [3] 

Where: 

Initial Volume is the volume of the patty before cooking (cm3). 

Final Volume is the volume of the patty after cooking (cm3). 

Color Analysis 

 Color analysis was performed using a precise color reader (WR-10). For this test, L*, a*, and 

b* values were measured. The L* value (lightness) operates on a scale from 0 to 100, with 0 

representing black and 100 representing white. Likewise, the a* and b* values represent chromaticity, 

where positive and negative a* values correspond to red and green, respectively, and positive b* 

values are toward the yellow, and negative b* values correspond to blue color. 

Texture Profile Analysis 

Texture analysis was evaluated using a double compression test performed with a TA.HDplus 

Texture Analyzer (Stable Micro Systems brand) equipped with a 50 mm diameter probe. The 

measurements were conducted according to the methodology described by Vu et al. (2022). Samples 

were prepared by cutting them into 1 cm × 1 cm × 1 cm cubes to get uniform geometries. 

Subsequently, they were placed in the measurement cell of the instrument and subjected to two 

cycles of compression/decompression at a fixed speed of 2.00 mm/s. The test parameters included a 

final strain of 50%, a trigger force of 15.0 g, and an interval of 5 seconds between compressions. 

Proximal Analysis 

Proximal analyses were carried out on both the plant-based burger patties and the animal-

based patties (control) after cooking. 

Protein Content 

 Protein content was determined using the AOCS Method PROTEIN-COMBUSTION (NX6.25), 

where total nitrogen was measured and multiplied by a conversion factor of 6.25 to estimate the 



18 

 

 

protein content. The analysis followed the AOCS Ba4e-93 procedure, using a LECO FP828 unit that 

measures nitrogen by combustion. The furnace operated at 950 °C to ensure complete sample 

combustion (AOCS, 1998). 

Total Fat 

Fat content was determined using the AOCS Method OIL/FAT-ETHER EXTRACT, where fats and 

oils were extracted from the sample using an ether solvent, and the remaining fat was weighed to 

calculate its percentage. For this analysis, the AOCS Method Am 5-04 was followed, using an Ankom 

XT15 extractor set to operate at 90 °C for 100 minutes, with petroleum ether as the extraction solvent 

(AOCS, 1998). 

Experimental Design & Statistical Analysis 

Physicochemical analysis were performed in all treatments. For each treatment, three 

repetitions were taken. The analyses included the following parameters: fat, protein, water activity 

(aw), moisture, color, shrinkage, cooking loss, hardness, springiness, and compression rate. A 

Randomized Complete Block Design (RCBD) was employed to assess differences in physicochemical 

parameters and nutritional content among treatments, with a significance level of P < 0.05. A Shapiro-

Wilk normality test was conducted to test the normal distribution of the data. For those results that 

exhibited a normal distribution, an ANOVA was applied, while for those that were not normal, the 

Kruskal-Wallis test was used. Additionally, a post-hoc Tukey test for multiple means comparison was 

conducted to identify individual differences. Finally, Pearson correlation analysis was conducted to 

explore the potential linear relationships between the main parameters evaluated in this study. 

 



19 

 

 

Results and Discussion 

Physicochemical Analysis 

Water Activity Analysis (Aw) 

Water activity is a parameter that describes the amount of free water available for chemical 

reactions and microbial growth in food matrices and is, therefore, a key factor in the determination 

of the shelf life of food (Syamaladevi et al., 2016). Moreover, water activity is considered a critical 

boundary for evaluating the microbiological and physicochemical properties of food products 

(Barbosa-Cánovas et al., 2020). According to the results presented in Table 2, all the treatments 

exhibited Aw values above 0.95, which indicates a high availability of free water and susceptibility to 

microbial growth (U.S Food & Drug Administration, 2014). 

Statistical analysis revealed significant differences between ground beef and lentil patties; 

however, differences between ground beef and TVP patties, and between TVP and lentil patties, were 

not statistically significant. These results are consistent compared to other studies that have shown 

that values for water activity of plant-based burger patties ranged from 0.978 to 0.982 (Ardila et al., 

2023), and for ground beef patties were around 0.992 (Li et al., 2017). On the other hand, the ANOVA 

results indicate that the type of burger patty (treatments with different formulations) had a 

statistically significant effect on Aw (F = 5.43; p = 0.02), which confirms that the differences in these 

parameter values are driven by the raw materials. 

Table 2 

Water activity analysis results of plant-based and animal-based patties. 

Treatment Water Activity 

Ground beef burger patty 0.982±0.004a 

Lentil burger patty 0.972±0.006b 

TVP burger patty 0.979±0.005ab 

CV (%) 0.62 
Note. TVP= Texture Vegetable Protein; a-b= means with different letters are statistically different (P ≤ 0.05); C.V(%) = Coefficient of 

variation 

 



20 

 

 

Moisture Content 

Moisture content is a key factor in food materials, as it influences shrinkage or expansion 

during the drying process. It refers to the total amount of water in a sample, expressed on a wet or 

dry weight basis (Joardder et al., 2019). This parameter directly influences the physical structure, 

sensory properties, and stability of food products. In Table 3, the results for moisture content are 

shown. According to statistical analysis, significant differences (p < 0.05) were found among all 

treatments; ground beef patties exhibited the highest moisture content, followed by TVP patties, 

while lentil patties had the lowest value. 

These variations can be attributed primarily to the composition and structure of the raw 

ingredients. Beef naturally contains a high proportion of muscle fibers, fat, and structural proteins 

such as actin and myosin. These proteins form a complex matrix that retains water through both 

capillary action and polar interactions, allowing for greater water retention (Zielbauer et al., 2016). 

Although some moisture is lost during cooking due to protein denaturation and structural shrinkage, 

the inherent capacity of muscle tissue to bind water enables ground beef patties to maintain higher 

moisture levels than plant-based alternatives. In the case of Textured vegetable protein (TVP), derived 

from soy, it can form fibrous, meat-like textures through extrusion (Baune et al., 2022). During this 

process, proteins denature and align into porous structures that enhance water absorption during 

rehydration. However, because soy lacks the organized fiber network found in meat, the absorbed 

water is not as tightly bound. As a result, despite its good hydration capacity, soy-based TVP tends to 

show moderate moisture retention after cooking (Hong et al., 2022).  

Finally, lentil burger patties exhibited the lowest moisture content, likely due to their low fat 

and protein content and high levels of starch and dietary fiber compared to ground beef and soy-

based TVP (Jarpa-Parra, 2018). These compositional differences limit the water-binding capacity of 

lentils, as their proteins are less functional in hydration. 



21 

 

 

The ANOVA also indicated that the type of formulation had a significant effect on moisture (F 

= 173.88, p < 0.01), suggesting that the observed variations are primarily attributable to the intrinsic 

properties of the raw materials. 

Table 3 

Moisture content results of plant-based and animal-based patties. 

Treatment Moisture (%) 

Ground beef burger patty 47.78±2.44a 

Lentil burger patty 37.83±1.41c 

TVP burger patty 43.38±1.16b 

CV (%) 2.63 
Note. TVP= Texture Vegetable Protein; a-c= means with different letters are statistically different (P ≤ 0.05); C.V(%) = Coefficient of 

variation 

Cooking Loss 

Cooking loss is an essential attribute of meat quality and is used to evaluate its water-holding 

capacity; this parameter is expressed as the percentage of weight lost in meat while cooking (Pang et 

al., 2020). To obtain this value, samples were weighed before and after cooking. According to 

statistical analysis, this attribute was significantly affected by the type of burger patty (F=159.30, p < 

0.01). As indicated in Table 4, there were no significant differences between the two types of plant-

based burger patties. However, both were different from the control (animal-based), which was the 

treatment that obtained the highest percentage of cooking loss, with 28.48% (mainly moisture and 

fat). This result is consistent with other studies, which have shown that the percentage of weight loss 

for beef patties cooked at 70 °C ranged from 29 to 32% (Vaskoska et al., 2020). 

 In meat, thermal processes induce protein denaturation, which alters the interactions 

between proteins and water, along with structural changes. Those changes affect the spacing between 

muscle fibers and create pressure gradients, impacting their water-holding capacity, leading to water 

loss (Zielbauer et al., 2016). Moreover, although the main objective of adding salt was to enhance 

sensory properties, its functional role may also be linked to this behavior. As explained by Rysová & 

Šmídová (2021), sodium chloride increases the solubility of myofibrillar proteins such as actin and 



22 

 

 

myosin, which, upon heating, form strong gels but also promote the expulsion of water from the 

muscle fibers. This mechanism may explain why beef patties, which contain a high proportion of these 

proteins, exhibited greater cooking loss compared to the plant-based patties. In contrast, lentils and 

soy contain starch with the ability to absorb and retain water, a property that contributes to the lower 

cooking loss observed in plant-based patties (Jarpa-Parra, 2018). 

 In addition, for textured vegetable protein (TVP), the extrusion cooking process thermally 

denatures the protein with a series of unfolding and aggregation, which leads to a significant reduction 

in its solubility; thereby, TVP presents lower solubility than its native form (Hong et al., 2022). In 

general, for plant-based burgers, their protein structure does not collapse during heating since the 

proteins have already been denatured by previous procedures. This affirmation is supported by Vu et 

al. (2022) who obtained similar results. 

Table 4 

Cooking loss results of plant-based and animal-based patties. 

Treatment Cooking Loss (%) 

Ground beef burger patty 28.48±2.10a 

Lentil burger patty 6.66±1.05b 

TVP burger patty 8.48±1.05b 

CV (%) 11.42 
Note. TVP= Texture Vegetable Protein; a-b= means with different letters are statistically different (P ≤ 0.05); C.V(%) = Coefficient of 

variation 

Shrinkage 

 Dimensional shrinkage during cooking is a critical parameter in both animal-based and plant-

based patties, as it reflects their ability to retain their shape and structure during cooking. The 

shrinkage of a food product is expressed as the change in volume of food material due to water loss 

during dehydration (Parthasarathi & Anandharamakrishnan, 2014). In this sense, these structural 

changes might influence consumer perception, particularly regarding size, texture, and juiciness. 

The dimensional measurements before and after cooking are shown in Table 5, while the 

corresponding percentage shrinkage values for height, area, and volume are presented in Table 6. 



23 

 

 

 In this study, ground beef burger patties exhibit the greatest reduction in area and volume 

with 47.10% and 19.79%, respectively, indicating a significant contraction during cooking. These 

reductions were statistically different from the two types of plant-based patties (P<0.01). This high 

contraction could be attributed to protein denaturation, structural changes, moisture loss, and fat 

drainage during cooking (Hong et al., 2022). These results are aligned with findings by Zielbauer et al. 

(2016), who reported that thermal processing causes protein denaturation in meat, reducing water-

holding capacity and leading to muscle fiber contraction. 

 In the case of plant-based burger patties, both presented lower dimensional 

reduction compared to the control treatment, maintaining more stable structures after cooking. 

Notably, lentil patties slightly decreased their surface area and volume by 1.23% and 4.06%, 

respectively, which is consistent with their low cooking loss. Similarly, TVP burger patties also showed 

moderate decreases in shrinkage parameters with reductions of 5.86% in surface area and 23.55% in 

volume. These reductions, despite a loss of only 8.88% of fluids, can be attributed to the lower 

apparent density of TVP. A greater initial mass to reach the target weight of 110 g was needed for this 

ingredient; as noted, an increase in expansion generally results in a decrease in apparent density (Lyu 

et al., 2023). This initial expansion during hydration and the compression of the internal matrix during 

cooking contribute to this significant decrease in observed volume. 

In addition, the ANOVA indicated that the type of burger patty (treatments with different 

formulation) had a significant effect on all shrinkage parameters, which confirms that the differences 

in these values are driven by the raw materials. 

 

 

 

 



24 

 

 

Table 5 

Shrinkage results of plant-based and animal-based patties. 

Treatment 

Shrinkage 

Before Cooking After Cooking 

Height (cm) Area (cm2) Volume (cm3) Height (cm) Area (cm2) Volume (cm3) 

Ground beef 
burger patty 

1.31±0.11b 86.88±2.53a 114.40±10.87b 1.98±0.08a 45.92±1.54c 91.01±4.54b 
 

Lentil burger 
patty 

1.24±0.06b 87.34±1.03a 108.88±5.82b 1.20±0.04b 86.25±1.04a 104.22±4.16a  

TVP burger 
patty 

1.55±0.11a 89.13±2.82a 138.97±12.89a 1.26±0.05b 83.83±2.36b 105.80±5.67a  

CV (%) 8.27 2.50 9.51 4.60 2.62 5.39  

Note. TVP= Texture Vegetable Protein; a-c= means in same column with different letters are statistically different (P≤ 0.05); C.V(%) = 

Coefficient of variation 

Table 6 

Percentage shrinkage (height, area, and volume reduction) of plant-based and animal-based patties. 

Treatment Height reduction (%) Area reduction (%) Volume reduction (%) 

Ground beef burger patty −51.53±13.91a 47.10±2.41a 19.79±8.48a 

Lentil burger patty 2.92±4.35c 1.23±2.05c 4.06±5.89b 

TVP burger patty 18.73±4.74b 5.86±2.05b 23.55±4.55a 

P Value <.0001 <.0001 0.0002 
Note. TVP= Texture Vegetable Protein; a-c= means with different letters are statistically different (P ≤ 0.05)  

 

Color Analysis 

 As stated by (Wrolstad & Smith, 2017), among the main attributes that determine food 

acceptance, color often presents a stronger influence in consumer perception than expected. Color is 

defined as the sensation produced when radiant energy within the visible spectrum (370-770 nm) 

reaches the retina of the eye (Berns, 2019); and it is frequently used as an indicator of food overall 

quality, including factors such as flavor, safety, and nutritional value (Imchen & Singh, 2023). 

 According to the ANOVA results, the L* values, which means “lightness”, were significantly 

affected by the type of burger patties (treatments with different formulations) that were used 

(F=1804.70, p<0.01). As shown in Table 7, there were significant differences among all the treatments; 

however, all of them presented low luminosity, indicating darker colors. On the other hand, TVP 



25 

 

 

burger patties had the highest L* value, indicating that they have a lighter color when compared to 

the other treatments. 

 Similarly, the a* values, where positive and negative values correspond to red and green, 

respectively, were significantly affected by the type of burger patty (F=13.51, p=0.001). Among 

treatments, all of them presented positive values, ranging from 6.47 to 8.59, meaning a tendency 

towards redness. Also, for the a* values, there were no significant differences between the two types 

of plant-based burger patties. Nevertheless, both were different from the control, which had the 

lowest value. 

Finally, for the b* values, where positive values are towards the yellow color and negative 

values correspond to blue color, there were significant differences among treatments; however, all of 

them exhibited positive values, ranging from 7.97 to 27.81, indicating a tendency towards yellowness. 

TVP burger patty presented the highest b* value with 27.81. Additionally, the b* values were 

significantly affected by the type of burger patty (F=3245.96, p<0.01).  

Table 7 

Color analysis results of plant-based and animal-based patties. 

Treatment L* a* b* 

Ground beef burger patty 18.83±0.57c 6.46±0.94b 7.97±0.74c 

Lentil burger patty 34.11±1.11b 8.15±0.93a 25.51±0.83b 

TVP burger patty 43.83±0.87a 8.59±0.77a 27.81±0.89a 

CV (%) 2.75 11.83 2.79 
Note. TVP= Texture Vegetable Protein; a-c= means in the same column with different letters are statistically different (P ≤ 0.05); C.V(%) = 

Coefficient of variation 

Texture Profile Analysis 

 Texture is one of the attributes used by consumers to evaluate food quality, playing an 

important role in the liking of a product (Day & Golding, 2016). In this context, TPA helps in the 

characterization of foods and their influence in individuals with compromised oral function (Peleg, 

2019). For this analysis, three rheological properties were assessed, including hardness, springiness, 

and compression rate. 



26 

 

 

Hardness 

Hardness was measured by the first force peak achieved by the sample. As revealed in Table 

8, there were no significant differences between the two types of plant-based burger patties, which 

presented the lowest values. Conversely, both were different from the control. As mentioned, the 

structure of plant-based protein sources did not collapse during heating, as the proteins were already 

denatured prior to cooking; thus, the cooking process had less impact on this parameter. Furthermore, 

the low loss of fluids during the thermal process led to fewer changes in the texture attributes. 

In contrast, the ground beef burger patty showed a high peak force of 23.3 N; this result might 

be attributed to the denaturation of proteins, especially of actin and myosin, that occurred during the 

heating process, leading to the expulsion of fluids and shrinkage of the product’s structure. This 

structural contraction increases the density of the protein matrix, reduces water-holding capacity, and 

results in a firmer, more compact texture, thereby contributing to the observed increase in hardness 

(Vu et al., 2022; Yu et al., 2017). Furthermore, although salt was primarily added for taste, it may have 

contributed to firmness by enhancing protein solubilization and gel formation upon heating, which 

reinforces the internal structure (Rysová & Šmídová, 2021). 

Also, non-parametric statistical analysis (Kruskal-Wallis test) reflected that the type of burger 

patty had a statistically significant effect on this parameter (χ² = 17.36, p = 0.0002). 

Table 8 

Hardness results of plant-based and animal-based patties. 

Treatment Hardness (N) 

Ground beef burger patty 23.30±3.14a 

Lentil burger patty 5.24±0.86b 

TVP burger patty 5.25±0.92b 

P Value 0.0002 
Note. TVP= Texture Vegetable Protein; a-c= means with different letters are statistically different (P ≤ 0.05)  

 

Springiness 



27 

 

 

As established by (Szczesniak, 2002), “Springiness is the rate at which a deformed material 

goes back to its undeformed condition after the deforming force is removed”. In this context, this 

parameter is essential for assessing the texture of different food products. In Table 9, the results for 

springiness values on a scale of 0 to 1 are shown. According to the ANOVA results, there were 

significant differences among all the treatments. In this case, the animal-based burger patty presented 

the highest springiness value with 0.93, indicating that it had the greatest ability to recover its original 

shape after deformation, which is related to having a firmer and more elastic texture. This result can 

be explained by the denaturation of proteins, especially of actin and myosin, during the cooking 

process, known for forming elastic gels, contributing, in this way, to its firm and springy texture 

(Tornberg, 2005). 

On the other hand, the lentil patty had the lowest springiness value, which is associated with 

its softer texture. Similarly, for the TVP burger patty, an intermediate value was obtained; however, 

even though its extruded structure offers better texture attributes over lentils, it lacks certain 

characteristics of meat proteins, such as their thermic responses. In addition, both plant-based patty 

structures were already denatured before cooking, causing minimal changes and limiting their 

elasticity (Vu et al., 2022). 

Furthermore, the statistical analysis indicated that the type of burger patty had a significant 

effect on this parameter (F=86.22, p<0.01). 

Table 9 

Springiness results of plant-based and animal-based patties. 

Treatment Springiness (%) 

Ground beef burger patty 0.93±0.01a 

Lentil burger patty 0.81±0.03c 

TVP burger patty 0.84±0.02b 

CV (%) 2.78 
Note. TVP= Texture Vegetable Protein; a-c= means with different letters are statistically different (P ≤ 0.05); C.V(%) = Coefficient of 

variation; Springiness values range from 0 to 1 

 



28 

 

 

Compression Rate 

 Compression rate is represented by the percentage reduction in a food sample's height when 

it is compressed under a specific force and is considered a key parameter in food texture analysis. In 

this study, the differences in compression rates among animal and plant-based burger patties were 

statistically significant (P < 0.05), indicating that the type of burger patty, which had different protein 

sources, significantly affected this boundary (F=22.67, p<0.01). 

In table 10, the results showed that ground beef patties exhibited the highest value with 

83.97%, meaning a greater firmness than that of plant-based alternatives. As discussed earlier, the 

denaturation and aggregation of muscle proteins during the thermal process led to a tighter and more 

cohesive structure that resists deformation (Zielbauer et al., 2016). In contrast, lentil and TVP patties, 

with 70.31% and 69.63% respectively, exhibited statistically similar values to each other, but both 

were lower than their animal counterpart. It can be attributed to the previous denaturation of the 

protein sources, causing them to unfold and aggregate correctly into new configurations. 

Consequently, the final products (burger patties) tended to present a less cohesive structure and 

become more susceptible to deformation under compressive forces (Hong et al., 2022; Vu et al., 

2022). 

Table 10 

Compression rate results of plant-based and animal-based patties. 

Treatment  Compression Rate (%) 

Ground beef burger patty  82.97±4.79a 

Lentil burger patty  70.31±5.73b 

TVP burger patty  69.63±4.10b 

CV (%)  6.37 
Note. TVP= Texture Vegetable Protein; a-b= means with different letters are statistically different (P ≤ 0.05); C.V(%) = Coefficient of 

variation 

Proximal Analysis 

 Proximate analysis is a fundamental tool in food science used to determine the macronutrient 

composition of food products. These parameters are essential for evaluating the nutritional value and 



29 

 

 

overall quality of foods; in this way, monitoring these components allows for the comparison of 

formulations and assessment of how closely plant-based products resemble traditional animal-based 

foods in nutritional terms. For this analysis, two macronutrients were assessed: total protein and total 

fat. 

Total Fat 

Fat is a crucial macronutrient that serves as a dense energy source (9 kcal/g), supplies 

essential fatty acids like omega-3 and omega-6, and supports the absorption of fat-soluble vitamins 

A, D, E, and K (Espinosa-Salas & Gonzalez-Arias, 2023). Furthermore, it enhances texture, flavor, and 

juiciness, influencing consumer acceptance. In Table 11, statistically significant differences were found 

in fat content among the burger formulations (F = 17.12; p = 0.0109). Tukey’s HSD test showed that 

the TVP burger had significantly lower fat content compared to the lentil and beef patties, which did 

not differ from each other. These outcomes suggest that the variation in fat content is primarily 

associated with the type of formulation used. 

Although beef naturally contains fat due to intramuscular adipose tissue, canola oil was 

incorporated into the plant-based formulations as a strategy to mimic the fat levels of beef. In the 

case of the TVP burger, its lower fat value may be linked to its lower oil absorption capacity, which 

limits the amount of fat retained during formulation. This behavior has been previously reported by 

(Samard & Ryu, 2019) in various textured vegetable protein systems. 

Table 11 

Fat content results of plant-based and animal-based patties. 

Treatment Fat (g/100 g) 

Ground beef burger patty 17.51±0.35a 

Lentil burger patty 18.07±1.01a 

TVP burger patty 15.69±0.02b 

CV (%) 3.04 
Note. TVP= Texture Vegetable Protein; g/100 g in wet-based; a-b= means with different letters are statistically different (P ≤ 0.05); C.V(%) 

= Coefficient of variation 

 



30 

 

 

Total Protein 

Protein is an essential macronutrient for human health, and it is required for numerous 

physiological functions, including muscle development, enzymatic functions, and overall metabolic 

regulation (Wu, 2016). According to the data shown in Table 12, the ground beef burger patty 

exhibited the highest protein content, which is consistent with its origin, as meat is known for its high-

quality protein with complete amino acid profiles and excellent digestibility (Geiker et al., 2021). 

In contrast, the protein levels in the plant-based formulations were significantly lower than in 

the animal-based patties, which can be attributed to differences in the composition of the raw 

materials. Regarding TVP burger patties, they exhibited intermediate protein levels. This result is 

consistent with the nutritional profile of soy, which contains all essential amino acids, making it one 

of the few plant-based proteins considered complete (Thrane et al., 2017); although its digestibility is 

slightly lower than that of animal proteins, soy still offers a high protein density and favorable amino 

acid profile, especially when processed into TVP. These findings align with (Biazotto et al., 2025), who 

reported that soy-based burgers presented protein contents ranging from 12 to 13 g/100 g, confirming 

their role as a valuable protein source in plant-based meat analogs. Similarly, lentil patties had the 

lowest protein content among treatments. While lentils are recognized as a valuable source of plant-

based protein, their overall protein concentration is lower compared to soy. 

Table 12 

Protein content results of plant-based and animal-based patties. 

Treatment Protein (g/100 g) 

Ground beef burger patty 17.70±0.45a 

Lentil burger patty 10.58±0.62c 

TVP burger patty 12.93±0.40b 

CV (%) 0.94 
Note. TVP= Texture Vegetable Protein; g/100 g in wet-based; a-c= means with different letters are statistically different (P ≤ 0.05); C.V(%) = 

Coefficient of variation 



31 

 

 

Correlation Analysis 

Pearson correlation analysis was conducted to explore the linear relationships among the 

various physicochemical, proximal, and textural parameters of the burger patties. Statistically 

significant correlations were observed across several key parameters, underscoring the interplay 

between ingredient composition and the final product characteristics (Table 13).  A strong positive 

correlation was found between protein content and moisture, suggesting that patties with higher 

protein concentrations retained more moisture. This result supports the idea that proteins, especially 

structural ones such as actin and myosin in meat or soy proteins in TVP, can effectively bind and retain 

water (Hong et al., 2022; Zielbauer et al., 2016). Furthermore, protein content was positively 

correlated with cooking loss, indicating that high-protein samples experienced greater fluid loss during 

cooking. This relationship is explained by the contraction of the protein network under heat, which 

expels moisture and fat (Zielbauer et al., 2016). In addition, protein content showed a strong positive 

correlation with hardness, meaning that higher protein density contributes to firmer textures. 

In terms of moisture, it was positively correlated with several other parameters, including 

cooking loss, shrinkage, and compression rate. These results suggest that higher moisture content 

leads to greater fluid loss and volume reduction during cooking, as well as an increased tendency for 

the patties to deform under compression. Regarding texture attributes, springiness and hardness 

exhibited a strong positive correlation, highlighting the cohesive nature of firmer matrices. 

Compression rate, another indicator of textural resistance, also showed a high correlation with 

hardness and cooking loss, suggesting that patties losing more fluids during cooking tend to develop 

firmer structures that are more resistant to deformation. 

Additionally, water activity (Aw), typically discussed in terms of microbial safety, showed 

significant positive correlations with protein, moisture, and shrinkage. These findings suggest that Aw 

is not only a microbiological parameter but also reflects the functional availability of water for 

structural transformations. Higher Aw may increase the susceptibility of patties to moisture loss and 



32 

 

 

dimensional reduction during thermal processing, especially when the protein matrix is less capable 

of binding water (Barbosa-Cánovas et al., 2020; Syamaladevi et al., 2016). Furthermore, the 

compression rate emerged as an integrative texture parameter, strongly correlated with protein, 

moisture, cooking loss, hardness, and springiness. These associations indicate that patties with higher 

moisture and protein content, particularly animal-based, tend to experience more severe contraction 

during cooking, resulting in denser matrices that resist compression. 

Finally, these interrelations reflect a functional chain in which protein content appears to 

influence Aw and cooking loss, which in turn affect key texture attributes like hardness, elasticity, and 

compressibility. This is particularly evident in the ground beef patties, which showed the highest 

values in these parameters. The observed correlations align with known mechanisms of protein 

denaturation and matrix contraction under heat, supporting the idea that the structural changes 

occurring in formulations with higher protein concentrations during cooking directly influence the 

final physicochemical and textural profile of the patties (Vu et al., 2022; Zielbauer et al., 2016). 

Table 13 

Pearson correlation analysis of physicochemical, proximal, and textural parameters of plant-based 

and animal-based patties. 

Parameters Pearson's r p-value 

Protein Moisture 0.938 0.0002 

Protein Aw 0.768 0.0156 

Protein Cooking loss 0.953 <0.0001 

Protein Springiness 0.753 0.0191 

Protein Hardness 0.937 0.0002 

Protein Compression rate 0.838 0.0047 

Moisture Aw 0.703 0.0344 

Moisture Cooking loss 0.859 0.0030 

Moisture Shrinkage 0.671 0.0477 

Moisture Hardness 0.813 0.0077 

Moisture Compression rate 0.704 0.0340 

Aw Shrinkage 0.685 0.0414 

Cooking loss Springiness 0.877 0.0019 

Cooking loss Hardness 0.987 <0.0001 

Cooking loss Compression rate 0.875 0.0020 



33 

 

 

Parameters Pearson's r p-value 

Springiness Hardness 0.907 0.0007 

Springiness Compression rate 0.673 0.0467 

Hardness Compression rate 0.868 0.0024 
Note. Pearson’s correlation coefficients (r) between physicochemical and textural parameters. Statistically significant correlations 

(p < 0.05). Positive values indicate direct relationships. 



34 

 

 

Conclusions 

Plant-based patties made from lentils and textured vegetable protein (TVP) were successfully 

formulated using simple, accessible ingredients. Preliminary trials allowed improvements in texture 

and structure, particularly through the incorporation of flour and adjustments in oil and salt content. 

These modifications resulted in patties with acceptable consistency and cohesion for cooking and 

analysis. In terms of nutritional composition, ground beef patties exhibited the highest protein 

content, while TVP patties presented intermediate levels and lentil patties the lowest. Although both 

plant-based alternatives had lower protein values compared to meat, lentil patties reached fat 

content comparable to beef, mainly due to the addition of canola oil. TVP patties, on the other hand, 

contained slightly more protein than lentils but had lower fat values, resulting in a different nutritional 

profile. 

Physicochemical and textural analyses revealed that beef patties retained more moisture 

before cooking but experienced greater fluid loss, shrinkage, and firmness after cooking due to protein 

denaturation. Plant-based patties, especially those made with lentils, maintained more stable 

structures and showed lower cooking loss, but were also softer and less elastic. Correlation analysis 

confirmed strong associations between protein content, moisture, texture, and cooking loss, 

indicating that protein concentration plays a central role in shaping the structural behavior of burger 

patties. Overall, beef patties maintained superior structural and textural properties, but, the plant-

based formulations exhibited promising characteristics, especially those incorporating soy-derived 

ingredients. Their performance demonstrates the feasibility of developing plant-based meat analogs 

with acceptable nutritional value and functional quality, provided that appropriate formulation 

strategies are applied.



35 

 

 

Recommendations 

A microbiological analysis with repeated measures over time is recommended before 

conducting sensory evaluations, both for beef patties and plant-based patties, in order to ensure food 

safety during storage and testing. 

A sensory analysis is recommended for future research to assess the acceptability of plant-

based patties in comparison to their animal-based counterparts. By evaluating attributes such as taste, 

texture, and overall satisfaction, among others, a clearer understanding of consumer perception can 

be obtained. Additionally, the implementation of satiety tests is encouraged to determine whether 

differences in composition influence the feeling of fullness after consumption. This would allow the 

nutritional and functional impact of these formulations to be more comprehensively evaluated. 

Further research should be directed toward the inclusion of alternative plant-based protein sources 

such as chickpeas, peas, or quinoa. These ingredients may contribute to more diverse and nutritionally 

balanced formulations. Moreover, the incorporation of natural binders or structuring agents should 

be investigated to improve texture, water retention, and overall product stability, with the aim of 

enhancing the physicochemical performance of plant-based patties to more closely resemble that of 

animal-based counterparts. 

 

 

 

 

 

 

 

 

 



36 

 

 

References 

 

Alae-Carew, C., Green, R., Stewart, C., Cook, B., Dangour, A. D. & Scheelbeek, P. F. (2022). The role of 

plant-based alternative foods in sustainable and healthy food systems: Consumption trends 

in the UK. Science of the Total Environment, 807(3), Artículo 151041. 

https://doi.org/10.1016/j.scitotenv.2021.151041 

Ali, A. & Bharali, P. (2025). The rise of plant-based meat alternatives: Challenges and perspectives. 

Food Bioscience, 68, 106640. https://doi.org/10.1016/j.fbio.2025.106640 

AOCS. (1998). AOCS official method Ba 4e-93: Generic combustion method for determination of crude 

protein.: Official methods and recommended practices of the AOCS, Firestone, D.E., editor. 

AOCS Press, Champaign, IL.  

Ardila, P., Honrado, A., Marquina, P., Beltrán, J. A. & Calanche, J. B. (2023). Innovative Plant-Based 

Burger Enriched with Tenebrio molitor Meal: Characterization and Shelf-Life. Foods, 12(18). 

https://doi.org/10.3390/foods12183460 

Aschemann-Witzel, J., Gantriis, R. F., Fraga, P. & Perez-Cueto, F. J. A. (2020). Plant-based food and 

protein trend from a business perspective: markets, consumers, and the challenges and 

opportunities in the future. Critical Reviews in Food Science and Nutrition, 61(18), 3119–3128. 

https://doi.org/10.1080/10408398.2020.1793730 

Barbosa-Cánovas, G. V., Fontana Jr., A. J., Schmidt, S. J. & Labuza. T. P. (Eds.). (2020). Water Activity in 

Foods: Fundamentals and Applications. © 2020 John Wiley & Sons, Inc.  

Baune, M. C., Terjung, N., Tülbek, M. Ç. & Boukid, F. (2022). Textured vegetable proteins (TVP): Future 

foods standing on their merits as meat alternatives. Future Foods, 6, 100181. 

https://doi.org/10.1016/j.fufo.2022.100181 

Berns, R. S. (2019). Billmeyer and Saltzman's principles of color technology. © 2019 John Wiley & Sons 

Inc.  

Biazotto, K. R., Xavier, A. C., Mattos, R. R., Furlan, J. M., Wagner, R., Bandoni, D. H. & Rosso, V. V. 

(2025). Plant-Based Burgers in the Spotlight: A Detailed Composition Evaluation and 

Comprehensive Discussion on Nutrient Adequacy. Foods, 14(3). 

https://doi.org/10.3390/foods14030372 

Bryant, C. J. (2022). Plant-based animal product alternatives are healthier and more environmentally 

sustainable than animal products. Future Foods, 6, Artículo 100174. 

https://doi.org/10.1016/j.fufo.2022.100174 

Chelladurai, V. & Erkinbaev, C. (2020). Lentils. En A. Manickavasagan y P. Thirunathan (Eds.), Pulses: 

Processing and Product Development (pp. 129–143). Springer International Publishing. 

https://doi.org/10.1007/978-3-030-41376-7_8 

Day, L. & Golding, M. (2016). Food Structure, Rheology, and Texture. En L. Melton, F. Shahidi y P. & 

Varelis (Eds.), Encyclopedia of Food Chemistry (pp. 125–129). Academic Press. 

https://doi.org/10.1016/B978-0-08-100596-5.03412-0 

Dekkers, B. L., Boom, R. M. & van der Goot, A. J. (2018). Structuring processes for meat analogues. 

Trends in Food Science & Technology, 81, 25–36. https://doi.org/10.1016/j.tifs.2018.08.011 



37 

 

 

Durgapal, S. (2020). Standardization and quality evaluation of lentil based burger patty mix [, Govind 

Ballabh Pant University of Agriculture and Technology, Pantnagar, Uttarakhand, India]. RIS. 

https://krishikosh.egranth.ac.in/items/aba439ea-ac46-4123-8279-c81ac4c03a11 

El Sadig, R. & Wu, J. (2024). Are novel plant-based meat alternatives the healthier choice? Food 

Research International, 183, Artículo 114184. https://doi.org/10.1016/j.foodres.2024.114184 

Espinosa-Marrón, A., Adams, K., Sinno, L., Cantu-Aldana, A., Tamez, M., Marrero, A., 

Bhupathiraju, S. N. & Mattei, J. (2022). Environmental Impact of Animal-Based Food 

Production and the Feasibility of a Shift Toward Sustainable Plant-Based Diets in the United 

States. Frontiers in Sustainability, 3, Artículo 841106. 

https://www.frontiersin.org/journals/sustainability/articles/10.3389/frsus.2022.841106 

Espinosa-Salas, S. & Gonzalez-Arias, M. (2023). Nutrition: micronutrient intake, imbalances, and 

interventions. En StatPearls [Internet]. StatPearls Publishing. 

Geiker, N. R. W., Bertram, H. C., Mejborn, H., Dragsted, L. O., Kristensen, L., Carrascal, J. R., Bügel, S. 

& Astrup, A. (2021). Meat and Human Health-Current Knowledge and Research Gaps. Foods, 

10(7). https://doi.org/10.3390/foods10071556 

Giacalone, D., Clausen, M. P. & Jaeger, S. R. (2022). Understanding barriers to consumption of plant-

based foods and beverages: insights from sensory and consumer science. Current Opinion in 

Food Science, 48, Artículo 100919. https://doi.org/10.1016/j.cofs.2022.100919 

Hampton, J. O., Hyndman, T. H., Allen, B. L. & Fischer, B. (2021). Animal Harms and Food Production: 

Informing Ethical Choices. Animals, 11(5), Artículo 1225. 

https://doi.org/10.3390/ani11051225 

Hong, S., Shen, Y. & Li, Y. (2022). Physicochemical and Functional Properties of Texturized Vegetable 

Proteins and Cooked Patty Textures: Comprehensive Characterization and Correlation 

Analysis. Foods, 11(17). https://doi.org/10.3390/foods11172619 

Imchen, T. & Singh, K. S. (2023). Marine algae colorants: Antioxidant, anti-diabetic properties and 

applications in food industry. Algal Research, 69, 102898. 

https://doi.org/10.1016/j.algal.2022.102898 

Jarpa-Parra, M. (2018). Lentil protein: a review of functional properties and food application. An 

overview of lentil protein functionality. International Journal of Food Science and Technology, 

53(4), 892–903. https://doi.org/10.1111/ijfs.13685 

Joardder, M. U. H., Mourshed, M [M.] & Hasan M., M. (2019). Water in Foods. En M. U. Joardder, M. 

Mourshed y M. Hasan Masud (Eds.), State of Bound Water: Measurement and Significance in 

Food Processing (pp. 7–27). Springer International Publishing. https://doi.org/10.1007/978-3-

319-99888-6_2 

Kyriakopoulou, K., Keppler, J. K. & van der Goot, A. J. (2021). Functionality of Ingredients and Additives 

in Plant-Based Meat Analogues. Foods, 10(3), Artículo 600. 

https://doi.org/10.3390/foods10030600 

Li, K., McKeith, A. G., Shen, C. & McKeith, R. (2017). A Comparison Study of Quality Attributes of 

Ground Beef and Veal Patties and Thermal Inactivation of Escherichia coli O157:H7 after 

Double Pan-Broiling Under Dynamic Conditions. Foods, 7(1). 

https://doi.org/10.3390/foods7010001 



38 

 

 

Lyu, J. S., Lee, J., Chae, T. Y., Yoon, C. S. & Han, J. (2023). Effect of screw speed and die temperature 

on physicochemical, textural, and morphological properties of soy protein isolate-based 

textured vegetable protein produced via a low-moisture extrusion. Food Science and 

Biotechnology, 32(5), 659–669. https://doi.org/10.1007/s10068-022-01207-8 

McClements, D. J. & Grossmann, L. (2022). Physicochemical and Sensory Properties of Plant-Based 

Foods. En D. J. McClements y L. Grossmann (Eds.), Next-Generation Plant-based Foods: 

Design, Production, and Properties (pp. 155–226). Springer International Publishing. 

https://doi.org/10.1007/978-3-030-96764-2_4 

Nelson, M. E., Hamm, M. W., Hu, F. B., Abrams, S. A. & Griffin, T. S. (2016). Alignment of Healthy 

Dietary Patterns and Environmental Sustainability: A Systematic Review. Advances in 

Nutrition, 7(6), 1005–1025. https://doi.org/10.3945/an.116.012567 

Nolden, A. A. & Forde, C. G. (2023). The Nutritional Quality of Plant-Based Foods. Sustainability, 15(4), 

Artículo 3324. https://doi.org/10.3390/su15043324 

Ohr, L. M. (2020). Plant-Based Protein Market Grows Stronger. Food Technology Magazine, 74(10). 

https://www.ift.org/news-and-publications/food-technology-

magazine/issues/2020/october/columns/nutraceuticals-plant-based-protein-market-grows-

stronger 

Pang, B., Bowker, B., Zhuang, H., Yang, Y. & Zhang, J. (2020). Research Note: Comparison of 3 methods 

used for estimating cook loss in broiler breast meat. Poultry Science, 99(11), 6287–6290. 

https://doi.org/10.1016/j.psj.2020.08.038 

Parthasarathi, S. & Anandharamakrishnan, C. (2014). Modeling of Shrinkage, Rehydration and 

Textural Changes for Food Structural Analysis: A Review. Journal of Food Process Engineering, 

37(2), 199–210. https://doi.org/10.1111/jfpe.12073 

Peleg, M. (2019). The instrumental texture profile analysis revisited. Journal of Texture Studies, 50(5), 

362–368. https://doi.org/10.1111/jtxs.12392 

Peña-Jorquera, H., Cid-Jofré, V., Landaeta-Díaz, L., Petermann-Rocha, F., Martorell, M., Zbinden-

Foncea, H., Ferrari, G., Jorquera-Aguilera, C. & Cristi-Montero, C. (2023). Plant-Based 

Nutrition: Exploring Health Benefits for Atherosclerosis, Chronic Diseases, and Metabolic 

Syndrome—A Comprehensive Review. Nutrients, 15(14). 

https://doi.org/10.3390/nu15143244 

Plant Based Foods Association (2022). Retail Sales Data. https://plantbasedfoods.org/2022-retail-

sales-data-plant-based-food 

Rajaretnam, S. & Malik, N. (2023). Physical and Sensory Properties of Vegetarian Burger Patty. 

Enhanced Knowledge in Sciences and Technology, 3(2), 422–431. 

https://penerbit.uthm.edu.my/periodicals/index.php/ekst/article/view/10698 

Riaz, M. N. (2001). Textured soy protein and its uses. Agro Food Industry Hi Tech, 12(5), 28–31. 

Rysová, J. & Šmídová, Z. (2021). Effect of Salt Content Reduction on Food Processing Technology. 

Foods, 10(9). https://doi.org/10.3390/foods10092237 

Samard, S., Maung, T.‑T., Gu, B.‑Y., Kim, M.‑H. & Ryu, G.‑H. (2021). Influences of extrusion parameters 

on physicochemical properties of textured vegetable proteins and its meatless burger patty. 



39 

 

 

Food Science and Biotechnology, 30(3), 395–403. https://doi.org/10.1007/s10068-021-00879-

y 

Samard, S. & Ryu, G.‑H. (2019). Physicochemical and functional characteristics of plant protein-based 

meat analogs. Journal of Food Processing and Preservation, 43(10), e14123. 

https://doi.org/10.1111/jfpp.14123 

Sha, L. & Xiong, Y. L. (2020). Plant protein-based alternatives of reconstructed meat: Science, 

technology, and challenges. Trends in Food Science & Technology, 102, 51–61. 

https://doi.org/10.1016/j.tifs.2020.05.022 

Syamaladevi, R. M., Tang, J., Villa-Rojas, R., Sablani, S., Carter, B. & Campbell, G. (2016). Influence of 

Water Activity on Thermal Resistance of Microorganisms in Low-Moisture Foods: A Review. 

Comprehensive Reviews in Food Science and Food Safety, 15(2), 353–370. 

https://doi.org/10.1111/1541-4337.12190 

Szczesniak, A. S. (2002). Texture is a sensory property. Food Quality and Preference, 13(4), 215–225. 

https://doi.org/10.1016/S0950-3293(01)00039-8 

Thompson, A. S., Tresserra-Rimbau, A., Karavasiloglou, N., Jennings, A., Cantwell, M., Hill, C., Perez-

Cornago, A., Bondonno, N. P., Murphy, N., Rohrmann, S., Cassidy, A. & Kühn, T. (2023). 

Association of Healthful Plant-based Diet Adherence With Risk of Mortality and Major Chronic 

Diseases Among Adults in the UK. JAMA Network Open, 6(3), Artículo e234714. 

https://doi.org/10.1001/jamanetworkopen.2023.4714 

Thrane, M., Paulsen, P. V., Orcutt, M. W. & Krieger, T. M. (2017). Chapter 2 - Soy Protein: Impacts, 

Production, and Applications. En S. R. Nadathur, J. P. D. Wanasundara y L. & Scanlin (Eds.), 

Sustainable Protein Sources (pp. 23–45). Academic Press. https://doi.org/10.1016/B978-0-12-

802778-3.00002-0 

Tornberg, E. (2005). Effects of heat on meat proteins – Implications on structure and quality of meat 

products. Meat Science, 70(3), 493–508. https://doi.org/10.1016/j.meatsci.2004.11.021 

U.S Food & Drug Administration (2014). Water Activity (aw) in Foods. 

https://www.fda.gov/inspections-compliance-enforcement-and-criminal-

investigations/inspection-technical-guides/water-activity-aw-foods 

United States Department of Agriculture (2020). Safe Minimum Internal Temperature Chart. 

https://www.fsis.usda.gov/food-safety/safe-food-handling-and-preparation/food-safety-

basics/safe-temperature-chart 

van Vliet, S., Kronberg, S. L. & Provenza, F. D. (2020). Plant-Based Meats, Human Health, and Climate 

Change. Frontiers in Sustainable Food Systems, 4, Artículo 128. 

https://www.frontiersin.org/journals/sustainable-food-

systems/articles/10.3389/fsufs.2020.00128 

Vaskoska, R., Ha, M., Naqvi, Z. B., White, J. D. & Warner, R. D. (2020). Muscle, Ageing and 

Temperature Influence the Changes in Texture, Cooking Loss and Shrinkage of Cooked Beef. 

Foods, 9(9). https://doi.org/10.3390/foods9091289 

Vu, G., Zhou, H. & McClements, D. J. (2022). Impact of cooking method on properties of beef and 

plant-based burgers: Appearance, texture, thermal properties, and shrinkage. Journal of 

Agriculture and Food Research, 9, 100355. https://doi.org/10.1016/j.jafr.2022.100355 



40 

 

 

Wang, Y., Lyu, B., Fu, H., Li, J., Ji, L., Gong, H., Zhang, R., Liu, J. & Yu, H. (2023). The development 

process of plant-based meat alternatives: Raw material formulations and processing 

strategies. Food Research International, 167, Artículo 112689. 

https://doi.org/10.1016/j.foodres.2023.112689 

Wrolstad, R. E. & Smith, D. E. (2017). Color Analysis. En S. S. Nielsen (Ed.), Food Analysis (pp. 545–555). 

Springer International Publishing. https://doi.org/10.1007/978-3-319-45776-5_31 

Wu, G. (2016). Dietary protein intake and human health. Food & Function, 7(3), 1251–1265. 

Wunsch, N. G. (2024). Plant-based milk and dairy alternatives worldwide - statistics & facts. Statista. 

https://www.statista.com/topics/12897/plant-based-milk-and-dairy-alternatives-

worldwide/#topicOverview 

Yu, T.‑Y., Morton, J. D., Clerens, S. & Dyer, J. M. (2017). Cooking-Induced Protein Modifications in 

Meat. Comprehensive Reviews in Food Science and Food Safety, 16(1), 141–159. 

https://doi.org/10.1111/1541-4337.12243 

Zielbauer, B. I., Franz, J., Viezens, B. & Vilgis, T. A. (2016). Physical Aspects of Meat Cooking: Time 

Dependent Thermal Protein Denaturation and Water Loss. Food Biophysics, 11(1), 34–42. 

https://doi.org/10.1007/s11483-015-9410-7 

 



41 

 

 

Appendices 

Appendices A 

Correlation analysis