Search citation statements
Paper Sections
Citation Types
Publication Types
Relationship
Authors
Journals
Extrusion‐based 3D printing technology has emerged as a promising method for developing soy protein‐based meat analogs, addressing the urgent demand for sustainable and nutritious alternatives to traditional meat sources. There is a growing global interest in soy protein‐based diets, driven by environmental sustainability, health, and animal welfare concerns. Extrusion‐based 3D printing involves pushing soy protein pastes through a nozzle to develop layers that build up into three‐dimensional objects and enable the production of structures closely mimicking the texture and appearance of real meat. Soy proteins, characterized by their high protein content and balanced amino acid profile, are ideal for producing meat‐like textures and flavors. This review explores the application of extrusion and 3D printing technologies in soy protein‐based meat analog production, emphasizing their potential to replicate the sensory qualities of animal meat. It discusses the advantages and challenges associated with these technologies, including the optimization of printing parameters for consistency and quality. Rheological studies are conducted to achieve smooth extrusion and proper layer formation whereas integrating fats, fibers, and natural flavors to enhance texture and taste. The review provides an overview of extrusion processes, highlighting rheological studies optimizing the flow behavior of soy protein pastes for effective 3D printing. Additionally, it examines textural studies aimed at mimicking the mouthfeel and bite of real meat, as well as printing performance evaluated through shape retention, layer resolution, structural strength, and printing accuracy. Consumer acceptance of soy protein‐based meat analogs is also discussed, highlighting the familiarity with soy products and the increasing demand for plant‐based alternatives. The review concludes by considering prospects for these technologies, focusing on innovations in extrusion and 3D printing, market trends, and evolving consumer preferences.
Extrusion‐based 3D printing technology has emerged as a promising method for developing soy protein‐based meat analogs, addressing the urgent demand for sustainable and nutritious alternatives to traditional meat sources. There is a growing global interest in soy protein‐based diets, driven by environmental sustainability, health, and animal welfare concerns. Extrusion‐based 3D printing involves pushing soy protein pastes through a nozzle to develop layers that build up into three‐dimensional objects and enable the production of structures closely mimicking the texture and appearance of real meat. Soy proteins, characterized by their high protein content and balanced amino acid profile, are ideal for producing meat‐like textures and flavors. This review explores the application of extrusion and 3D printing technologies in soy protein‐based meat analog production, emphasizing their potential to replicate the sensory qualities of animal meat. It discusses the advantages and challenges associated with these technologies, including the optimization of printing parameters for consistency and quality. Rheological studies are conducted to achieve smooth extrusion and proper layer formation whereas integrating fats, fibers, and natural flavors to enhance texture and taste. The review provides an overview of extrusion processes, highlighting rheological studies optimizing the flow behavior of soy protein pastes for effective 3D printing. Additionally, it examines textural studies aimed at mimicking the mouthfeel and bite of real meat, as well as printing performance evaluated through shape retention, layer resolution, structural strength, and printing accuracy. Consumer acceptance of soy protein‐based meat analogs is also discussed, highlighting the familiarity with soy products and the increasing demand for plant‐based alternatives. The review concludes by considering prospects for these technologies, focusing on innovations in extrusion and 3D printing, market trends, and evolving consumer preferences.
This study develops a mathematical model for soil moisture diffusion, addressing the inverse problem of determining both the diffusion coefficient and the variation coefficient in a nonlinear moisture transfer equation. The model incorporates specific boundary and initial conditions and utilizes experimentally measured moisture values at a boundary point as input data. An iterative method, based on an explicit gradient scheme, is introduced to estimate the soil parameters. The initial boundary value problem is discretized, leading to a difference analog and the formulation of a conjugate difference problem. Iterative formulas for calculating the unknown parameters are derived, with a priori estimates ensuring the convergence of the iterative process. Additionally, the research establishes the convergence of the numerical model itself, providing a rigorous foundation for the proposed approach. The study also emphasizes symmetry in moisture calculations, ensuring consistency regardless of the calculation direction (from right to left or left to right) and confirming that moisture distribution remains symmetric within specified intervals. This preservation of symmetry enhances the model’s robustness and accuracy in parameter estimation. The numerical simulations were successfully conducted over a 7-day period, demonstrating the model’s reliability. The discrepancy between the numerical predictions and experimental observations remained within the margin of measurement error, confirming the model’s accuracy.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.