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Current Practice and Future Directions of Application of Puffed/Extruded Technologies...
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Current Practice and Future Directions of Application of Puffed/Extruded Technologies in Food (Volume II)

A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Food Engineering and Technology".

Deadline for manuscript submissions: closed (30 June 2024) | Viewed by 7135

Special Issue Editors

Dr. Min Wu

E-Mail Website
Guest Editor
Department of Engineering, China Agricultural University, Beijing, China
Interests: extrusion process; puffing; grains; drying; food extrusion technology; numerical simulation
Special Issues, Collections and Topics in MDPI journals
Dr. Lijun Wang

E-Mail Website
Guest Editor
College of Food Science & Nutritional Engineering, China Agricultural University, Beijing, China
Interests: rheological properties and interaction of protein; polysaccharide; starch and cellulose in food
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The development of new food products via extrusion processing has advanced and increased in scope over recent years. As a highly versatile, productive, low-cost, and low energy cost mechanical process, extrusion encompasses the multiple unit operations needed to produce a wide variety of food products, such as ready-to-eat foods, and enhance the nutritional quality in the food industry. These methods include mixing, shearing, plasticizing, melting, cooking, denaturation, fragmentation, and texturization to produce a wide variety of food products.

The physical and chemical property changes induced to the material involve complex changes in the food matrix, phytochemical composition and organoleptic properties, such as texture, colour and flavour, due to the influence of high temperature, high pressure, and high shear pressure during the extrusion process.  These changes are related to extrusion parameters, such as processing temperature, processing speed, and feed moisture, and to the characteristics of the raw materials. This Special Issue aims to focus on the variation in extrusion puffing and texturizing technologies which improve the nutritional, functional and acceptability of food, as well as on the effects and effectiveness of pre-treatment methods and numerical simulation.

Dr. Min Wu
Dr. Lijun Wang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Foods is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2900 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • extrusion
  • puffing
  • extrusion texture
  • extrusion parameters
  • low/high moisture extrusion
  • single-screw/twin-screw extruder
  • numerical simulation
  • functional properties
  • physicochemical and structural properties
  • rheology property

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Published Papers (4 papers)

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Research

14 pages, 3801 KiB  
Article
The Effects of Adding Extruded Highland Barley Flour on the Thermomechanical Properties of Wheat Flour Dough and the Overall Quality of Fresh Wet Noodles
by Yiqing Zhu, Xuecong Wang, Xinyu Zhang, Yan Du, Feng Liang, Fan Zhang, Chongyi Wu, Qingyu Zhao and Qun Shen
Foods 2024, 13(19), 3105; https://doi.org/10.3390/foods13193105 - 28 Sep 2024
Viewed by 992
Abstract
This study examined how adding extruded highland barley flour (EHBF) affects the thermomechanical properties of wheat flour dough and the overall quality of fresh wet noodles. EHBF increased the gel strength and pasting temperature of wheat flour compared to regular highland barley flour. [...] Read more.
This study examined how adding extruded highland barley flour (EHBF) affects the thermomechanical properties of wheat flour dough and the overall quality of fresh wet noodles. EHBF increased the gel strength and pasting temperature of wheat flour compared to regular highland barley flour. Moreover, higher EHBF levels reduced dough development time and stability time. EHBF improved the color and springiness of fresh wet noodles and decreased their cooking time and light transmittance relative to the color and springiness of the noodles in the control group. Notably, noodles with 20% EHBF showed a compact microstructure and received the highest sensory evaluation score. Adding EHBF lowered the estimated glycemic index of fresh wet noodles by reducing rapidly digestible starch and increasing slowly digestible starch and resistant starch contents. Thus, EHBF is a promising functional ingredient for enhancing the quality of fresh wet noodles. Full article
(This article belongs to the Special Issue Current Practice and Future Directions of Application of Puffed/Extruded Technologies in Food (Volume II))
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17 pages, 2390 KiB  
Article
Nitrogen Gas-Assisted Extrusion for Improving the Physical Quality of Pea Protein-Enriched Corn Puffs with a Wide Range of Protein Contents
by Siwen Luo, Jitendra Paliwal and Filiz Koksel
Foods 2024, 13(15), 2411; https://doi.org/10.3390/foods13152411 - 30 Jul 2024
Cited by 1 | Viewed by 1465
Abstract
Blowing agent-assisted extrusion cooking is a novel processing technique that can alter the expansion of extruded snacks and, thus, enhance their physical appeal, such as texture. However, to this day, this technique has only been studied for ingredients with limited protein contents (<30%). [...] Read more.
Blowing agent-assisted extrusion cooking is a novel processing technique that can alter the expansion of extruded snacks and, thus, enhance their physical appeal, such as texture. However, to this day, this technique has only been studied for ingredients with limited protein contents (<30%). In this study, protein-enriched snacks were extruded using nitrogen gas as a blowing agent at a wide protein range (0–50%) to better explore the potential of this technique in manufacturing high-protein snacks. The results showed that, with nitrogen gas injection, extrudate radial expansion was significantly (p < 0.05) improved at 10% and 40% protein, while extrudate density was significantly reduced at 30% and 50% protein. Nitrogen gas-injected extrudates, especially at 50% protein, exhibited improvements in texture, including a reduction in hardness and an increase in crispness. Collectively, this study showed the promising potential of nitrogen gas-assisted extrusion in improving the physical appeal of innovative healthy snacks at a high protein level (i.e., 50%). Full article
(This article belongs to the Special Issue Current Practice and Future Directions of Application of Puffed/Extruded Technologies in Food (Volume II))
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Graphical abstract

16 pages, 4707 KiB  
Article
Synergistic Effects and Kinetic Analysis in Co-Pyrolysis of Peanut Shells and Polypropylene
by Zhigang Huang, Jiahui Wu, Tenglun Yang, Zihan Wang, Tong Zhang, Fei Gao, Li Yang and Gang Li
Foods 2024, 13(8), 1191; https://doi.org/10.3390/foods13081191 - 13 Apr 2024
Cited by 1 | Viewed by 2089
Abstract
The impact of COVID-19 has boosted growth in the takeaway and medical industries but has also generated a large amount of plastic waste. Peanut shells (PS) are produced in large quantities and are challenging to recycle in China. Co-pyrolysis of peanut shells (PS) [...] Read more.
The impact of COVID-19 has boosted growth in the takeaway and medical industries but has also generated a large amount of plastic waste. Peanut shells (PS) are produced in large quantities and are challenging to recycle in China. Co-pyrolysis of peanut shells (PS) and polypropylene (PP) is an effective method for processing plastic waste and energy mitigation. Thermogravimetric analysis was conducted on PS, PP, and their blends (PS-PP) at different heating rates (10, 20, 30 °C·min−1). The results illustrated that the co-pyrolysis process of PS-PP was divided into two distinct decomposition stages. The first stage (170–400 °C) was predominantly linked to PS decomposition. The second stage (400–520 °C) resulted from the combinations of PS and PP’s thermal degradations, with the most contribution from PP degradation. With the increase in heating rate, thermogravimetric hysteresis appeared. Kinetic analysis indicated that the co-pyrolysis process reduced the individual pyrolysis activation energy, especially in the second stage, with a correlation coefficient (R2) generally maintained above 0.95. The multi-level reaction mechanism function model can effectively reveal the co-pyrolysis process mechanism. PS proved to be high-quality biomass for co-pyrolysis with PP, and all mixtures exhibited synergistic effects at a mixing ratio of 1:1 (PS1-PP1). This study accomplished effective waste utilization and optimized energy consumption. It holds significance in determining the interaction mechanism of mixed samples in the co-pyrolysis process. Full article
(This article belongs to the Special Issue Current Practice and Future Directions of Application of Puffed/Extruded Technologies in Food (Volume II))
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22 pages, 11175 KiB  
Article
Study on the Residence Time and Texture Prediction of Pea Protein Extrusion Based on Image Analysis
by Qi Wu, Xun Zhang, Fei Gao and Min Wu
Foods 2023, 12(24), 4408; https://doi.org/10.3390/foods12244408 - 7 Dec 2023
Cited by 5 | Viewed by 1632
Abstract
This paper initially involves three main processing parameters: screw speed, feeding speed, and initial material moisture content, exploring the RTD of materials inside the extruder barrel under varying parameters and clarifying the impact of parameter variations on RTD. Finally, machine vision technology was [...] Read more.
This paper initially involves three main processing parameters: screw speed, feeding speed, and initial material moisture content, exploring the RTD of materials inside the extruder barrel under varying parameters and clarifying the impact of parameter variations on RTD. Finally, machine vision technology was utilized to link extruded product images to texture features, and a texture prediction model based on image features was established using a Back Propagation (BP) neural network. Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) were applied to optimize the BP neural network. The results indicate that the feeding speed has a stronger impact than the screw speed on the extrusion process, and an increase in the initial material moisture content tends to shorten the RTD. Specifically, an increase in screw speed results in a denser product structure, while higher feeding speeds lead to reduced pore size in the microstructure. As the initial material moisture content increased from 55% to 70%, the average residence time MRT decreased from 265.21 s to 166.62 s. Additionally, elevated moisture content causes a more porous microstructure. After optimizing the texture prediction model of extruded products through the application of Particle Swarm Optimization and Genetic Algorithm models, it was discovered that the Genetic Algorithm was more effective in reducing errors (p < 0.05) than the Particle Swarm Optimization algorithm. It was found that the Particle Swarm Optimization model exhibited better prediction performance. The results of the prediction indicated a significant association between the image features of the product and hardness, resilience, and chewiness, as corroborated by correlation coefficients of 0.93913, 0.94040, and 0.94724, respectively. Full article
(This article belongs to the Special Issue Current Practice and Future Directions of Application of Puffed/Extruded Technologies in Food (Volume II))
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