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Forster RA, Hassall E, Hoffman LC, Baier SK, Stokes JR, Smyth HE. Comparing the sensory properties of commercially available animal and plant-based burgers. J Texture Stud 2024; 55:e12838. [PMID: 38816187 DOI: 10.1111/jtxs.12838] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2023] [Revised: 05/06/2024] [Accepted: 05/09/2024] [Indexed: 06/01/2024]
Abstract
The number of plant-based meat products on supermarket shelves around the world has grown in recent years however reproducing the sensory experience of eating meat remains a challenge. This study aims to evaluate the sensory gaps between animal and plant-based meat products, specifically burger-type products, from the Australian market. The sample set of 19 commercially available burgers comprises 8 animal-based burgers prepared using beef, chicken, kangaroo, pork, or turkey and 11 high protein plant-based burgers. Vegetable patties are beyond the scope of this study. A trained sensory panel (n = 14) determined the major differences in aroma, texture, flavor, and aftertaste between meat and meat analogues during oral processing, particularly those that may impact consumer acceptability. The animal-based burgers scored high for meaty (aroma), meaty (flavor), and umami but not legume, vegetative, bitterness, and lingering spice attributes. They also received higher average scores for juiciness, fattiness, and final moistness than the plant-based burgers but scored lower in cohesiveness. The plant-based burgers scored high for legume and bitterness but not meaty (aroma), meaty (flavor), and umami attributes. Improving current products and designing new products with desirable sensory properties will enhance consumer acceptability and reinforce recent growth in the plant-based meats market.
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Affiliation(s)
- Rebecca A Forster
- School of Chemical Engineering, The University of Queensland, St Lucia, Queensland, Australia
| | - Emma Hassall
- Centre for Nutrition and Food Sciences, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Indooroopilly, Queensland, Australia
| | - Louwrens C Hoffman
- Centre for Nutrition and Food Sciences, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Indooroopilly, Queensland, Australia
| | | | - Jason R Stokes
- School of Chemical Engineering, The University of Queensland, St Lucia, Queensland, Australia
| | - Heather E Smyth
- Centre for Nutrition and Food Sciences, Queensland Alliance for Agriculture and Food Innovation, The University of Queensland, Indooroopilly, Queensland, Australia
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Canoy TS, Wiedenbein ES, Bredie WLP, Meyer AS, Wösten HAB, Nielsen DS. Solid-State Fermented Plant Foods as New Protein Sources. Annu Rev Food Sci Technol 2024; 15:189-210. [PMID: 38109492 DOI: 10.1146/annurev-food-060721-013526] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2023]
Abstract
The current animal-based production of protein-rich foods is unsustainable, especially in light of continued population growth. New alternative proteinaceous foods are therefore required. Solid-state fermented plant foods from Africa and Asia include several mold- and Bacillus-fermented foods such as tempeh, sufu, and natto. These fermentations improve the protein digestibility of the plant food materials while also creating unique textures, flavors, and taste sensations. Understanding the nature of these transformations is of crucial interest to inspire the development of new plant-protein foods. In this review, we describe the conversions taking place in the plant food matrix as a result of these solid-state fermentations. We also summarize how these (nonlactic) plant food fermentations can lead to desirable flavor properties, such as kokumi and umami sensations, and improve the protein quality by removing antinutritional factors and producing additional essential amino acids in these foods.
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Affiliation(s)
- Tessa S Canoy
- Department of Food Science, University of Copenhagen, Frederiksberg, Denmark; ,
| | | | - Wender L P Bredie
- Department of Food Science, University of Copenhagen, Frederiksberg, Denmark; ,
| | - Anne S Meyer
- Department of Biotechnology and Biomedicine, Technical University of Denmark, Lyngby, Denmark
| | - Han A B Wösten
- Microbiology, Department of Biology, Utrecht University, Utrecht, The Netherlands
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Oppen D, Attig T, Weiss J, Krupitzer C. Anticipating food structure of meat products from mastication physics applying machine learning. Food Res Int 2023; 174:113576. [PMID: 37986524 DOI: 10.1016/j.foodres.2023.113576] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2023] [Revised: 10/04/2023] [Accepted: 10/09/2023] [Indexed: 11/22/2023]
Abstract
Alternatives to animal-based products are becoming more relevant. Most of those products rely at some stage on a structuring process; hence researchers are developing techniques to measure the goodness of the structured material. Conventionally, a typical sensory study or texture analysis by measuring deformation forces would be applied to test the produced material for its texture. However, meat alternatives and meat differ in more points than just the texture, making it hard to extract the isolated texture impression. To objectively obtain qualitative and quantitative differences between different food structures, evaluation of oral processing features is an upcoming technology which qualifies as promising addon to existing technologies. The kinematic data of the jaw and exerted forces regarding muscle activities are recorded during mastication. Resulting datasets are high in dimensionality, covering thousands of individual chews described by often more than ten features. Evaluating such a dataset could benefit from applying computational evaluation strategies designed for large datasets, such as machine learning and neural networks. The aim of this work was to assess the performance of machine learning algorithms such as Support Vector Machines and Artificial Neural Networks or ensemble learning algorithms like Extra Trees Classifier or Extreme Gradient Boosting. We evaluated different pre-processing techniques and various machine algorithms for learning models with regard to their performance measured with established benchmark values (Accuracy, Area under Receiver-Operating Curve score, F1 score, precision-recall Curve, Matthews Correlation Coefficient (MCC)). Results show remarkable performance of classification of each single chew between isotropic and anisotropic material (MCC up to 0.966). According to the feature importance, the lateral jaw movement was the most important feature for classification; however, all features were necessary for an optimal learning process.
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Affiliation(s)
- Dominic Oppen
- Department of Food Material Science, Institute of Food Science and Biotechnology, University of Hohenheim, Garbenstraße 25, 70599 Stuttgart, Germany
| | - Tabea Attig
- Department of Food Informatics, Institute of Food Science and Biotechnology, and Computational Science Hub, University of Hohenheim, Fruwirthstraße 21, 70599 Stuttgart, Germany
| | - Jochen Weiss
- Department of Food Material Science, Institute of Food Science and Biotechnology, University of Hohenheim, Garbenstraße 25, 70599 Stuttgart, Germany.
| | - Christian Krupitzer
- Department of Food Informatics, Institute of Food Science and Biotechnology, and Computational Science Hub, University of Hohenheim, Fruwirthstraße 21, 70599 Stuttgart, Germany.
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Oppen D, Weiss J. Oral processing, rheology, and mechanical response: Relations in a two-phase food model with anisotropic compounds. J Texture Stud 2023; 54:808-823. [PMID: 37718549 DOI: 10.1111/jtxs.12799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 08/15/2023] [Accepted: 08/30/2023] [Indexed: 09/19/2023]
Abstract
Food-material poses a challenging matrix for objective material scientific description that matches the consumers' perception. With eyes on the emerging structured food materials from alternative protein sources, objectively describing perceived texture characteristics became a topic of interest to the food industry. This work made use of the well-known methodologies of jaw tracking and electromyography from the field of "food oral processing" and compared outcomes with mechanical responses to the deformation of model food systems to meat alternatives. To enable transferability to meat alternative products, an anisotropic structuring ingredient for alternative products, high-moisture texturized vegetable protein (HM-TVP), was embedded in an isotropic hydrocolloid gel. Data of the jaw movement and muscle activities exerted during mastication were modeled in a linear mixed model and set in relation to characteristic values obtained from small- and large-strain deformation. For improvement of the model fit, this work makes use of two new data-processing strategies in the field of oral processing: (i) Muscle activity data were set in relation to true forces and (ii) measured data were standardized and subjected to dimensional reduction. Based on that, model terms showed decreased p-values on various oral processing features. As a key outcome, it could be shown that an anisotropic structured phase induces more lateral jaw movement than isotropic samples, as was shown in meat model systems.
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Affiliation(s)
- Dominic Oppen
- Department of Food Material Science, Institute of Food Science and Biotechnology, University of Hohenheim, Stuttgart, Germany
| | - Jochen Weiss
- Department of Food Material Science, Institute of Food Science and Biotechnology, University of Hohenheim, Stuttgart, Germany
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Huang X, Zhao H, Guo R, Du F, Dong X, Qin L. The Interaction Relationship of Aroma Components Releasing with Saliva and Chewing Degree during Grilled Eels Consumption. Foods 2023; 12:foods12112127. [PMID: 37297372 DOI: 10.3390/foods12112127] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Revised: 05/19/2023] [Accepted: 05/23/2023] [Indexed: 06/12/2023] Open
Abstract
The interaction perception between aroma and oral chewing during food consumption has always been a hot topic in exploring consumers' preferences and purchase desires. A chewing simulation system was set to find out the effect of key saliva components and chewing time on odorants released with grilled eel meat. Odor release did not always enhance with the degree of chewing, or the amount of saliva released. The breaking up of the tissue structure of the fish meat by the teeth encourages the release of odorants and the participation of saliva partially blocks this process. The release of pyrazine, alcohol, and acid compounds in grilled eel meat peaked within 20-60 s after chewing. Sufficient exposure of saliva to grilled eel meat will inhibit aromatic, ketone, ester, hydrocarbon, and sulfur compounds release. 3-methyl-2-butanol contributed to the subtle aroma differences that arise before and after eating grilled eel meat. Naphthalene, 2-acetylthiazole, 2-decenal, 2-undecanone, 5-ethyldihydro-2(3H)-furanone were the main odorants released in large quantities in the early stages of eating grilled eel and affected the top note. Consequently, the results provided the odorants information in aroma perception during grilled eel consumption and benefited the objective evaluation of grilled eel product optimization.
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Affiliation(s)
- Xuhui Huang
- School of Food Science and Technology, National Engineering Research Center of Seafood, Collaborative Innovation Center of Seafood Deep Processing, Dalian Polytechnic University, Dalian 116034, China
| | - Huilin Zhao
- School of Food Science and Technology, National Engineering Research Center of Seafood, Collaborative Innovation Center of Seafood Deep Processing, Dalian Polytechnic University, Dalian 116034, China
| | - Renrong Guo
- School of Food Science and Technology, National Engineering Research Center of Seafood, Collaborative Innovation Center of Seafood Deep Processing, Dalian Polytechnic University, Dalian 116034, China
| | - Fei Du
- School of Food Science and Technology, National Engineering Research Center of Seafood, Collaborative Innovation Center of Seafood Deep Processing, Dalian Polytechnic University, Dalian 116034, China
| | - Xiuping Dong
- School of Food Science and Technology, National Engineering Research Center of Seafood, Collaborative Innovation Center of Seafood Deep Processing, Dalian Polytechnic University, Dalian 116034, China
| | - Lei Qin
- School of Food Science and Technology, National Engineering Research Center of Seafood, Collaborative Innovation Center of Seafood Deep Processing, Dalian Polytechnic University, Dalian 116034, China
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Ilic J, Djekic I, Tomasevic I, van den Berg M, Oosterlinck F. Beef and plant-based burgers' mastication parameters depend on texture rather than on serving conditions. J Texture Stud 2023. [PMID: 37114586 DOI: 10.1111/jtxs.12763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2022] [Revised: 03/13/2023] [Accepted: 04/10/2023] [Indexed: 04/29/2023]
Abstract
Previous studies dealing with plant-based meat analogs confirmed the potential of oral processing methods to identify options for improving those products. Knowing that sensory perception can be influenced by adding condiments, this short communication aimed to investigate the texture and oral processing of four plant-based burger analogs and a beef burger when consumed in portions or as part of model meals with buns and sides. Texture profile analysis indicated that beef burgers and analog E were the toughest. Two analogs (B and S) showed textures close to beef, while one (analog D) displayed significantly lower values for hardness, toughness, cohesiveness, and springiness. The instrumental data was only partly reflected in the mastication parameters. Adaptations in mastication behavior were expected, but differences between the plant-based analogs were smaller than anticipated, although clear differences were observed for consumption time, number of chews and number of swallows. On the whole, mastication patterns concurred within different consumption scenarios (portions, model burgers), and significant correlations with instrumental texture were obtained.
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Affiliation(s)
- Jovan Ilic
- Department of Food Safety and Quality Management, Faculty of Agriculture, Institute of Food Technology and Biochemistry, University of Belgrade, Belgrade, Serbia
| | - Ilija Djekic
- Department of Food Safety and Quality Management, Faculty of Agriculture, Institute of Food Technology and Biochemistry, University of Belgrade, Belgrade, Serbia
| | - Igor Tomasevic
- German Institute of Food Technologies (DIL), Quakenbrück, Germany
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Younis K, Ashfaq A, Ahmad A, Anjum Z, Yousuf O. A Critical review focusing the effect of ingredients on the textural properties of plant-based meat products. J Texture Stud 2022. [PMID: 35717605 DOI: 10.1111/jtxs.12704] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2022] [Revised: 05/18/2022] [Accepted: 06/09/2022] [Indexed: 11/29/2022]
Abstract
Plant-based meat alternatives have been studied for decades, but have recently gained more attraction in the food industries and research communities. Concern about animal welfare, health, environment and moral beliefs acts as a driving force for the growth of plant-based meat products. The most challenging task in the development of meat analog is to imitate the texture of conventional meat products. The fabrication of plant-based meat product requires a wise selection and formulation of ingredients to perfectly mimic the fibrous structure of meat. Top-down and bottom-up approaches are the two most commonly used structuring techniques for the preparation of plant-based meat products. Development of comminuted meat product is easy as compared to the whole-muscle type plant-based meat products. Several plant-based ingredients such as texturized and non-texturized proteins, fats, binding agents, flavoring and coloring agents accompanied with different processing techniques (extrusion, shear cell, wet spinning, electrospinning, and freeze structuring) are used in the preparation of meat analogs. This paper aims to discuss the impact of ingredients on the textural properties of plant-based meat products.
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Affiliation(s)
- Kaiser Younis
- Department of Bioengineering, Integral University, Lucknow, U.P., India
| | - Alweera Ashfaq
- Department of Bioengineering, Integral University, Lucknow, U.P., India
| | - Alisha Ahmad
- Department of Bioengineering, Integral University, Lucknow, U.P., India
| | - Zayeema Anjum
- Department of Bioengineering, Integral University, Lucknow, U.P., India
| | - Owais Yousuf
- Department of Bioengineering, Integral University, Lucknow, U.P., India
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