Materials Properties, Oral Processing, and Sensory Analysis of Eating Meat and Meat Analogs

Anticipating food structure of meat products from mastication physics applying machine learning

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.

Oral processing, rheology, and mechanical response: Relations in a two-phase food model with anisotropic compounds

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.

The Interaction Relationship of Aroma Components Releasing with Saliva and Chewing Degree during Grilled Eels Consumption

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.

Beef and plant-based burgers' mastication parameters depend on texture rather than on serving conditions

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.

A Critical review focusing the effect of ingredients on the textural properties of plant-based meat products

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.