Food Oral Processing-An Industry Perspective

Effects of the extrusion conditions, the addition of oil and the food matrix on the physical and sensory characteristics of pre-extrusion flavored products

Thermoplastic extrusion is important in processing a wide variety of food products. In this paper, the effects of different extrusion conditions, addition of vegetable oil and the food matrix itself on the physical and sensory characteristics of corn snacks and meat analogs were evaluated. Cysteine and butyric acid (cheese aroma precursors) and thiamine (a meat aroma precursor) were added to corn grits and soy protein concentrate, respectively, before extrusion. For each matrix, three combinations of moistures of the raw material and extrusion temperatures were used and, after extrusion, vegetable oil was added to one portion of each product and not to another one. The extrusion conditions and the addition of oil affected the physical properties and sensory characteristics of corn snacks more while they had less influence on the properties of the meat analogs. There were similar correlations between the physical and sensory variables, independent of the food matrix used. The sensory acceptance stood out for samples from intermediate and less severe extrusion conditions and with added oil, showing that these factors have an impact on the physical properties and sensory characteristics, with little effect from the food matrix.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13197-024-05985-3.

Potential of 3D printing in development of foods for special medical purpose: A review

Nutritional management has emerged as an effective strategy to mitigate the risks of malnutrition and disease-related mortality among patients. The emergence of novel food types, particularly foods for special medical purposes (FSMPs), has garnered increasing attention from researchers and businesses. 3D printing (3DP) technology, alternatively known as food additive manufacturing, has gained popularity among novel food developers due to its distinct capabilities in tailoring nutrition, appearance, texture, and enhancing overall edible quality. This review examines current market trends, product forms, and unique characteristics of FSMPs, highlighting the progress made in applying 3DP to the development of functional foods and drugs. Despite its potential medical benefits, there are limited instances of direct utilization of 3DP in the production of such specialized food type. Currently, the FSMP market faces several challenges, including limited product diversity, inadequate formula design, and a lack of product appeal. 3DP offers significant advantages in catering to the unique needs of special patients, encompassing both physiological medical benefits and enhanced sensory as well as psychological eating experiences. It holds great promise in promoting precision medicine and personalized home-based FSMPs preparations. This review will delve into the development strategies and feasibility of 3DP in creating specialized medical food for patients with unique conditions and across different age groups. Additionally, it explores the potential challenges of applying 3DP to the FSMP sector, such as regulatory frameworks, patient acceptance, cost of 3D-printed FSMPs, and the improvement of 3DP.

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.

Fibrous food and particle size influence electromyography and the kinematics of oral processing

Structure-sensory relationships are essential for understanding food perception. Food microstructure impacts how a food is comminuted and processed by the human masticatory system. This study investigated the impact of anisotropic structures, explicitly the structure of meat fibers, on the dynamic process of mastication. For a general understanding of texture-structure relationships, the three typically used deformation-tests: Kramer shear cell-, Guillotine cutting- and texture-profile-analyses were conducted. 3D jaw movements and muscle activities of the masseter muscle were additionally tracked and visualized using a mathematical model. Particle size had a significant effect on jaw movements and muscle activities for both the homogeneous (isotropic) and fibrous (anisotropic) meat-based samples with the same composition. Mastication was described using jaw movement and muscle activity parameters determined for each individual chew. The adjusted effect of fiber length was extracted from the data, suggesting that longer fibers induce a more strenuous chewing in which the jaw undergoes faster and wider movements requiring more muscle activity. To the authors' knowledge, this paper presents a novel data analysis approach for identifying oral processing behavior differences. This is an advancement on previous studies because a holistic overview of the entire mastication process can be visualized.

Computer-aided food engineering

Computer-aided food engineering (CAFE) can reduce resource use in product, process and equipment development, improve time-to-market performance, and drive high-level innovation in food safety and quality. Yet, CAFE is challenged by the complexity and variability of food composition and structure, by the transformations food undergoes during processing and the limited availability of comprehensive mechanistic frameworks describing those transformations. Here we introduce frameworks to model food processes and predict physiochemical properties that will accelerate CAFE. We review how investments in open access, such as code sharing, and capacity-building through specialized courses could facilitate the use of CAFE in the transformation already underway in digital food systems.

Food systems at a watershed: Unlocking the benefits of technology and ecosystem symbioses

The current food systems require change to improve sustainability resilience. Humans need food and food requires natural resources which have been consistently reduced, destroyed, or eliminated during human development, and excessive during the last 50-70 years. Though essential, there has been less of a focus on the inter-relations and inter-dependences of our food supply with and on the world's eco-system and organisms. Integrating evidence for the importance of plants, the microbiota in plants, animals and humans and their reciprocal effects of their interactions on food systems is essential for creating more inclusive strategies for future food systems. This review examines the role of plants, microorganisms, plant-microbial, animal-microbial, and human-microbial interactions, their co-evolution on the food supply and human and eco-systems well-being. It also recognizes the contribution of indigenous knowledge for lasting protection of the land, managing resources and biodiversity and the usefulness of food processing for producing safe, tasty, and nutritious food sustainably. We demonstrate that new targets and priorities for harnessing science and technology for improving food and nutritional security and avoiding environmental degradation and biodiversity loss are urgently needed. For improved long-term sustainability, the benefits of technology and ecosystem interactions must be unlocked.