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Plant cell culture technology in the cosmetics and food industries: current state and future trends
The production of drugs, cosmetics, and food which are derived from plant cell and tissue cultures has a long tradition. The emerging trend of manufacturing cosmetics and food products in a natural and sustainable manner has brought a new wave in plant cell culture technology over the past 10 years. More than 50 products based on extracts from plant cell cultures have made their way into the cosmetics industry during this time, whereby the majority is produced with plant cell suspension cultures. In addition, the first plant cell culture-based food supplement ingredients, such as Echigena Plus and Teoside 10, are now produced at production scale. In this mini review, we discuss the reasons for and the characteristics as well as the challenges of plant cell culture-based productions for the cosmetics and food industries. It focuses on the current state of the art in this field. In addition, two examples of the latest developments in plant cell culture-based food production are presented, that is, superfood which boosts health and food that can be produced in the lab or at home.
Journal Article
Apparent digestibility coefficients of selected protein ingredients for juvenile Totoaba macdonaldi
Two feeding trials were performed to evaluate the apparent digestibility coefficients (ADCs) of dry matter, protein, and amino acids of three animal‐origin and four plant‐origin ingredients in Totoaba macdonaldi. In the first feeding trial, the animal‐origin ingredients were evaluated using totoaba juveniles with an initial weight of 529.7 ± 104.2 g, and for the second feeding trial 745.9 ± 210.6 g. Evaluated ingredients were: poultry by‐product meal, meat and bone meal, feather meal (FM), soy protein concentrate, soybean meal (SBM), corn gluten (CG), and wheat gluten (WG). Each experimental ingredient was evaluated in triplicate. ADCs of dry matter ranged from 35.9% for FM to 67.9% for poultry by‐product, while the protein ADCs values ranged from 41.7% for CG to 83.2% for poultry by‐product. Fish meal ADC (79.6%) was similar to poultry by‐product but significantly higher than WG and soy protein concentrate (72.5% and 72.6%, respectively). The ADCs for lysine were significantly higher for WG, sardine meal, poultry by‐product, and SMB (94.5%, 79.8%, 79.4%, and 79.4%, respectively). Based on the results from the present study, poultry by‐product, WG, and soy protein concentrate are the most promising alternative ingredients (i.e., to the fishmeal) for the formulation of totoaba grow‐out feeds.
Journal Article
Consensus, Global Definitions of Whole Grain as a Food Ingredient and of Whole-Grain Foods Presented on Behalf of the Whole Grain Initiative
Proposed global definitions of whole grain as an ingredient and whole grain food are presented by the authors on behalf of the Whole Grain Initiative. Whole grains are an important pillar of healthy and sustainable diets. Internationally accepted credible definitions of whole grains as food ingredients and whole-grain foods are necessary to ensure that all global stakeholders have shared standards, and that consumers find them clear, credible, and useful. Based on widely accepted, existing definitions and new developments, the Definitions Working Group of the global Whole Grain Initiative, with experts from academia, government agencies and industry, developed definitions for global application. The key statements of the definition documents are as follows: “Whole grains shall consist of the intact, ground, cracked, flaked or otherwise processed kernel after the removal of inedible parts such as the hull and husk; all anatomical components, including the endosperm, germ, and bran must be present in the same relative proportions as in the intact kernel” and “A whole-grain food shall contain at least 50% whole-grain ingredients based on dry weight. Foods containing 25–50% whole-grain ingredients based on dry weight, may make a front-of-pack claim on the presence of whole grain but cannot be designated ‘whole grain’ in the product name”. The definition documents have been ratified by the leading international scientific associations in this area. We urge that these consensus Whole Grain Initiative definitions be adopted as the basis for definitions used by national regulatory authorities and for health promotion organisations worldwide to use in nutrition education and food labelling.
Journal Article
Improving Personalized Meal Planning with Large Language Models: Identifying and Decomposing Compound Ingredients
Background/Objectives: Identifying and decomposing compound ingredients within meal plans presents meal customization and nutritional analysis challenges. It is essential for accurately identifying and replacing problematic ingredients linked to allergies or intolerances and helping nutritional evaluation. Methods: This study explored the effectiveness of three large language models (LLMs)—GPT-4o, Llama-3 (70B), and Mixtral (8x7B), in decomposing compound ingredients into basic ingredients within meal plans. GPT-4o was used to generate 15 structured meal plans, each containing compound ingredients. Each LLM then identified and decomposed these compound items into basic ingredients. The decomposed ingredients were matched to entries in a subset of the USDA FoodData Central repository using API-based search and mapping techniques. Nutritional values were retrieved and aggregated to evaluate accuracy of decomposition. Performance was assessed through manual review by nutritionists and quantified using accuracy and F1-score. Statistical significance was tested using paired t-tests or Wilcoxon signed-rank tests based on normality. Results: Results showed that large models—both Llama-3 (70B) and GPT-4o—outperformed Mixtral (8x7B), achieving average F1-scores of 0.894 (95% CI: 0.84–0.95) and 0.842 (95% CI: 0.79–0.89), respectively, compared to an F1-score of 0.690 (95% CI: 0.62–0.76) from Mixtral (8x7B). Conclusions: The open-source Llama-3 (70B) model achieved the best performance, outperforming the commercial GPT-4o model, showing its superior ability to consistently break down compound ingredients into precise quantities within meal plans and illustrating its potential to enhance meal customization and nutritional analysis. These findings underscore the potential role of advanced LLMs in precision nutrition and their application in promoting healthier dietary practices tailored to individual preferences and needs.
Journal Article
Recognizing Multiple Ingredients in Food Images Using a Single-Ingredient Classification Model
Recognizing food images presents unique challenges due to the variable spatial layout and shape changes of ingredients with different cooking and cutting methods. This study introduces a new approach for recognizing multiple ingredients segmented from food images. The method localizes the candidate regions of the ingredients, and then, these regions are assigned into ingredient classes using a CNN-based single-ingredient classification model trained on a dataset of single-ingredient images covering 110 kinds of foundational ingredient categories. Subsequently, the multi-ingredient identification is achieved through a decision-making scheme, incorporating a novel top n algorithm with integrating the classification results from various candidate regions to improve the ingredient recognition accuracy. Experimental results validate the effectiveness and efficiency of our method, particularly highlighting its competitive performance in recognizing multiple ingredients compared to state-of-the-art (SOTA) methods, while offering high interpretability.
Journal Article
Ingesting Risk — The FDA and New Food Ingredients
Food additives that are “generally recognized as safe” — a determination that can be made by manufacturers — aren’t required to be approved by the FDA. This system could pose a threat to public health.
Journal Article
The Application of Pollen as a Functional Food and Feed Ingredient—The Present and Perspectives
Pollen is recognized as an excellent dietary supplement for human nutrition, which is why it can be found in different forms on the market (granules, capsules, tablets, pellets, and powders). But, the digestibility of pollen’s nutrients is strongly affected by the presence of a pollen shell, which can decrease the bioavailability of nutrients by 50% and more. Since consumers have become more aware of the benefits of a healthy diet and the necessity to improve pollen digestibility, different pollen-based functional food products have been developed and extensive studies were done to estimate the beneficial effects of pollen-based feed on animal growth, health, and rigor mortise stage. Considering the positive effects of pollen nutrients and phytometabolites on human and animal health, the aim of this paper was to give an overview of recent achievements in the application of pollen in the formulation of functional food and animal diets. Special attention was paid to the effects of pollen’s addition on the nutritional, functional, techno-functional, and sensory properties of the new formulated food products. Anti-nutritional properties of pollen were also discussed. This review points out the benefits of pollen addition to food and feed and the possible directions in the further development of functional food and feed for the wellbeing of everyone.
Journal Article
INFOGEST static in vitro simulation of gastrointestinal food digestion
Developing a mechanistic understanding of the impact of food structure and composition on human health hasincreasingly involved simulating digestion in the upper gastrointestinal tract. These simulations have used a wide range of different conditions that often have very little physiological relevance, and this impedes the meaningful comparison of results. The standardized protocol presented here is based on an international consensus developed by the COST INFOGEST network. The method is designed to be used with standard laboratory equipment and requires limited experience to encourage a wide range of researchers to adopt it. It is a static digestion method that uses constant ratios of meal to digestive fluids and a constant pH for each step of digestion. This makes the method simple to use but not suitable for simulating digestion kinetics. Using this method, food samples are subjected to sequential oral, gastric and intestinal digestion while parameters such as electrolytes, enzymes, bile, dilution, pH and time of digestion are based onavailable physiological data. This amended and improved digestion method (INFOGEST 2.0) avoids challenges associated with the original method, such as the inclusion of the oral phase and the use of gastric lipase. The method can be used to assess the endpoints resulting from digestion of foods by analyzing the digestion products (e.g., peptides/amino acids, fatty acids, simple sugars) and evaluating the release of micronutrients from the food matrix. The whole protocol can be completed in ~7 d, including ~5 d required for the determination of enzyme activities.
Journal Article