Hasil untuk "Nutrition. Foods and food supply"

C. Agostoni, G. Buonocore, V. Carnielli et al.

R. Lal

Despite a 2.3% increase in world cereal production in 2019 over 2018, the number of people facing severe food insecurity may double from 135 million in January 2020 to 265 million by the end of 2020. The problem of food and nutritional insecurity is severe in urban centers, where the global population is projected to increase (%/year) by 1.84, 1.63, and 1.44 between 2015 to 2020, 2020 to 2025, and 2025 to 2030, and it will increase overall from 54% in 2016 to 60% by 2030. The number of megacities (>10 million people) will increase from 34 in 2015 to 41 by 2030. The COVID-19 pandemic has aggravated food insecurity in urban centers because of the disruption in the food supply chain, aggravation of the physical and economic barriers that restrict access to food, and the catastrophic increase in food waste because of labor shortages. Thus, there is a need to adopt more resilient food systems, reduce food waste, and strengthen local food production. Enhancing availability at the household and community levels through home gardening and urban agriculture is an important strategy. Food production within the cities include small land farming in households, local community gardens, indoor and rooftop gardens, vertical farming, etc. Home gardening can play an important role in advancing food and nutritional security during and after the COVD-19 pandemic, while also strengthening the provisioning of numerous ecosystem services (i.e., plant biodiversity, microclimate, water runoff, water quality, human health). However, risks of soil contamination by heavy metals must be addressed.

J. Poti, M. Mendez, S. Ng et al.

Mariela Contreras, María Elena Perdomo

Introducción: La desnutrición infantil es una condición asociada a la mortalidad infantil global. En los últimos 70 años, ha existido colaboración científica para poder aliviarla en el mundo. Objetivo: Analizar las conexiones de coautorías de países y organizaciones sobre la desnutrición infantil, con base en artículos científicos de 1942 a 2024 en una plataforma de libre acceso. Materiales y métodos: Se llevó a cabo un análisis bibliométrico de artículos científicos de desnutrición infantil en países de bajos y medianos ingresos, consultando la base de datos Dimensions y exportando un archivo de valores separados por comas (csv) en formato de mapeo bibliográfico. El análisis incorporó la herramienta Vosviewer 1.6.20 y el archivo csv fue importado para crear mapas con base en datos bibliográficos. Con la información importada, se crearon mapas de conexiones de países y de organizaciones. Resultados: Un total de 8.333 artículos científicos fueron derivados a partir de la estrategia de búsqueda y los criterios de inclusión y exclusión. Las conexiones de coautorías se dieron entre países localizados en el Norte y en el Sur Global. Algunos de los países del Sur Global también se posicionaron como parte de los 10 primeros países con conexiones más fuertes. Se observó el mismo patrón de conexiones de coautorías entre organizaciones localizadas en estas dos regiones. Conclusiones: Esta área de investigación se destaca por contar con conexiones fuertes de coautorías entre el Norte y el Sur Global. Esto es el reflejo de la colaboración internacional que ha existido en la nutrición en salud pública de la niñez.

Travis C Eden, Tyler J Godsey, Abby Maupin et al.

Azam Bayat, Aref Khalkhali, Ali Reza Mahjoub

Anemia is a decrease in hemoglobin and red blood cells and due to a decrease in hemoglobin, oxygen carrying capacity reduce. In this disease, the red blood cell the amount and volume decrease. In this research, healthy and live food powder were synthesized by a green route. This organic biomaterial was named NBS. The NBS healthy and live food powder has various vitamins, macro and micro molecules, and ingredients. Twenty Wistar rats were randomly divided into 4 equal groups, including control and treatment groups 1, 2 and 3. Nutritional supplements for healthy living were administered orally via gavage to rats in groups 1, 2, and 3 at 12.5, 25, and 50 mg/ kg, respectively, and within a period of 20 days, one day in between. There was no intervention in the control group in order to reach baseline blood factors. At the end of the study, blood samples were taken from the heart, including blood-red blood cells, hemoglobin, hematocrit and platelets using a fully automated blood cell counting machine. The results showed that the new dietary supplement reduced the level of hematocrit and platelets in the studied rats. The healthy and live food supplement at a concentration of 50 mg / kg increased blood levels compared to the control group. The results of this study showed that the use of healthy and live food supplement increased blood factors compared to the control group.

Jiajun Song, Xiaoou Liu

Food recognition has gained significant attention, but the rapid emergence of new dishes requires methods for recognizing unseen food categories, motivating Zero-Shot Food Learning (ZSFL). We propose the task of Compositional Zero-Shot Food Recognition (CZSFR), where cuisines and ingredients naturally align with attributes and objects in Compositional Zero-Shot learning (CZSL). However, CZSFR faces three challenges: (1) Redundant background information distracts models from learning meaningful food features, (2) Role confusion between staple and side dishes leads to misclassification, and (3) Semantic bias in a single attribute can lead to confusion of understanding. Therefore, we propose SalientFusion, a context-aware CZSFR method with two components: SalientFormer, which removes background redundancy and uses depth features to resolve role confusion; DebiasAT, which reduces the semantic bias by aligning prompts with visual features. Using our proposed benchmarks, CZSFood-90 and CZSFood-164, we show that SalientFusion achieves state-of-the-art results on these benchmarks and the most popular general datasets for the general CZSL. The code is avaliable at https://github.com/Jiajun-RUC/SalientFusion.

Leonardo Arrighi, Ingrid Alves de Moraes, Marco Zullich et al.

Artificial Intelligence (AI) has become essential for analyzing complex data and solving highly-challenging tasks. It is being applied across numerous disciplines beyond computer science, including Food Engineering, where there is a growing demand for accurate and trustworthy predictions to meet stringent food quality standards. However, this requires increasingly complex AI models, raising reliability concerns. In response, eXplainable AI (XAI) has emerged to provide insights into AI decision-making, aiding model interpretation by developers and users. Nevertheless, XAI remains underutilized in Food Engineering, limiting model reliability. For instance, in food quality control, AI models using spectral imaging can detect contaminants or assess freshness levels, but their opaque decision-making process hinders adoption. XAI techniques such as SHAP (Shapley Additive Explanations) and Grad-CAM (Gradient-weighted Class Activation Mapping) can pinpoint which spectral wavelengths or image regions contribute most to a prediction, enhancing transparency and aiding quality control inspectors in verifying AI-generated assessments. This survey presents a taxonomy for classifying food quality research using XAI techniques, organized by data types and explanation methods, to guide researchers in choosing suitable approaches. We also highlight trends, challenges, and opportunities to encourage the adoption of XAI in Food Engineering.

Matthias Kaiser, Agnese Cretella, Cordula Scherer et al.

We explore the challenges and opportunities of transitioning towards sustainable food systems through the lens of democratic food governance fostering inclusive and systemic transformation. Drawing on concepts of wicked problems and systems thinking, we propose a theory of change represented as a 'turtle model' that embraces the diversity of citizens' values and knowledge to highlight multiple avenues of transformation. As quadruple helix innovation and governance hubs, cities can be hotspots for food system transformations. We illustrate this for Dublin, Ireland, where local citizens' value-based food identities were galvanized to activate ecological awareness and promote sustainable seafood consumption. Within this democratic food governance framework, approaches such as open science, transdisciplinarity, and citizen engagement are fit-for-purpose to engage diverse food actors from government, industry, academia, and civil society in shared dialogue and action to transform food systems.

David Li

Food insecurity is a significant social and public health issue that plagues many urban metropolitan areas around the world. Existing approaches to identifying food insecurity rely primarily on qualitative and quantitative survey data, which is difficult to scale. This project seeks to explore the effectiveness of using street-level images in modeling food insecurity at the census tract level. To do so, we propose a two-step process of feature extraction and gated attention for image aggregation. We evaluate the effectiveness of our model by comparing against other model architectures, interpreting our learned weights, and performing a case study. While our model falls slightly short in terms of its predictive power, we believe our approach still has the potential to supplement existing methods of identifying food insecurity for urban planners and policymakers.

Joséphine Gehring, M. Touvier, J. Baudry et al.

BACKGROUND There is a growing availability of industrial plant-based meat and dairy substitutes that can be classified as ultra-processed foods (UPFs). Very little is known about the consumption of UPFs by vegetarians. OBJECTIVE The aim of this cross-sectional study, from the NutriNet-Santé cohort, was to describe the contribution of UPFs to different vegetarian diets, in relation to the nutritional quality of their diet, and determinants of UPF consumption, including duration and age at vegetarian diet initiation. METHODS The study population (n = 21,212) was divided into 4 groups: 19,812 meat eaters, 646 pesco-vegetarians, 500 vegetarians, and 254 vegans. Daily food intakes were collected using repeated 24-h dietary records. Vegetarian diets were described by the proportion of energy from UPFs and the nutritional quality of the diet using healthy and unhealthy plant-based diet indices (PDIs). In a subsample without meat eaters (n = 1,400), a multivariable linear regression model was performed to study the association between UPF consumption and its determinants. RESULTS Higher avoidance of animal-based foods was associated with a higher consumption of UPFs (P < 0.001), with UPFs supplying 33.0%, 32.5%, 37.0%, and 39.5% of energy intakes for meat eaters, pesco-vegetarians, vegetarians, and vegans. The nutritional quality of diets was also associated with the level of animal-based foods avoidance (P < 0.001), with healthy PDIs at 53.5, 60.6, 61.3 and 67.9 for meat-eaters, pesco-vegetarians, vegetarians, and vegans. Short duration and young age at diet initiation were associated with an increased consumption of UPFs (βage at initiation = -0.003, P = 0.001; βduration = -0.002, P < 0.001). CONCLUSIONS Not all vegetarian diets necessarily have health benefits, because of potential adverse effects of UPFs on nutritional quality and healthiness of diet. UPF consumption by vegetarians and their diet characteristics should be considered in future studies on the links between vegetarianism and health. This trial was registered at clinicaltrials.gov as NCT03335644.

Ce Shi, Zhiyao Zhao, Zhixin Jia et al.

Abstract The prediction of food shelf life has become a vital tool for distributors and consumers, enabling them to determine storage and optimal edible time, thus avoiding unexpected food waste. Artificial neural network (ANN) have emerged as an effective, fast and accurate method for modeling, simulating and predicting shelf life in food. ANNs are capable of tackling nonlinear, complex and ill-defined problems between the variables without prior knowledge. ANN model exhibited excellent fit performance evidenced by low root mean squared error and high correlation coefficient. The low relative error between actual values and predicted values from the ANN model demonstrates its high accuracy. This paper describes the modeling of ANN in food quality prediction, encompassing commonly used ANN architectures, ANN simulation techniques, and criteria for evaluating ANN model performance. The review focuses on the application of ANN for modeling nonlinear food quality during storage, including dairy, meat, aquatic, fruits, and vegetables products. The future prospects of ANN development mainly focus on optimal models and learning algorithm selection, multiple model fusion, self-learning and self-correcting shelf-life prediction model development, and the potential utilization of deep learning techniques. HIGHLIGHTS ANN-based food shelf life prediction methods are reviewed. This paper discusses application of ANN in the food storage process. BPNN is the mainstream ANN architecture used for the prediction of food quality. ANNs are useful for prediction of outputs with high accuracy. Future trends of ANN in the agri-supply chain are evaluated.

Okim Okim Nsor, Babatunde Adebola Alabi, Babatunde Adebola Alabi et al.

IntroductionDespite the high phenolic content of Annona muricata, little is known about its anti-hypertensive and antihyperlipidemic properties. This study evaluated the anti-hypertensive and antihyperlipidemic potential of A. muricata leaf extracts.Materials and methodsForty-two male Wistar rats were divided into seven groups of six animals each. N-nitro-L-arginine methyl ester (L-NAME) was used to induce hypertension and hyperlipidemia.ResultsPhytochemical screening of Annona muricata leaf extracts (AMLE) revealed the presence of saponins, alkaloids, flavonoids, tannins, coumarins, steroids, terpenoids, and phenols. Comparing the methanol extract with the ethyl acetate fraction, quantification revealed that the methanol extract contained more phenolics, flavonoids, and alkaloids. The AMLE rats significantly reduced triglycerides, total cholesterol, LDL, VLDL, atherogenic index, coronary risk index, and blood pressure. The significant decrease in GSH, catalase, SOD, GST, and oxidative stress markers (MDA, nitrites, and MPO) was reversed by AMLE in a dose-dependent manner. Also, the elevated serum levels of TNF-α and IL-1β in the hypertensive rats were attenuated in the treatment groups.DiscussionThis study suggests the potential ameliorative effects of Annona muricata leaf extracts against L-NAME-induced hypertension in rats. Notably, the study showed the antioxidant and anti-inflammatory properties of A. muricata leaf extracts, which is seen in its ability to attenuate oxidative stress and inflammatory cytokines in L-NAME-induced hypertensive rats. A. muricata extracts also decreased atherogenic risk and improved lipid profiles.

Eirin Winje, Ian Lake, Simon N. Dankel

Differentiating between an irrational versus a rational fear of hypoglycemia has treatment implications and presents significant challenge for clinicians facing patients with type 1 diabetes, illustrated in this case. A 39-year-old woman with autoimmune-positive insulin-dependent diabetes sought help to alleviate severe diabetes distress, and symptoms of depression and anxiety, associated with unpredictable drastic blood glucose drops. After exhausting conventional methods, she adopted a ketogenic diet (KD). Her glucose values decreased from around 20 mmol/L to 12 mmol/L (360 mg/dL to 216 mg/dL) in the first days. Then, by combining a KD with an insulin pump, her time in optimal glucose range increased from 8 to 51% after 2 months, reducing her HbA1c with 25 mmol/mol (2.2%). This reduced biological and psychological stress, immediately improving her mental health and renewing her hope for the future. The main concerns regarding KD in patients with comorbid type 1 diabetes is the assumed increased risk of ketoacidosis, theoretical depletion of glycogen stores, and a potential adverse effect of saturated fat on cardiovascular risk factors. These concerns are evaluated against existing empirical evidence, suggesting instead that a KD may protect against acidosis, hypoglycemia, and cardiovascular risk. The present case, together with available data, indicate that patients with type 1 diabetes experiencing high levels of biological and psychological stress should be informed of the expected benefits and possible risks associated with a KD, to ensure their right to take informed decisions regarding their diabetes management.

Michal Pšurný, Michal Pšurný, Irena Baláková et al.

The paper deals with consumer behavior in the context of sustainable development of society. A questionnaire survey of 732 respondents was used to understand the determinants of food purchasing behavior toward sustainable consumption. The paper identifies the factors that the consumer determines in food purchasing as critical in terms of sustainable consumption and requiring behavioral change toward sustainability in terms of healthy lifestyle, reduction of food wastage, and conscious consumption. Respondents commented on 22 factors and the quantification of their impact on food waste and expressed the strength of opinion on sustainability issues. To evaluate the collected data, PCA factor analysis was used, which defines the importance of each factor by identifying artificial hypothetical variables, which are “Sustainability” and targeted education as appropriate tools for it, “Food usability,” which is a recommendation to producers by food quality, offering new types of food with longer shelf life, as well as “Pricing,” “Quality” and “Convenience.” The authors also sought to understand what measures they take in relation to waste and how they behave toward sustainable consumption and environmental protection. They created 14 content questions on this topic and by using factor analysis, 3 hypothetical variables were created, namely “Sustainable behavior” which expresses a healthy lifestyle, “Thoughtful purchase” which expresses a relationship with environmental protection before purchasing and “Zero waste” which means that the household tries to make additional use of food. Thus, it seeks a use for the food it cannot consume at a given time and creates a supply for other consumers. This behavior is a good prerequisite for achieving a change in consumption behavior. The influence of selected sociodemographic indicators on the frequency of wastage was also investigated using the χ-squared test. The influence of generation and number of children in the household on the frequency of wastage was demonstrated. The results of the analyses on the importance of individual factors and consumer behavior, especially of the young generation, argue for education on sustainable consumption.

Rikhaturhohmah, Rospadila Dwi Adrila, Widiya Dwi Handayani et al.

Dental plaque is the main cause of dental caries caused by Streptococcus mutans, with a high prevalence in Indonesia. Currently, the mouthwash market contains high levels of alcohol, which can cause long-term side effects. Tampala bajakah root (Spatholobus littoralis) is used in traditional medicine for the Dayak community in Central Kalimantan. Bajakah Tampala root has antibacterial activity produced by flavonoids and phenolic compounds. The development of herbal cosmetics can be achieved by Bajakah Tampala mouthwash formulations to prevent dental plaque caused by Streptococcus mutans infection. In this study, ultrasound-assisted extraction (UBT) and infusion (IBT) derived the active compounds of Bajakah Tampala root extract. The various concentrations of UBT (20–80%) and IBT (10%) were evaluated for antibacterial activity using the disk diffusion method. The results showed that positive control and 80% UBT have antibacterial activity higher than other extracts, with an inhibition zone of 14,01±2,70 mm. Based on these results, an effective mouthwash dosage formulation can be developed at 80% UBT. The formulation evaluation of mouthwash assessed viscosity, homogeneity, pH, and organoleptic test. The UBT mouthwash product has qualified formulation evaluation parameters. This research contributed to the innovation of herbal cosmetics by developing the potential of Indonesian medicinal plants

Abed Forouzesh, Fatemeh Forouzesh, Sadegh Samadi Foroushani et al.

Abstract Computing the food component (nutrient) amount in 100 kilocalories, 100 grams or 100 milliliters, the reference amount customarily consumed (RACC), or 50 grams of food demonstrates the food component amount of some foods unsuitably. So, selecting some foods based on them may elevate the hazards of some chronic diseases. Computing the food component amount and assessing suitable levels of food components and the nutritional quality according to the Codex Alimentarius Commission (CAC), the United States Food and Drug Administration (FDA), and the suggested procedure were implemented on 8,596 food cases, 29 food components, and 25 food categories. Selecting some foods under the FDA and CAC to reach sufficient intakes of positive food components surpassed energy demands. Selecting some foods under the CAC did not satisfy the demands of positive food components. Some foods that satisfied the demands of positive food components were not suitable food selections under the CAC. Selecting some foods under the FDA or CAC surpassed the demands of negative food components (including cholesterol, energy, fat, saturated fat, and sodium). Some foods that did not surpass the demands of negative food components were not suitable food selections under the CAC or FDA. Due to the vulnerabilities of selecting foods on the basis of the reference amounts of food, fast foods under the CAC and FDA in serving size (the serving size or serving is obtained from the RACC), spices and herbs under the CAC in 100 grams or 100 milliliters, and vegetables and vegetable products under the CAC in 100 kilocalories obtained the highest average scores for nutritional quality based on positive food components (including vitamins, protein, dietary fiber, and minerals, excluding sodium) among food categories for children aged four years and older and adults. Graphical Abstract

Xiaoyu Ji, Jan P Allebach, Ali Shakouri et al.

This paper is directed towards the food crystal quality control area for manufacturing, focusing on efficiently predicting food crystal counts and size distributions. Previously, manufacturers used the manual counting method on microscopic images of food liquid products, which requires substantial human effort and suffers from inconsistency issues. Food crystal segmentation is a challenging problem due to the diverse shapes of crystals and their surrounding hard mimics. To address this challenge, we propose an efficient instance segmentation method based on object detection. Experimental results show that the predicted crystal counting accuracy of our method is comparable with existing segmentation methods, while being five times faster. Based on our experiments, we also define objective criteria for separating hard mimics and food crystals, which could benefit manual annotation tasks on similar dataset.

Georges Dubourg, Zoran Pavlović, Branimir Bajac et al.

The application of metal oxide nanomaterials (MOx NMs) in the agrifood industry offers innovative solutions that can facilitate a paradigm shift in a sector that is currently facing challenges in meeting the growing requirements for food production, while safeguarding the environment from the impacts of current agriculture practices. This review comprehensively illustrates recent advancements and applications of MOx for sustainable practices in the food and agricultural industries and environmental preservation. Relevant published data point out that MOx NMs can be tailored for specific properties, enabling advanced design concepts with improved features for various applications in the agrifood industry. Applications include nano-agrochemical formulation, control of food quality through nanosensors, and smart food packaging. Furthermore, recent research suggests MOx's vital role in addressing environmental challenges by removing toxic elements from contaminated soil and water. This mitigates the environmental effects of widespread agrichemical use and creates a more favorable environment for plant growth. The review also discusses potential barriers, particularly regarding MOx toxicity and risk evaluation. Fundamental concerns about possible adverse effects on human health and the environment must be addressed to establish an appropriate regulatory framework for nano metal oxide-based food and agricultural products.

Zhening Li, John Harte

Food web topology and energy flow rates across food web linkages can influence ecosystem properties such as stability. Stability predictions from current models of energy flow are often sensitive to details in their formulation, and their complexity makes it difficult to elucidate underlying mechanisms of general phenomena. Here, within the maximum information entropy inference framework (MaxEnt), we derive a simple formula for the energy flow carried by each linkage between two adjacent trophic layers. Inputs to the model are the topological structure of the food web and aggregate energy fluxes entering or exiting each species node. For ecosystems with interactions dominated by consumer-resource interactions between two trophic layers, we construct a model of species dynamics based on the energy flow predictions from the MaxEnt model. Mathematical analyses and simulations of the model show that a food web topology with a higher matrix dipole moment promotes stability against small perturbations in population sizes, where the \textit{matrix dipole moment} is a simple nestedness metric that we introduce. Since nested bipartite subnetworks arise naturally in food webs, our result provides an explanation for the stability of natural communities.