Hasil untuk "Nutrition. Foods and food supply"

P. Baker, P. Machado, T. Santos et al.

Understanding the drivers and dynamics of global ultra‐processed food (UPF) consumption is essential, given the evidence linking these foods with adverse health outcomes. In this synthesis review, we take two steps. First, we quantify per capita volumes and trends in UPF sales, and ingredients (sweeteners, fats, sodium and cosmetic additives) supplied by these foods, in countries classified by income and region. Second, we review the literature on food systems and political economy factors that likely explain the observed changes. We find evidence for a substantial expansion in the types and quantities of UPFs sold worldwide, representing a transition towards a more processed global diet but with wide variations between regions and countries. As countries grow richer, higher volumes and a wider variety of UPFs are sold. Sales are highest in Australasia, North America, Europe and Latin America but growing rapidly in Asia, the Middle East and Africa. These developments are closely linked with the industrialization of food systems, technological change and globalization, including growth in the market and political activities of transnational food corporations and inadequate policies to protect nutrition in these new contexts. The scale of dietary change underway, especially in highly populated middle‐income countries, raises serious concern for global health.

S. Nordhagen, Uduak Igbeka, H. Rowlands et al.

Food and nutrition security play an essential role in weathering and overcoming the COVID-19 pandemic—and in achieving sustainable development. In most low- and middle-income countries, micro, small, and medium-sized enterprises (MSMEs) play an essential role in food supply chains and thus in ensuring food and nutrition security. However, limited attention has been paid to how these critical food system actors are being impacted by the pandemic and associated measures. This paper helps fill that gap through analysis of data from 367 agri-food MSMEs in 17 countries, collected in May 2020 and capturing early impacts of the pandemic on their operations. About 94.3% of respondents reported that their firm’s operations had been impacted by the pandemic, primarily through decreased sales as well as lower access to inputs and financing amid limited financial reserves. Difficulty with staffing was also widely cited. Eighty-four percent of firms reported changing their production volume as a result of the pandemic; of these, about 13% reported stopping production and about 82% reported decreasing production. Approximately 54% had changed product prices as a result of the pandemic. The probability of being severely impacted was significantly higher for firms with <50,000 USD in annual turnover; a larger decrease in consumer mobility for grocery/pharmacy shopping also increased the probability of a severe impact. Surprisingly, the youngest firms and those with the fewest employees (controlling for turnover) were less likely to be severely impacted. Over 80% of firms had taken actions to mitigate the pandemic’s impact on their operations and/or staff, and about 44% were considering exploring new business areas, with some seeing opportunities for growth. We conclude by discussing implications for policy responses to address immediate challenges as well as increase long-term food system resilience to support further progress towards sustainable development.

Raif Cergibozan, Emre Akusta

Food security refers to people's access to enough safe nutritious food in order to be able to lead a healthy active life. It also involves elements such as food availability and affordability, as well as people being able to access food that can be consumed healthily. Natural disasters, however, can seriously threaten food security. Disasters' effects on food security are especially more evident in countries such as Turkiye that are frequently exposed to natural disasters due to their geologic and geographical structure. For this reason, the study investigates the effects of natural disasters on food security in Turkiye. The research first creates the Food Security Index in order to estimate the effects of natural disasters on food security. The next phase follows the process of econometric analysis, which consists of three steps. Step one of the econometric analysis uses unit root tests to check the stationarity levels of the series. The second step uses the autoregressive distributed lag (ARDL) bounds test to examine the long-term relationship between natural disasters and food security. The third and final step estimates the effects of natural disasters on food security. According to the obtained results, the study shows earthquakes, storms, and floods to have a significant short- as well as long-term negative effect on food security. The overall impact of natural disasters on food security has also been determined to be negative.

Zhenbo Xu, Jinghan Yang, Gong Huang et al.

With the rise and development of computer vision and LLMs, intelligence is everywhere, especially for people and cars. However, for tremendous food attributes (such as origin, quantity, weight, quality, sweetness, etc.), existing research still mainly focuses on the study of categories. The reason is the lack of a large and comprehensive benchmark for food. Besides, many food attributes (such as sweetness, weight, and fine-grained categories) are challenging to accurately percept solely through RGB cameras. To fulfill this gap and promote the development of intelligent food analysis, in this paper, we built the first large-scale spectral food (SFOOD) benchmark suite. We spent a lot of manpower and equipment costs to organize existing food datasets and collect hyperspectral images of hundreds of foods, and we used instruments to experimentally determine food attributes such as sweetness and weight. The resulting benchmark consists of 3,266 food categories and 2,351 k data points for 17 main food categories. Extensive evaluations find that: (i) Large-scale models are still poor at digitizing food. Compared to people and cars, food has gradually become one of the most difficult objects to study; (ii) Spectrum data are crucial for analyzing food properties (such as sweetness). Our benchmark will be open source and continuously iterated for different food analysis tasks.

Anna Kalenkova, Lu Xia, Dirk Neumann

This paper proposes a novel method for analyzing food retail processes with a focus on reducing food waste. The approach integrates object-centric process mining (OCPM) with stochastic process discovery and analysis. First, a stochastic process in the form of a continuous-time Markov chain is discovered from grocery store sales data. This model is then extended with supply activities. Finally, a what-if analysis is conducted to evaluate how the quantity of products in the store evolves over time. This enables the identification of an optimal balance between customer purchasing behavior and supply strategies, helping to prevent both food waste due to oversupply and product shortages.

Marcela Reymond Simoes, Bruna Bombassaro, Milena Monfort-Pires et al.

Julio Cesar dos Reis, Mariana Yumi Takahashi Kamoi, Tarik Marques do Prado Tanure et al.

Diversified sustainable agricultural systems, such as integrated crop-livestock-forest systems (ICLFs), offer substantial potential for enhancing food production to meet the increasing global demand for agricultural goods while, simultaneously, conserving vital natural resources, including soil, water, and forests. However, a critical barrier to the widespread adoption of these sustainable systems in Brazil’s Amazon and Cerrado biomes, its primary agricultural commodity-producing regions, is the lack of comprehensive economic information. This paper presents case studies that evaluate the economic performance of ICLFs compared to traditional agricultural practices in these biomes (extensive livestock and large-scale cropping systems). Additionally, we employ an economic impact analysis using an input–output matrix approach to assess the economic benefits associated with ICLF adoption. The findings indicate that integrated systems exhibit superior economic performance, particularly over the long-term, as evidenced by more favorable viability indicators, such as higher internal rates of return and profitability indexes. In the Cerrado biome, the gross profit per hectare is up to USD 200 higher compared to traditional livestock and USD 26.5 higher than crop farming. While these systems necessitate higher initial investments per hectare, they provide shorter payback periods and increased profitability. Furthermore, it is observed that an ICLF expansion over degraded pasture in Brazil would promote highly positive economic impacts. Approximately 61,000 and 50,000 additional jobs would be generated in the Cerrado and Amazon biomes, respectively. In terms of production value, it would be up to USD 19.7 billion higher in the Cerrado biome and USD 16 billion higher in the Amazon biome compared to traditional livestock farming. These findings reinforce the role of public policies aimed at promoting sustainable agriculture and achieving the targets established in the Brazilian Low-Carbon Agriculture Plan.

Hong-Ju He, M. V. da Silva Ferreira, Qianyi Wu et al.

Abstract Food fraud, a pervasive issue in the global food industry, poses significant challenges to consumer health, trust, and economic stability, costing an estimated $10–15 billion annually. Therefore, there is a rising demand for developing portable and miniature sensors that facilitate food authentication throughout the supply chain. This review explores the recent advancements and applications of portable and miniature sensors, including portable/miniature near-infrared (NIR) spectroscopy, e-nose and colorimetric sensors based on nanozyme for food authentication within the supply chain. After briefly presenting the architecture and mechanism, this review discusses the application of these portable and miniature sensors in food authentication, addressing the challenges and opportunities in integrating and deploying these sensors to ensure authenticity. This review reveals the enhanced utility of portable/miniature NIR spectroscopy, e-nose, and nanozyme-based colorimetric sensors in ensuring food authenticity and enabling informed decision-making throughout the food supply chain.

Dietrich Knorr, Mary Ann Augustin

Abstract Many underutilized food resources have been traditionally used by regional and poor communities. The history of their consumption makes them potential new food sources for incorporation into the wider food supply. The ability to tap the potential of undervalued and underutilized food sources will reduce the world's reliance on a limited number of food sources and improve food security and sustainability. The expansion of the food diversity of the food supply to include underutilized food resources will require overcoming challenges in the efficient and profitable production of the raw material, application of suitable postharvest handling procedures to maintain the quality of perishable produce, and the use of appropriate traditional and emerging food processing technologies for conversion of the raw material into safe, nutritious and consumer‐acceptable foods. Improvement of food processing technologies, particularly resource‐efficient resilient food processes, are required to ensure the safety, quality and functionality of the whole food or extracts, and to develop ingredient formulations containing new foods for manufacture of consumer food products. Factors that help facilitate the social acceptance of new underutilized foods include increasing consumer knowledge and understanding of the contribution of new underutilized food resources to diet diversity for good nutrition, confidence in the safety and value of new foods, and their low environmental impact and importance for future sustainable food. The introduction of new underutilized food resources will increasingly require collaboration along the whole food value chain, including support from government and industry. © 2024 The Author(s). Journal of the Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Theofilos D. Mastos, Katerina Gotzamani, Petros Ieromonachou et al.

This paper presents a model designed to measure and investigate the relationships between critical factors, practices, and performance of sustainable supply chain management (SSCM) in the food industry. A survey of 423 firms in the Greek food industry was conducted to meet these objectives. The data were analyzed using exploratory factor analysis, followed by confirmatory factor analysis and structural equation modeling, to explore the relationships between the model’s constructs. The results indicate that “firm-level critical sustainability factors” and “supply chain critical sustainability factors” significantly enhance “supply chain collaboration” and “supply chain strategic orientation”. Additionally, “supply chain strategic orientation” positively influences “social performance” and “environmental performance”, while “supply chain collaboration” positively affects “economic performance” and “environmental performance”. Furthermore, “social performance” is found to have a significant positive impact on “economic performance”. This study provides empirical evidence that helps managers understand the importance of the relationships among SSCM critical factors, SSCM practices, and SSCM performance, and enables them to allocate resources effectively and design SSCM strategies. Finally, the developed constructs offer a measurement tool useful for both practitioners implementing SSCM in their firms and researchers who wish to apply or test the proposed scales in other projects or use them as benchmarks.

Selina Cox, Alicia Sandall, Leanne Smith et al.

AbstractFood additive intakes have increased with the increase in “ultra-processed” food consumption. Food additive emulsifiers have received particular research attention in recent years due to preliminary evidence of adverse gastrointestinal and metabolic health effects. In this review, the use of emulsifiers as food additives is discussed, and the current estimations of exposure to, and safety of, emulsifiers are critically assessed. Food additive emulsifier research is complicated by heterogeneity in additives considered to be emulsifiers and labelling of them on foods globally. Major limitations exist in estimating food additive emulsifier exposure, relating predominantly to a lack of available food occurrence and concentration data. Development of brand-specific food additive emulsifier databases are crucial to accurately estimating emulsifier exposure. Current research on the health effects of food additive emulsifiers are limited to in vitro and murine studies and small, acute studies in humans, and future research should focus on controlled human trials of longer duration.

Guoshan Liu, Yang Jiao, Jingjing Chen et al.

The precise recognition of food categories plays a pivotal role for intelligent health management, attracting significant research attention in recent years. Prominent benchmarks, such as Food-101 and VIREO Food-172, provide abundant food image resources that catalyze the prosperity of research in this field. Nevertheless, these datasets are well-curated from canteen scenarios and thus deviate from food appearances in daily life. This discrepancy poses great challenges in effectively transferring classifiers trained on these canteen datasets to broader daily-life scenarios encountered by humans. Toward this end, we present two new benchmarks, namely DailyFood-172 and DailyFood-16, specifically designed to curate food images from everyday meals. These two datasets are used to evaluate the transferability of approaches from the well-curated food image domain to the everyday-life food image domain. In addition, we also propose a simple yet effective baseline method named Multi-Cluster Reference Learning (MCRL) to tackle the aforementioned domain gap. MCRL is motivated by the observation that food images in daily-life scenarios exhibit greater intra-class appearance variance compared with those in well-curated benchmarks. Notably, MCRL can be seamlessly coupled with existing approaches, yielding non-trivial performance enhancements. We hope our new benchmarks can inspire the community to explore the transferability of food recognition models trained on well-curated datasets toward practical real-life applications.

Abdulla Alourani, Shahnawaz Khan

The demand of the halal food products is increasing rapidly around the world. The consumption of halal food product is just not among the Muslims but also among non-Muslims, due to the purity of the halal food products. However, there are several challenges that are faced by the halal food consumers. The challenges raise a doubt among the halal food consumers about the authenticity of the product being halal. Therefore, a solution that can address these issues and can establish trust between consumers and producers. Blockchain technology can provide a distributed ledger of an immutable record of the information. Artificial intelligence supports developing a solution for pattern identification. The proposed research utilizes blockchain an artificial intelligence-based system for developing a system that ensure the authenticity of the halal food products by providing the traceability related to all the operations and processes of the supply chain and sourcing the raw material. The proposed system has been tested with a local supermarket. The results and tests of the developed solution seemed effective and the testers expressed interest in real-world implementation of the proposed system.

Giovanni Palermo, Claudio Caprioli, Giambattista Albora

In the early 2000s, renowned chef Heston Blumenthal formulated his "food pairing" hypothesis, positing that if foods share many flavor compounds, then they tend to taste good when eaten together. In 2011, Ahn et al. conducted a study using a dataset of recipes, ingredients, and flavor compounds, finding that, in Western cuisine, ingredients in recipes often share more flavor compounds than expected by chance, indicating a natural tendency towards food pairing. Building upon Ahn's research, our work applies state-of-the-art collaborative filtering techniques to the dataset, providing a tool that can recommend new foods to add in recipes, retrieve missing ingredients and advise against certain combinations. We create our recommender in two ways, by taking into account ingredients appearances in recipes or shared flavor compounds between foods. While our analysis confirms the existence of food pairing, the recipe-based recommender performs significantly better than the flavor-based one, leading to the conclusion that food pairing is just one of the principles to take into account when creating recipes. Furthermore, and more interestingly, we find that food pairing in data is mostly due to trivial couplings of very similar ingredients, leading to a reconsideration of its current role in recipes, from being an already existing feature to a key to open up new scenarios in gastronomy. Our flavor-based recommender can thus leverage this novel concept and provide a new tool to lead culinary innovation.

Ahmad AlMughrabi, Adrián Galán, Ricardo Marques et al.

Food segmentation, including in videos, is vital for addressing real-world health, agriculture, and food biotechnology issues. Current limitations lead to inaccurate nutritional analysis, inefficient crop management, and suboptimal food processing, impacting food security and public health. Improving segmentation techniques can enhance dietary assessments, agricultural productivity, and the food production process. This study introduces the development of a robust framework for high-quality, near-real-time segmentation and tracking of food items in videos, using minimal hardware resources. We present FoodMem, a novel framework designed to segment food items from video sequences of 360-degree unbounded scenes. FoodMem can consistently generate masks of food portions in a video sequence, overcoming the limitations of existing semantic segmentation models, such as flickering and prohibitive inference speeds in video processing contexts. To address these issues, FoodMem leverages a two-phase solution: a transformer segmentation phase to create initial segmentation masks and a memory-based tracking phase to monitor food masks in complex scenes. Our framework outperforms current state-of-the-art food segmentation models, yielding superior performance across various conditions, such as camera angles, lighting, reflections, scene complexity, and food diversity. This results in reduced segmentation noise, elimination of artifacts, and completion of missing segments. Here, we also introduce a new annotated food dataset encompassing challenging scenarios absent in previous benchmarks. Extensive experiments conducted on MetaFood3D, Nutrition5k, and Vegetables & Fruits datasets demonstrate that FoodMem enhances the state-of-the-art by 2.5% mean average precision in food video segmentation and is 58 x faster on average.

Raiyan Rahman, Mohsena Chowdhury, Yueyang Tang et al.

The escalating global concern over extensive food wastage necessitates innovative solutions to foster a net-zero lifestyle and reduce emissions. The LILA home composter presents a convenient means of recycling kitchen scraps and daily food waste into nutrient-rich, high-quality compost. To capture the nutritional information of the produced compost, we have created and annotated a large high-resolution image dataset of kitchen food waste with segmentation masks of 19 nutrition-rich categories. Leveraging this dataset, we benchmarked four state-of-the-art semantic segmentation models on food waste segmentation, contributing to the assessment of compost quality of Nitrogen, Phosphorus, or Potassium. The experiments demonstrate promising results of using segmentation models to discern food waste produced in our daily lives. Based on the experiments, SegFormer, utilizing MIT-B5 backbone, yields the best performance with a mean Intersection over Union (mIoU) of 67.09. Class-based results are also provided to facilitate further analysis of different food waste classes.

Ryoken Aoki, Yasuo Watanabe, Yuki Sakai et al.

Sparassis crispa, an edible mushroom, has been reported to show many kinds of physiological functions. The present paper focused on reducing body weight, subcutaneous fat, and visceral fat gain in ovariectomized (OVX) mice. Using the fruiting body powder of the indoor cultivation S. crispa (IT S. crispa: ITSc), one week after the OVX, ITSc was administered to two OVX groups by per os (p.o). In the sham group, 10 mL/kg water and 10 mL/kg saline were administered by p.o. and subcutaneous adm, respectively. OVX groups were divided into four groups. These treatments were performed on animals 6 days a week for 8 weeks. Subcutaneous and visceral fat measurements were performed under inhalation anesthesia with isoflurane using a Latheta LCT-200 X-ray CT system. The biochemical markers and the mRNA expression levels of the PPARγ, adiponectin, TNF-α, PPARα, and leptin were measured. Significant increases in body weight, fat ratio, and glucose levels were detected in OVX mice compared to sham mice. These increases were significantly blocked by ITSc, but not estradiol. Furthermore, ITSc treatment significantly increased adiponectin and leptin levels in adipose tissue. These results suggest that ITSc improves lipid abnormalities due to the less activity of women's ovary function, excluding estrogen functions.

Ting Miao, Pathairat Pastpipatkul, Xinhua Liu et al.

This study employs the stochastic frontier model (SFM) to analyze trade potential and efficiency in wheat and maize among Belt and Road Initiative (BRI) countries from 2002 to 2021, encompassing 45 countries for wheat trade and 55 for maize trade. The empirical findings reveal that economic development level, population growth, government efficiency, political stability, and regulatory quality are critical determinants of trade efficiency. Notably, World Trade Organization (WTO) membership exhibits a negative correlation with trade efficiency, potentially reflecting challenges in rule implementation and opportunity utilization among member states. In the context of maize trade, increased arable land area is inversely associated with efficiency, suggesting potential issues in managing large-scale agricultural regions or optimizing land use. The BRI’s impact on trade efficiency varies across countries, with Turkey and Hungary showing improved wheat trade efficiency, while Ethiopia and Georgia experienced declines. During the COVID-19 pandemic, effective disease management strategies and diversified trade mechanisms significantly influenced trade efficiency. Furthermore, the study reveals that larger economies do not necessarily outperform small and medium-sized economies in terms of trade potential. These findings contribute significantly to the literature on agricultural trade and offer valuable insights for policymakers, emphasizing the importance of enhancing government efficiency, political stability, and regulatory quality in the context of regional economic development initiatives such as the BRI. This research underscores the need for tailored approaches to trade policy and agricultural management, considering the unique characteristics and challenges faced by different economies along BRI.

Mahfujul Alam, Mir Meahadi Hasan, Mrinal Kanti Debnath et al.

Papaya fruits different edible and non-edible portions are valued for the abundance of numerous nutrients and therapeutic benefits. The study was aimed to examine the physico-chemical properties, bioactive compounds (total phenolics and total flavonoids), antioxidant activity and microstructure analysis of the peel, pulp and seed flour of both ripe and unripe papaya. The results demonstrated the different portions of both ripe and unripe papaya fruit flour differed significantly with respect to almost all quality attributes within them. The physico-chemical variations have been evaluated through evaluation of the pH, moisture content, TSS, and ascorbic acid content of the papaya fruits during both ripening stages. Statistically significant variations (p < 0.05) were observed between two distinct stages of ripening. The concentration of ascorbic acid in the fruit revealed a notable increase as it matured, while the pH, moisture, and TSS all exhibited a substantial decrease (p < 0.05) during the immature stage. The unripe peel showed the most significant level of bulk density, tapped density, swelling capacity, crude fiber, and TFC whereas the unripe seed showed the highest value of ash, crude fat, and TPC. For the rest of the value, ripe pulp and seed flour showed a significantly higher value than others. The total phenolic content in seed flour and the total flavonoid content of peel flour were 196.9 ± 0.03 and 164.9 ± 0.08 mgQE/100 g, respectively, at unripe conditions. An immense amount of antioxidant activity was found in ripe (20.48 ± 0.54%) and unripe (16.05 ± 0.32%) peels flour. The flour granules' diverse morphological forms and particle sizes were identified by SEM analysis. The versatility of papaya and its various components provides opportunities for applications in the food, pharmaceutical, cosmetic, and agricultural industries. The papaya fruit flour of different portions have unique functional, nutritional, and morphological characteristics that may contribute to the development of gluten free flour based value added baked products.

Imran Ali, A. Sadiddin, A. Cattaneo

ABSTRACT The sustainable and resilient agri-food systems are essential to ensure food security and nutrition for a rapidly growing world population. While the unprecedented COVID-19 outbreak has undoubtedly disrupted numerous businesses, small- and medium-sized enterprises (SMEs) of agri-food supply chains (AFSCs) were seen more vulnerable to disruptions due to their unique operational challenges. This research explores how SMEs of AFSCs across developing and developed contexts were disrupted by COVID-19 inflicted risks and what useful measures were embraced to cultivate supply chain resilience (SCRE). A qualitative research method, with 24 semi-structured interviews including two developing (Pakistan and Tanzania) and a developed (Australia) country, was employed. The cross-country analysis unveils a noticeable difference in risk and SCRE profiles between developing and developed contexts. We devise a systematic account of COVID-19 inflicted risks and related SCRE strategies to survive and thrive amid the current pandemic and similar future crises. Multiple perspectives from different contexts would assist practitioners and policymakers to learn the key lessons, enhancing resilience of agri-food SMEs. This is among the few studies exploring risk and SCRE in SMEs of AFSCs across developing and developed contexts, benchmarking robust strategies applied by some leading firms. Our proposed conceptual framework offers a roadmap to building more resilient agri-food SMEs.