Hasil untuk "Nutrition. Foods and food supply"

Maryam Rostamzadeh, Elham Khalili Sadrabad, Fateme Akrami Mohajeri et al.

ABSTRACTDue to the high occupational exposure of miners to heavy metals, the concentration of arsenic, cadmium, lead, copper, and zinc in raw and cooked foods consumed by mine workers and the risk assessment of the consumption of these foods were investigated. A total of 105 samples of raw and cooked foods and beverages were collected. Samples were oven‐dried, digested with microwave‐assisted nitric acid for the analysis of heavy metals using an ICP‐OES. The health risk assessment was performed through hazard quotient (HQ) and hazard index (HI) calculations. The concentrations of all heavy metals measured in both raw foods and cooked foods were lower than the permissible limits as determined by FAO/WHO and Iranian national standards. The HQ and HI for all metals were less than one, signifying no health risk from dietary exposure. Heavy metal levels in food taken by miners fell within permissible limits, but periodic monitoring is necessary because of miners' occupational exposure to heavy metals.

Na Dong, Chenyu Xue

Bioactive peptides (BPs), predominantly generated from food-derived proteins via enzymatic hydrolysis and microbial fermentation, have demonstrated multifunctional biological activities. These include antimicrobial, immunomodulatory, antioxidant, and anticancer effects, which are often mediated through mechanisms such as enzyme inhibition, metal chelation, and modulation of cellular signaling pathways. Owing to these properties, BPs have attracted considerable attention for the development of functional foods, dietary supplements, and therapeutic agents. This chapter provides a comprehensive overview of their physiological functions, molecular mechanisms of action, and production methods, including enzymatic hydrolysis, microbial fermentation, membrane separation, and emerging omics-based strategies. Key challenges in bioavailability, stability, and large-scale applications are discussed, along with recent innovations and future perspectives for the integration of BPs into health-promoting food systems.

Syamsul Rahman

The global functional food market was valued at approximately USD 280.7 billion in 2021, with a projected growth rate of 8.5% from 2022 to 2030. Functional foods are attractive to a diverse global population due to their potential to improve and maintain human health. Plant-based diets contain numerous secondary metabolites that may influence health and disease prevention, with a primary focus on the potential bioactivity and nutritional relevance of several classes of phytochemicals, such as polyphenols, flavonoids, saponins, tannins, carotenoids, phytoestrogens, and fructooligosaccharides, many of which are found in cassava leaves (Manihot esculenta Crantz). The purpose of this chapter is to provide an in-depth overview of the potential use of cassava leaves as functional foods, with an emphasis on traditional knowledge and practices. Evidence from various regions in Indonesia indicates that cassava leaves have long been utilized, both as food and as conventional medicine. Its widespread use is due to its rich composition of nutrients, minerals, vitamins, and phytochemicals, including carbohydrates, essential amino acids, dietary fiber, β-carotene, phenolics, anthocyanins, flavonoids, tannins, and saponins, which are widely associated with its various beneficial properties for health such as antidiabetic, anti-inflammatory, antibacterial, and anti-obesity effects.

Wanying Zhu, Yuhe Dong, Tong Wu et al.

Citral and linalool are two well-studied antibacterial essential oil compounds. However, their synergistic antibacterial effects have not been fully elucidated. This study explored their synergistic mechanism against Escherichia coli and the potential of their β-cyclodextrin (β-CD) inclusion complexes in food preservation. The combination of citral and linalool demonstrated enhanced efficiency in damaging bacterial cell membranes, inducing protein leakage, causing structural collapse, and inhibiting biofilm formation, reducing extracellular polymeric substance (EPS), and impairing bacterial motility compared to the individual use of either compound. Furthermore, the β-CD inclusion complexes of these two compounds exhibited synergistic effects in cooked chicken by inhibiting total viable counts (TVC) to 3.31 Log CFU/g after 3 days of storage, which is lower than the single-use groups (4.07 and 3.78 Log CFU/g for citral and linalool, respectively). These complexes also decreased total volatile basic nitrogen (TVB-N) accumulation and prevented pH increase, thereby enhancing food safety and quality.

Christina G. Slater, Andrew Muhammad, Karen L. DeLong

Product quality is essential, as it influences consumer preferences and, hence, affects imports. In this study, we employed a demand system framework to estimate source-differentiated beef demand in Japan. Additionally, we evaluated whether the quality attributes of chilled versus frozen beef were significant in explaining trade flows. Using quarterly trade data, we estimated Japanese beef demand by exporting source (e.g., Australia, U.S.) and product quality (chilled and frozen). We used different models based on assumptions about quality (unrestricted, quality aggregated, and quality separability) and compared the demand estimates and resulting elasticities across models. The importance of quality was also verified by separability and aggregation likelihood-ratio tests.Results indicate that quality matters. In fact, likelihood-ratio tests indicate that preferences for chilled and frozen beef may even be independent. That is, the demand for chilled beef imports could be estimated separately from frozen beef imports. However, resulting elasticity estimates did not significantly differ when quality attributes were considered, except for U.S. chilled beef where the own-price elasticity was statistically different between the unrestricted model (−0.4) and quality-aggregated model (−1.2). However, we found no significant difference between the elasticities from the quality-separability and quality-aggregated models regardless of source. Results provide insights into Japanese beef import demand, which is important considering Japan is the third largest beef importer in the world.

Haojie Wang, Jiuyun Jiang, L. Jeff Hong et al.

The development of large language models (LLMs) has provided new tools for research in supply chain management (SCM). In this paper, we introduce a retrieval-augmented generation (RAG) framework that dynamically integrates external knowledge into the inference process, and develop a domain-specialized SCM LLM, which demonstrates expert-level competence by passing standardized SCM examinations and beer game tests. We further employ the use of LLMs to conduct horizontal and vertical supply chain games, in order to analyze competition and cooperation within supply chains. Our experiments show that RAG significantly improves performance on SCM tasks. Moreover, game-theoretic analysis reveals that the LLM can reproduce insights from the classical SCM literature, while also uncovering novel behaviors and offering fresh perspectives on phenomena such as the bullwhip effect. This paper opens the door for exploring cooperation and competition for complex supply chain network through the lens of LLMs.

Alessandro Ferrari, Lorenzo Pesaresi

We study how product specialization choices affect supply chain resilience. We propose a theory of supply chain formation in which only compatible inputs can be used in final production. Intermediate producers choose how much to specialize their goods, trading off higher value added against a smaller pool of compatible final producers. Final producers operate complex supply chains, requiring multiple complementary inputs. Specialization choices determine how quickly final producers can replace suppliers after disruptions, and thus supply chain resilience. In equilibrium, production inputs are over-specialized due to a novel network externality. Intermediate producers fail to internalize how their specialization choices affect the likelihood that final producers source all required inputs, and therefore the lost value added from complementary inputs if production halts. As a result, supply chains are more productive in normal times but less resilient than socially desirable. We characterize the optimal transfer that restores the efficient allocation and show that non-fiscal interventions, such as compatibility standards, are generally welfare-enhancing.

Junguo Hua, Chunhui Ma, Wei Li et al.

IntroductionWith the rapid development of digital agriculture, digitalization has gradually become a key factor affecting the resilience of China’s pig farming industry.MethodsFrom both the test results and the theoretical point of view, the individual fixed-effect model is more suitable for this paper’s study. Therefore, based on the panel data of 31 provinces in China from 2011 to 2022, this study constructs an individual fixed-effect model to examine how digitization affects the resilience of China’s pig farming industry.Results and discussionThe findings indicated that digitization significantly enhanced the resilience of China’s hog breeding industry, especially in potential growth areas. Improving breeding technology and scale is a crucial avenue for digitalization to bolster the industry’s resilience. Digitalization exerts a double threshold effect on the industry’s resilience, with its promotional impact only realized within a specific range. The article proposes policy suggestions, such as strengthening infrastructure construction and giving play to regional advantages.

Yohannes Girma Asefa, Abera Ayalew Muluken

Even if smallholder farmers have a large share in the Ethiopian economy, they operate below their potential. Land use is fundamental in determining the efficiency of farmers. However, the effect of land size on efficiency is still a controversial issue in the country. This review was designed to determine the effect of land size on farmers’ efficiency. The random-effects model showed that the farmers with smaller land sizes (≤0.5 ha) were more efficient by 21% than the farmers with larger land sizes. Moreover, the results of meta-regression analysis showed that resource endowment, labor quality, information contact, and total income were the important moderators of the presence of heterogeneity in the effect size among the studies. It was deduced that farmers are efficient with smaller land sizes since they have resources to manage their farms appropriately. Therefore, improving farmers’ production skills, providing input subsidies, and upgrading development agents’ skills are crucial to boost farmers’ efficiency in the country.

Simona Piccolella, Marika Fiorentino, Giovanna Cimmino et al.

In the framework aimed at evaluating the close link between the chemical composition of poorly explored organs of local edible medicinal plants in the Cilento region (Southern Italy) and their recovery for new health products, Cichorium intybus L. was of interest. Ultra-High Performance Liquid Chromatography Quadrupole-Time-Of-Flight tandem Mass Spectrometry (UHPLC-QqTOF-MS/MS) investigation revealed that sesquiterpene lactones characterized roots and stems, while hydroxycinnamic derivatives accumulated in florets, bracts, and leaves. Florets diverged for anthocyanin derivatives, while roots differed by low flavonoid content. Despite shared phytochemical constituents, their ratio was responsible for different antioxidant responses. Notably, extracts, particularly rich in hydroxycinnamoyl derivatives, showed protective effects against oxidative stress induced by hydrogen peroxide in SH-SY5Y and HaCaT cell lines. The wound healing assay revealed marked inhibition of SH-SY5Y cell migration, avoiding wound closure. Overall, the research encourages the use of different organs from Cilentan wild chicory to obtain antioxidant safe and consumer-guaranteed products.

Dwi Budiningsari, Yeni Prawiningdyah, Joko Prianto et al.

Latar Belakang: Penyakit yang disebabkan oleh makanan merupakan masalah yang signifikan di tingkat global, di mana makanan yang terdapat di lembaga pendidikan menjadi sumber keracunan makanan di Indonesia. Kurangnya perhatian akan kebersihan dan sanitasi oleh para penjamah makanan merupakan faktor utama, yang sering kali disebabkan oleh bias optimis, yang menyebabkan rendahnya perhatian terhadap prosedur yang sesuai dalam pengolahan dan penyajian makanan. Tujuan: Menganalisis pengetahuan dan sikap keamanan pangan dan hubungannya dengan bias optimis pada penjamah makanan di kantin SMA Negeri Kota Magelang. Metode: Penelitian yang menggunakan desain potong lintang ini diikuti oleh 41 orang responden yaitu keseluruhan penjamah makanan yang bekerja di kantin lima SMA Negeri Kota Magelang. Variabel bebas yaitu pengetahuan dan sikap keamanan pangan, sedangkan variabel terikat yaitu bias optimis. Kategori variabel pengetahuan keamanan pangan terdiri dari pengetahuan keamanan pangan baik dan buruk. Sikap keamanan pangan dikategorikan sebagai sikap positif dan sikap negatif. Kategori variabel bias optimis terdiri dari bias optimis tinggi, mungkin, dan rendah. Uji korelasi Spearman digunakan sebagai metode analisis statistik pada penelitian ini. Hasil: Hubungan pengetahuan dan sikap keamanan pangan dengan bias optimis pada penjamah makanan di kantin SMA Negeri Kota Magelang menghasilkan p-value=0,704 dan 0,498. Kesimpulan: Pengetahuan dan sikap keamanan pangan tidak berkorelasi signifikan dengan bias optimis pada penjamah makanan di kantin SMA Negeri Kota Magelang. Pelatihan keamanan pangan bekerja sama dengan dinas kesehatan sangat dibutuhkan untuk meningkatkan mutu produk yang dihasilkan.

Chala G. Kuyu, Asamnew Hailu Abebe, Tizazu Y. Bereka et al.

Teff is a gluten-free cereal crop widely cultivated in Ethiopia and is a critical ingredient in making injera, a unique flatbread. However, there is a significant issue with adulteration of teff, impacting its safety and quality. This study evaluated economically-driven adulteration effects on teff grains' nutritional and microbial quality. A preliminary survey revealed that it is a common practice to adulterate teff grains with inexpensive and inedible materials throughout the supply chain in the study area. One hundred and thirty teff grain samples were collected from producers, collectors, whole-sellers, and retailers in the cities of Tulu bolo and Jimma to determine the types and extents of adulterants present and their effect on the nutritional and microbial quality of the grains. They were mixed separately to create composite samples representing different supply chain actors. Standard protocols were used to evaluate nutritional and microbial quality. The results showed significant differences among the supply chain actors regarding identified adulterants, nutritional content, and microbial quality. The study identified chaff, soil + sand, and dukkaa (a combination of nonedible substances separated from teff grains in milling houses and warehouses) as the significant adulterants, with mean ranges of 1.17–8.07%, 1.29–7.23%, and 8.93–37.13% respectively. The study also evaluated the proximate composition and microbial load of the teff samples collected from different supply chain actors. The ranges of values for moisture, protein, fat, ash, fiber, carbohydrate, and energy were 8.33–10.53%, 6.49–9.42%, 2.29–3.86%, 2.33–6.39%, 2.42–3.95%, 70.9–73.76%, and 333.52–361.9 kcal, respectively. The microbial load showed ranges of 6.92–7.98, 3.17–3.22, 1.78–2.04, 6.73–7.89, and 6.88–7.93 log CFU/g for Total Plate Count, Escherichia coli, Salmonella, mold, and yeast, respectively. The results showed an increase in teff adulteration from producers to Jimma retailers, indicating multiple-stage adulteration throughout the supply chain, posing a threat to product safety and quality. The study recommends good coordination among the bodies responsible for food safety, producers, and consumers to mitigate this issue effectively.

Azam Ashrafi, Hamed Ahari, Gholamhassan Asadi et al.

This study aimed to assess the impact of an edible coating holding within chia seed gum (CSG) and Rosa canina L. extract (RCE) nanoemulsions (10%, 20%, and 40% w/w) on the oxidation, microbial load, and sensory characteristics of burgers in a 90-day frozen storage period. Based on the findings, the active CSG coatings showed remarkable antioxidant and antimicrobial activities. By increasing the level of RCE nanoemulsions, the functional activity of coatings significantly increased (P < 0.05). Upon the termination of the storage period, the lowest microbial load (i.e., a decrease of 0.5–2 log CFU/g in the number of different bacteria compared to the control) and oxidation stability were observed in burgers coated with a CSG solution containing 40% RCE nanoemulsions. This burger also showed the highest sensory acceptance on the last day. In conclusion, it is proposed to use the active coating produced in this study to maintain meat products' quality and safety and increase their shelf-life.

Ermias Debie

IntroductionThe adoption of climate-smart agriculture practices (CSAPs) at the plot level is a promising yet underutilized strategy in Ethiopia, where subsistence farming predominates. This study investigates the factors influencing the intensity of CSAPs on homesteads and identifies key barriers to their broader adoption.MethodsQuantitative data were collected through household surveys. Multiple Linear Regression (MLR) analysis was employed to examine the relationship between the independent variables and farmers' decisions to intensify CSAPs.ResultsThe findings reveal that slope gradient, extension contacts, farming experience, dependency ratio-induced labor, and livestock diversity significantly impact farmers' decisions to enhance CSAPs. Major barriers include insecure land tenure, poor management of open grazing, labor-intensive practices, and limited access to agricultural inputs.DiscussionTo promote the widespread implementation of CSAPs, it is imperative that these variables are prioritized in agricultural extension policies. Addressing these barriers is essential for enhancing the adoption of CSAPs, which will significantly contribute to sustainable agricultural development in Ethiopia.

Samia Valeria Ozorio Dutra, Samia Valeria Ozorio Dutra, Samia Valeria Ozorio Dutra et al.

IntroductionVery Low Birth Weight (VLBW) infants, born weighing less than 1,500 grams, are at risk for both gut dysbiosis and later neuropsychological developmental deficits. Behavioral effects, while related to neurodevelopment, are often more subtle and difficult to measure. The extent of later neurobehavioral consequences associated with such microbial dysbiosis has yet to be determined. We explored associations between the infants’ gut microbiome and early childhood behavior at 4 years of age and identified the bacterial taxa through a multivariate analysis by linear models.MethodsParents completed the Child Behavior Checklist (CBCL) focused on different DSM diagnostic categories: affective, anxiety, pervasive developmental, attention deficit/hyperactivity, and oppositional defiant. All the CBCL scores were corrected for gender, delivery method, gestational age, infant birth weight, occurrence of sepsis, and days on antibiotics prior statistical analyses. Canonical correlation analysis (CCA) was performed to determine the relationship between early life gut microbiome and the adjusted CBCL scores. The association of bacterial Amplicon sequence Variants (ASVs) to the CBCL scores were tested with multivariate analysis by linear models (MaAsLin).ResultsNineteen children who were previously born with very low birth weight and studied while hospitalized in the Neonatal Intensive Care Unit (NICU) were included in this study. Statistically significant associations were observed between early life gut bacteria such as Veillonella dispar, Enterococcus, Escherichia coli, and Rumincococcus to later behavior at 4 years. No significant association could be observed with early-life gut microbiome alpha diversity and behavioral measures at 4 years.DiscussionThese preliminary observational data provide insight into the relationships between VLBW gut microbiome dysbiosis and childhood behavior. This study contributes to the literature on gut microbiome analysis by examining various behavioral domains using a standardized tool linked to the Diagnostic and Statistical Manual of Mental Disorders (DSM).

Tianshi Li, Lorrie Faith Cranor, Yuvraj Agarwal et al.

Apple and Google introduced their versions of privacy nutrition labels to the mobile app stores to better inform users of the apps' data practices. However, these labels are self-reported by developers and have been found to contain many inaccuracies due to misunderstandings of the label taxonomy. In this work, we present Matcha, an IDE plugin that uses automated code analysis to help developers create accurate Google Play data safety labels. Developers can benefit from Matcha's ability to detect user data accesses and transmissions while staying in control of the generated label by adding custom Java annotations and modifying an auto-generated XML specification. Our evaluation with 12 developers showed that Matcha helped our participants improved the accuracy of a label they created with Google's official tool for a real-world app they developed. We found that participants preferred Matcha for its accuracy benefits. Drawing on Matcha, we discuss general design recommendations for developer tools used to create accurate standardized privacy notices.

Forkan Uddin Ahmed, Annesha Das, Md Zubair

The development of an intelligent agricultural decision-supporting system for crop selection and disease forecasting in Bangladesh is the main objective of this work. The economy of the nation depends heavily on agriculture. However, choosing crops with better production rates and efficiently controlling crop disease are obstacles that farmers have to face. These issues are addressed in this research by utilizing machine learning methods and real-world datasets. The recommended approach uses a variety of datasets on the production of crops, soil conditions, agro-meteorological regions, crop disease, and meteorological factors. These datasets offer insightful information on disease trends, soil nutrition demand of crops, and agricultural production history. By incorporating this knowledge, the model first recommends the list of primarily selected crops based on the soil nutrition of a particular user location. Then the predictions of meteorological variables like temperature, rainfall, and humidity are made using SARIMAX models. These weather predictions are then used to forecast the possibilities of diseases for the primary crops list by utilizing the support vector classifier. Finally, the developed model makes use of the decision tree regression model to forecast crop yield and provides a final crop list along with associated possible disease forecast. Utilizing the outcome of the model, farmers may choose the best productive crops as well as prevent crop diseases and reduce output losses by taking preventive actions. Consequently, planning and decision-making processes are supported and farmers can predict possible crop yields. Overall, by offering a detailed decision support system for crop selection and disease prediction, this work can play a vital role in advancing agricultural practices in Bangladesh.

Hyung-il Ahn, Santiago Olivar, Hershel Mehta et al.

Supply chain networks in enterprises are typically composed of complex topological graphs involving various types of nodes and edges, accommodating numerous products with considerable demand and supply variability. However, as supply chain networks expand in size and complexity, traditional supply chain planning methods (e.g., those found in heuristic rule-based and operations research-based systems) tend to become locally optimal or lack computational scalability, resulting in substantial imbalances between supply and demand across nodes in the network. This paper introduces a novel Generative AI technique, which we call Generative Probabilistic Planning (GPP). GPP generates dynamic supply action plans that are globally optimized across all network nodes over the time horizon for changing objectives like maximizing profits or service levels, factoring in time-varying probabilistic demand, lead time, and production conditions. GPP leverages attention-based graph neural networks (GNN), offline deep reinforcement learning (Offline RL), and policy simulations to train generative policy models and create optimal plans through probabilistic simulations, effectively accounting for various uncertainties. Our experiments using historical data from a global consumer goods company with complex supply chain networks demonstrate that GPP accomplishes objective-adaptable, probabilistically resilient, and dynamic planning for supply chain networks, leading to significant improvements in performance and profitability for enterprises. Our work plays a pivotal role in shaping the trajectory of AI adoption within the supply chain domain.

Zhengdong Luo

Supply Chain Finance is very important for supply chain competition, which is an important tool to activate the capital flow in the supply chain. Supply Chain Finance-related research can support multiple applications and services, such as providing accounts receivable financing, enhancing risk management, and optimizing supply chain management. For more than a decade, the development of Blockchain has attracted widely attention in various fields, especially in finance. With the characteristics of data tamper-proof, forgery-proof, cryptography, consensus verification, and decentralization, Blockchain fits well with the realistic needs of Supply Chain Finance, which requires data integrity, authenticity, privacy, and information sharing. Therefore, it is time to summarize the applications of Blockchain technology in the field of Supply Chain Finance. What Blockchain technology brings to Supply Chain Finance is not only to alleviate the problems of information asymmetry, credit disassembly, and financing cost, but also to improve Supply Chain Finance operations through smart contracts to intelligent Supply Chain Finance and in combination with other technologies, such as artificial intelligence, cloud computing, and data mining, jointly. So there has been some work in Blockchain-based Supply Chain Finance research for different Supply Chain Finance oriented applications, but most of these work are at the management level to propose conceptual frameworks or simply use Blockchain without exploiting its deep applications. Moreover, there are few systematic reviews providing a comprehensive summary of current work in the area of Blockchain-based Supply Chain Finance. In this paper, we ...

Wang-Yu Zhu, Yu-Mei Wang, Ming-Xue Ge et al.

BackgroundExceeding 50% tuna catches are regarded as byproducts in the production of cans. Given the high amount of tuna byproducts and their environmental effects induced by disposal and elimination, the valorization of nutritional ingredients from these by-products receives increasing attention.ObjectiveThis study was to identify the angiotensin-I-converting enzyme (ACE) inhibitory (ACEi) peptides from roe hydrolysate of Skipjack tuna (Katsuwonus pelamis) and evaluate their protection functions on H2O2-induced human umbilical vein endothelial cells (HUVECs).MethodsProtein hydrolysate of tuna roes with high ACEi activity was prepared using flavourzyme, and ACEi peptides were isolated from the roe hydrolysate using ultrafiltration and chromatography methods and identified by ESI/MS and Procise Protein/Peptide Sequencer for the N-terminal amino acid sequence. The activity and mechanism of action of isolated ACEi peptides were investigated through molecular docking and cellular experiments.ResultsFour ACEi peptides were identified as WGESF (TRP3), IKSW (TRP6), YSHM (TRP9), and WSPGF (TRP12), respectively. The affinity of WGESF (TRP3), IKSW (TRP6), YSHM (TRP9), and WSPGF (TRP12) with ACE was −8.590, −9.703, −9.325, and −8.036 kcal/mol, respectively. The molecular docking experiment elucidated that the significant ACEi ability of WGESF (TRP3), IKSW (TRP6), YSHM (TRP9), and WSPGF (TRP12) was mostly owed to their tight bond with ACE’s active sites/pockets via hydrophobic interaction, electrostatic force and hydrogen bonding. Additionally, WGESF (TRP3), IKSW (TRP6), YSHM (TRP9), and WSPGF (TRP12) could dramatically elevate the Nitric Oxide (NO) production and bring down endothelin-1 (ET-1) secretion in HUVECs, but also abolish the opposite impact of norepinephrine (0.5 μM) on the production of NO and ET-1. Moreover, WGESF (TRP3), IKSW (TRP6), YSHM (TRP9), and WSPGF (TRP12) could lower the oxidative damage and apoptosis rate of H2O2-induced HUVECs, and the mechanism indicated that they could increase the content of NO and activity of superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px) to decrease the generation of reactive oxygen species (ROS) and malondialdehyde (MDA).ConclusionWGESF (TRP3), IKSW (TRP6), YSHM (TRP9), and WSPGF (TRP12) are beneficial ingredients for healthy products ameliorating hypertension and cardiovascular diseases.