Search Results (1,060)

The accurate prediction of parturition in managed beluga whales (Delphinapterus leucas) is fundamental for optimizing maternal and neonatal care; however, reliable predictive indicators remain limited. Here, eight pregnancies (five live births and three adverse pregnancy outcomes) monitored over 25 years at a single facility were retrospectively analyzed. The rectal temperatures, serum progesterone concentrations, gestation lengths, food intake, behavioral changes, and fetal heart rates of the whales were evaluated, particularly prepartum. Five successful pregnancies exhibited consistent seasonal timing and reproducible endocrine and physiological trajectories. The mean gestation length was 466 ± 8.4 days. The rectal temperatures of dams that delivered live offspring decreased by 1.6 ± 0.5 °C approximately 1.3 ± 0.5 days before parturition. In successful pregnancies, serum progesterone concentrations declined prepartum but typically remained detectable until parturition. In contrast, a concentration of approximately 1 ng/mL prior to parturition was observed in the pregnancy that resulted in stillbirth. Adverse pregnancy outcomes were associated with deviations from the patterns observed in successful pregnancies, including abnormal gestation length, notably reduced progesterone concentrations, altered fetal heart rate trajectories, and ultrasonographic evidence of fetal cranial asymmetry. These findings highlight the importance of integrated multimodal monitoring in predicting parturition and identifying abnormal pregnancy progression in managed beluga whales. Full article

Climate warming and the increasing frequency of extreme climate events have exerted a systemic shock on global Agricultural Production Resilience (APR). Clarifying the impact mechanism is essential to ensuring global food security. This study employs a cross-country network meta-analysis framework. We systematically synthesize 76 empirical studies published between 2005 and 2025. This paper aims to quantify the impacts of five climatic factors on APR. These factors include extreme high temperature, extreme drought, extreme flooding, precipitation variability, and temperature anomaly. Heterogeneity and moderating effects across latitudinal regions, agricultural production modes, agricultural structures, and irrigation conditions are examined, followed by robustness tests and publication bias analysis. The results show that: (1) At a cross-country scale, all five climatic factors have significant negative impacts on APR. The intensity of impact ranks in descending order as extreme flooding, extreme high temperature, extreme drought, precipitation variability, and temperature anomaly, with extreme climates as the dominant risk factor. (2) The impact effects exhibit significant latitudinal heterogeneity. The absolute value of adverse shocks to APR in low-latitude regions is markedly larger than that in mid- and high-latitude countries; extreme floods constitute the primary risk for low-latitude areas, while extreme high temperatures dominate mid- and high-latitude regions. (3) Rain-fed agriculture and crop farming suffer substantially stronger climatic impacts than irrigated agriculture and animal husbandry. (4) Agricultural structure and production modes exert prominent moderating effects. A higher share of crop cultivation and rain-fed farmland corresponds to stronger adverse climatic impacts, whereas animal husbandry, facility agriculture, and well-developed irrigation facilities can partially mitigate such disturbances. This study provides empirical evidence for countries and regions to implement differentiated adaptation policies within agricultural climate governance frameworks and enhance APR. Full article

Peri-urban regions around Southeast Asian megacities connect agriculture, markets, food-service facilities, households, and municipal waste systems, yet comparable data for individual waste streams are often unavailable. This study presents a screening framework for selecting the first organic waste streams and node types to measure in Tangerang Raya, Indonesia, before treatment performance data are available. The framework complements, rather than replaces, city scale circularity monitoring, life cycle assessment, and technology selection tools. Public and institutional data were screened by evidence class and temporal and spatial compatibility. The core Peri-Urban Organic Waste Circularity Readiness Index (PU-OCRI) evaluates five intrinsic criteria: feedstock concentration, source separation readiness, treatment pre-screening compatibility, institutional readiness, and the safety/quality gate. Scores represent collective author judgments linked to a criterion level evidence trail; they have not been independently rated by local stakeholders or empirically calibrated. Korea linked support is assessed separately and cannot affect the index. Available evidence included 3248.1 t of large chili production in Kabupaten Tangerang in 2024, 798,406 t yr⁻¹ of reported potential municipal-waste generation in Kota Tangerang in 2024, and a planning-based estimate that 52.89% of non-residential waste in Kota Tangerang Selatan was biogenic organic material. Under equal weights, market-linked organics scored 76/100 and garden and landscape organics 72; production-side residues and household food waste each scored 56, and mixed residual waste scored 32. In 100,000 weight only simulations, market linked organics ranked first in 65.9% of runs and garden and landscape organics in 31.2%. When each score was allowed to vary by one point and sampled together with the weights, the corresponding first-rank frequencies were 50.7% and 40.7%. These results define a provisional paired audit hypothesis, not evidence of superior circular-economy performance. A required 8–12-week comparison of market/food-service and garden/landscape nodes will apply predefined criteria for mass stability, contamination, safety, treatment feasibility, cost, and operator and stakeholder participation before scores are updated or any treatment or scale-up decision is made. Korea-linked cooperation is limited to digital logging, training, QA/QC, and pilot-operation protocols. Data provenance is explicit: the 798,406 t yr⁻¹ value is the issuing agency’s population × per-capita estimate, whereas 52.89% is an author calculated category sum (kitchen + garden + wood) used only as a screening proxy, not as a direct stream level measurement or the plan’s official aggregate organic fraction. Full article

Background: Oil-in-water nanoemulsions (NEs) represent versatile platforms for the delivery of hydrophobic compounds and find a wide range of applications in different fields such as food, cosmetics, agriculture, pharmaceutics, and oil and gas industries. Various methodologies can be applied for the preparation of NEs as low-energy and high-energy methods. Among them, high-energy ultrasonication (HEU) is a popular technique in research laboratories or small manufacturing facilities. However, a clear gap remains in understanding how, and to what extent, experimental parameters and the chemical and physical characteristics of the components affect the formation and properties of NEs through HEU. Methods: In this work, a comprehensive screening of factors (oil viscosity and density, surfactant type, processing parameters, and formulation composition) affecting NEs formation and quality was performed and an artificial neural network (ANN) was applied to determine the relative relevance of each parameter. Results: Oil viscosity revealed to be the primary factor affecting droplet size (Z_avg) and polydispersity index (PDI), with high-viscosity oils leading to poor emulsification into nanosized droplets. Higher processing temperatures improved NE formation by reducing viscosity during sonication. Ultrasound amplitude and pulse mode influenced NE characteristics, particularly under challenging conditions. Surfactant type and oil content had, instead, minor effects on the NEs’ features. ANN modelling accurately predicted NEs’ properties and identified critical viscosity limits for successful nanosized emulsification (Z_avg < 300 nm and PDI < 0.4). Conclusions: These findings provide a predictive basis for rational NE design under HEU, serving as a guide for researchers working in different fields. Full article

Improved varieties strengthen cassava’s roles as both a food security staple and a versatile industrial raw material across the tropical regions where it is produced. In support of this effort the International Center for Tropical Agriculture (CIAT) curates the world’s largest cassava germplasm collection at its Cali, Colombia, research center. Since the first collection expeditions in 1969, a primary focus was to assemble and conserve the diversity from the crop’s center of origin in the American tropics. Later additions expanded representation from Asia and Africa as secondary centers of diversity. The collection now consists mainly of landraces (about 5000 accessions), bred lines from CIAT (375) and from partner institutions (253), and related wild Manihot (377 accessions from 23 species or subspecies). Landrace diversity originated and evolved almost entirely through occasional farmer selections from seed-derived plants, which were subsequently conserved clonally over many generations. Secure ex situ conservation, first as a field collection and then in a slow-growth in vitro system, gave priority to pathogen testing and reliable culture and exchange methods. Cryopreservation research is ongoing to achieve added security and efficiency. CIAT extensively characterizes accessions through morphological, biochemical and molecular criteria. As a core goal, the collection has been a foundation for genetic improvement of the crop globally. This paper provides perspectives on the future management and use of the collection in the context of the recently established Future Seeds genebank facilities in Colombia, and new tools and technologies that support more effective conservation, evaluation and use. Full article

Food safety training is a cornerstone of foodborne disease prevention in collective catering, particularly in settings serving vulnerable populations. This study aimed to assess baseline food safety knowledge and evaluate the effectiveness of a food safety training session among food handlers employed in school cafeterias and residential care facilities (RSAs) collective catering. A pre–post design was applied to 168 participants who completed a structured knowledge questionnaire before and after training. At baseline, only 31% of participants achieved a passing score. Knowledge levels were significantly associated with primary job role (p < 0.001): food preparers and managers were more likely to pass compared with food service workers involved mainly in meal distribution. In multivariate analysis, both job role and catering setting remained independently associated with test performance. Following the training session, the proportion of participants passing the test increased to 74% (p < 0.001), and differences between professional categories were reduced. These findings indicate that food safety knowledge in collective catering could vary according to occupational role and organizational context, but can be improved through training. Role-tailored, HACCP-based educational programs could be essential to strengthen compliance and protect vulnerable populations in institutional catering settings. Full article

A sustainable cost optimization framework for the bioethanol supply chain is developed, using household food waste as a renewable feedstock. Unlike previous studies that mainly focus on agricultural residues, algae, or industrial biomass, this research addresses the specific logistical and economic challenges associated with household food waste, including decentralized generation, perishability, transportation complexity, and variable supply patterns. The proposed mathematical model incorporates key supply chain costs, including waste purchasing, handling, transportation, storage, processing, and facility installation, to minimize the total operational cost of the supply chain network. A genetic algorithm-based optimization approach is applied to determine the optimal configuration of collection centres, processing facilities, and distribution hubs subject to operational and capacity constraints. The numerical results indicate that the proposed framework improves supply chain efficiency while reducing overall system cost. The findings suggest that household food waste can serve as a sustainable and economically viable resource for decentralized bioethanol production and environmentally sustainable urban waste management. Full article

Egon Steinmann’s industrial architecture represents a significant yet insufficiently researched contribution to the development of post-war industrial architecture in Croatia. This paper examines his industrial projects designed between 1947 and 1965 within the context of post-war industrialization and modernization in socialist Yugoslavia. Based on archival documents, historical photographs, field observations, and comparative analysis, the paper first identifies Steinmann’s broader industrial work and then examines six selected industrial complexes in Zagreb. The case studies are compared in terms of their urban context, spatial organization, structural systems, production logistics, daylighting strategies, and architectural expression, highlighting differences between heavy industrial facilities and food-processing plants. A comparison of historical and contemporary orthophotos is further used to evaluate the long-term spatial transformation and adaptability of these industrial sites. The findings demonstrate that Steinmann’s designs were characterized by rational planning, large-span and flexible structures, integration of technological and transport requirements, and the capacity for phased expansion. The continued industrial use and preservation of many of these complexes confirm the lasting value of his architectural and planning concepts, contributing to a broader understanding of Croatian industrial architecture and socialist industrial modernism of the 1950s and 1960s. Full article

The digital transformation of agrifood systems demands an integrated infrastructure to ensure traceability, trust, and intelligent decision-making across complex and heterogeneous value chains. METROFOOD-IT, a large-scale national research infrastructure in food metrology aligned with the ESFRI METROFOOD-RI, addresses these challenges by combining advanced experimental facilities with a comprehensive digital ecosystem. This paper focuses on the IT kernel of METROFOOD-IT and presents an integrated architectural model that brings together four key technological paradigms: data acquisition through Internet of Things (IoT) and laboratory infrastructures, an Open Data Platform for interoperability and sharing, blockchain-based notarization for integrity and provenance, and Artificial Intelligence (AI) for knowledge extraction and decision support. Rather than describing these components in isolation, the paper abstracts from their implementation within the Italian National Recovery and Resilience Plan (NRRP) project METROFOOD-IT to distill a coherent and reusable architectural pattern in which data management, trust enforcement, and intelligent analytics are tightly coupled. Five explicit design principles are identified and articulated: federated data with centralized metadata, selective on-chain anchoring, user-unobtrusive trust infrastructure, explainability as a first-class architectural concern, and machine learning as the backbone of decision-making. Two empirical case studies—one centered on explainable AI for hyperspectral crop nitrogen assessment and the other on IoT-driven sustainable agriculture monitoring secured by distributed ledger technology—serve a dual role: they motivate and shape the architectural pattern, and they exemplify the operational regimes the resulting design supports. A reference deployment on the Ethereum Sepolia public test network, grounded on an IBM Power E1050 and IBM Storage Scale enterprise substrate, provides quantitative evidence for the proposed hybrid on-chain/off-chain pattern with streaming hash-only notarization. The architecture illustrates how research infrastructures can evolve into integrated digital platforms that enable transparent, verifiable, and scalable agrifood systems, and offers a foundation for generalizable design principles in data-intensive and trust-sensitive settings. Full article

Soil erosion (SE) is a constant, complex land degradation process, a common natural disaster that occurs all over the world and severely impacts soil fertility, food security, and environmental balance. Soil erosion depends on many factors, including soil properties, slope, vegetation, rainfall amount and intensity, and anthropogenic activities. There are two main natural erosive forces by which soil is eroded and transported—water and wind. Water erosion refers to the detachment, transportation, and deposition of soil particles (solid runoff) into river networks. These particles, varying in size and composition, are the main products of soil erosion and most strongly affect river ecosystems. Solid runoff, or sediment-laden runoff, affects water quality, destroying habitats, carrying pollutants, reducing reservoir storage, and causing flooding. Erosion control activities also influence river ecosystems in different ways. Hydrotechnical facilities, a major erosion control practice, can alter the composition of aquatic biota by disrupting longitudinal connectivity and isolating populations. Reforestation and afforestation are other erosion control practices that have a strong impact on ecosystems. Stormwater retention systems in urban and forest areas are also important measures addressed in this review. This review examines complex environmental interactions and the roles of erosion and erosion control activities in river ecosystems. During the research, several key points were established: erosion and erosion control activities significantly affect river ecosystems. There is a lack of quantitative analysis of erosion intensity and its influence on ecosystems. This is probably due to the exceptional complexity and diversity of river ecosystems, but such a study would provide important information about complex relationships in nature. Full article

Background/Objectives: Due to the rise in chronic disease in the United States, several policies, guidelines, and programs have focused on promoting healthy eating. This includes those aimed at service members, who may struggle to find nutritious food options on military bases. The Military Nutrition Environment Assessment Tool (mNEAT) assesses the access, availability, and promotion of nutritious foods and beverages on military bases. Military services vary in their policies related to the food environment, including the use of mNEAT, on their installations. The aim of this article is to examine the difference in mNEAT scores for those military services with a comprehensive mNEAT policy compared to those with a partial policy. Methods: Installations with mNEAT scores from October 2021 to September 2024 were separated into two groups: full-policy group (Air Force, Space Force, n_f = 76) and partial-policy group (Army, Navy, Marine Corps, n_p = 69). Food venue types assessed include: commissary (n_f = 67, n_p = 44); fast-food (n_f = 63, n_p = 48); vending (n_f = 42, n_p = 18); express stores (n_f = 65, n_p = 50); food truck (n_f = 42, n_p = 24); dining facility/galley (n_f = 51, n_p = 40); Morale, Welfare, and Recreation (MWR) food service venues (n_f = 56, n_p = 38). Installation-level venue types assessed include community (n_f = 56, n_p = 24) and worksite (n_f = 49, n_p = 20). Installations were separated into venue-type variety groups according to how many different venue types they assessed: low (1–4 venue types, n = 47), moderate (5–7 venue types, n = 48), and high (8–9 venue types, n = 50). Results: The full-policy group had higher total installation mNEAT scores on average than the partial-policy group (54.6% vs 50.4%, p = 0.034), but results were no longer significant when venue type assessment variety was added as a covariate (p = 0.074). In addition, the full-policy group had higher scores (p ≤ 0.05) for the following venue types: dining facility/galley, MWR, fast-food, express, and community. In the moderate (p = 0.012) and high (p = 0.022) venue-type variety groups, the full-policy group had significantly higher mNEAT scores, but not for the low venue-type variety group (p = 0.547). Conclusions: Higher mNEAT scores for full-policy installations may indicate a more supportive food environment than those in the partial-policy group, when ≥5 food venue types were assessed. Military services without a comprehensive mNEAT policy can consider modifying or implementing one to support easier access and availability of nutritious options. This public health strategy can support service members’ health and performance and can be applied to similar settings, such as universities and worksites. Full article

The high-rate biological contactor (HRBC) is an enhanced-primary, biosorption-based, carbon-diversion wastewater treatment process with short hydraulic retention time (HRT), short solids retention time (SRT), low dissolved oxygen (DO), and high food-to-microorganism ratio (F/M). This paper presents modifications to a commercial full-plant wastewater biodegradation model using extracellular polymeric substances (EPS) in waste activated sludge (WAS) to simulate pilot test biosorption data. Bench-scale HRBC tests found that each mg of EPS as COD (COD_EPS) biosorbed 1.02 mg sCOD contained in raw wastewater. The fraction of AS organics identified as EPS in terms of COD was 37% in a conventional AS (CAS), 33% in a trickling filter-solids contact (TF/SC), and 18% in a membrane bioreactor (MBR). The modeling process used stoichiometry equations to convert EPS from its constituent concentrations (carbohydrates, proteins, humic acids, uronic acids) into COD. The conversion did not alter the finding that the normalized total EPS showed a positive relationship with soluble chemical oxygen demand sCOD biosorption with a 0.91 coefficient of determination. The modified commercial biodegradation model gave a maximum error of −12.6% when simulating pilot-scale results, and 80% of all data points were less than ±10% error. The modified model predicted 16% sCOD biosorption by EPS using the design data for a full-scale HRBC facility currently under construction. Full article

This study presents a gate-to-gate life cycle assessment (LCA) of an industrial sweet cherry sorting and packing facility in Greece, directly addressing environmental sustainability in agri-food supply chains through data-driven impact quantification and improvement pathways in post-harvest operations. The assessment focuses on a gate-to-gate system boundary encompassing all processes inside the cherry sorting and packing facility, while upstream cherry production and downstream waste management are modeled and reported separately to provide system-level context. Core-stage hotspots are then analyzed in detail in the Results section, highlighting the dominant role of electricity use compared with packaging materials. The functional unit is defined as 1 kg of packed, market-ready cherries at the factory gate. Primary data are obtained from high-resolution, batch-level measurements of mass flows, energy use, water consumption, packaging materials and waste streams over a full processing season, structured as virtual sensor outputs. These sensor-informed operational data are combined with secondary life cycle inventory information from established databases to quantify climate change impacts and identify environmental hotspots across materials, energy, water, and waste, thereby delivering a quantified picture of environmental performance in the post-harvest stage. The results show that corrugated cardboard and associated packaging components are among the main contributors within the facility-level, gate-to-gate system, while the Core stage accounts for 28.43% of total GWP100. Upstream cherry production dominates the overall Upstream–Core–Downstream climate footprint with 70.61% of total impacts. Moreover, practical mitigation scenarios are modeled, including packaging optimization, partial substitution of grid electricity with photovoltaic generation, and increased water recirculation. Ιn the combined mitigation scenario, where packaging optimization, low-carbon electricity and improved water management are implemented simultaneously, total GWP100 decreases from 114,207.32 to 92,500.27 kg CO₂-eq (−19.0%) relative to the baseline, providing actionable sustainability improvements for industry stakeholders and supporting Sustainable Development Goals (SDGs) related to climate action and resource efficiency. In addition, the proposed virtual sensor architecture and data workflow support continuous monitoring, eco-efficiency management and near-real-time LCA implementation in post-harvest agri-food systems, enabling operational sustainability. Full article

Accurate quantification of glucose is vital for quality control in the food industry. While earth-abundant Cu has emerged as a promising candidate for non-enzymatic electrochemical sensing, conventional electrode fabrication relying on powder coating with polymeric binders inevitably buries active catalytic sites and impedes both electron transfer and mass transport. In this study, a binder-free, self-supporting Cu nanoparticles/Ni foam (Cu NPs/NF) electrode was developed via a facile one-step hydrothermal method. Benefitting from the enhanced charge-transfer efficiency and a substantially enlarged electrochemical active surface area, the Cu NPs/NF-based electrochemical glucose sensor exhibited a wide linear detection range (0.25–3310.52 μM), a high sensitivity of 7000 μA mM⁻¹ cm⁻², a low detection limit of 0.32 μM, and a rapid response time of 3 s. Furthermore, the developed Cu NPs/NF electrode displayed favorable reproducibility, storage stability, and high selectivity against common interferents present in food matrices, demonstrating its reliability for practical applications. The feasibility of the proposed sensor was successfully validated in real beverage samples. Given the simplicity of the one-step hydrothermal synthesis and the portability afforded by the self-supporting electrode architecture, this Cu NPs/NF electrode emerges as a highly attractive candidate for commercial glucose sensors. Beyond glucose, the design strategy can be readily extended to the detection of other electroactive food-quality markers, enabling the broader applicability of this electrode platform in comprehensive food analysis. Full article

Catechol, a prevalent phenolic pollutant in food products, poses a significant threat to food safety, necessitating the development of rapid and sensitive detection methods. To overcome the limitations of conventional analytical techniques, such as expensive equipment and operational complexity, electrochemical sensors have gained considerable attention owing to their rapid response and facile miniaturization. However, the rational design of sensing materials that exhibit both high sensitivity and selectivity remains a significant challenge. Herein, a series of PdCu bimetallic nanoparticles supported on reduced graphene oxide (PdCu@rGO) composites with varying Pd/Cu molar ratios was synthesized via a one-step liquid-phase reduction method. Owing to the synergistic electronic effects between Pd and Cu and the high electrical conductivity of the rGO support, the resulting nanocomposites exhibited excellent electrocatalytic activity toward catechol oxidation. At the optimal Pd/Cu molar ratio of 1:2, the fabricated Pd₁Cu₂@rGO/SPE sensor demonstrated a broad linear range of 0.5–500 μM, a low limit of detection of 200 nM (S/N = 3), good repeatability (RSD = 4.9%), and robust anti-interference capability. Furthermore, the proposed sensor was successfully applied to the detection of catechol in spiked green tea and fruit juice samples without complex pretreatment, achieving satisfactory recoveries of 91.0–101.4% and 98.6–104.8%, respectively. This work provides a reliable platform for the rapid, on-site screening of catechol in food matrices and offers valuable experimental insights into the rational design of bimetallic alloy–graphene heterostructures. Full article