Search Results (4,489)

Agriculture in the European Union operates in a context where productivity, output growth, and sustainability increasingly shape policy priorities and economic choices. This research explores how these elements have interacted and influenced one another from 2000 to 2024, focusing on the dynamic relationships among economic performance, sustainability, labor productivity, and agricultural output across EU member states. The methodology is straightforward: it starts with factor analysis to uncover the fundamental structures linking key variables and to clarify connections that are often hidden in aggregated data. Building on these insights, a General Linear Model provides a clearer picture of how economic performance and sustainability affect changes in labor productivity and agricultural output, revealing the mechanisms through which these factors promote or hinder agricultural progress. To enhance understanding, cluster analysis groups EU countries according to shared patterns, enabling interpretation of national differences within broader structural trends rather than as isolated cases. The findings show that countries with stronger economies and more consistent sustainability initiatives tend to achieve higher productivity and output, while the clusters identified demonstrate significant differences that explain the diverse development paths within the Union. Full article

Background/Objectives: Poor dietary habits are a major contributor to non-communicable diseases (NCDs), the leading cause of mortality worldwide. To promote healthier eating, governments and stakeholders have implemented various nutrition policies, including front-of-pack nutrition labeling (FOPNL). The Choices International Foundation (Choices), through its criteria, supports these efforts through its standardized nutrient profiling system (NPS). Originally developed to underpin a positive FOPNL logo, in 2021, the criteria were expanded into a globally oriented five-level profiling system covering 23 basic and 10 discretionary food groups, addressing key nutrients such as trans-fatty acids, saturated fat, sodium, sugar, fiber, and energy. To ensure continued scientific relevance, the Choices criteria are periodically reviewed by an independent International Scientific Committee (ISC). Methods: This paper presents the 2025 revision of the Choices criteria, focusing on priority areas identified through stakeholder consultation and recent scientific developments. Results: Key updates include the introduction of nutrient-based equivalence criteria for plant-based alternatives to meat and dairy, based on protein and selected micronutrient thresholds. Non-sugar sweeteners (NSSs) were newly included as a factor that lowers a product’s health classification and makes it ineligible for a positive FOPNL. Additionally, the industrially produced trans-fatty acid (iTFA) criteria were revised and aligned with the latest World Health Organization (WHO) recommendations, improving both technical feasibility and policy coherence. While options for incorporating whole-grain and micronutrient criteria were explored, these were not included in the current revision. Conclusions: The 2025 update system enhances the scientific rigor, policy alignment, and global applicability of the Choices system. By providing a harmonized and evidence-based tool, it aims to support national policies that foster healthier food environments and, ultimately, improve public health outcomes worldwide. Full article

Cassava is one of the most important crops in global food security. It is the second most important staple crop in Africa. Its significance is enhanced by the fact that it very well tolerates droughts, and therefore it may be a prospective response to climate change in hot and dry areas. The potentials of cassava are under-utilized in Eastern Africa, and there is a lack of research studies regarding climate impacts on cassava yields in this region. The present research focuses on cassava production in Eastern Africa, analyzing the relationship of cassava yields, harvested areas, temperature, and precipitation from 1961 to 2023. The statistical analysis applies panel regression for the 63 years of time series, for the 15 most important cassava producing countries of Eastern Africa. Findings show that while the impacts of rainfall are insignificant on yields, the effects of temperature are significantly positive, indicating yield and area increases with warming climate. An expansion of the cassava growing area and the expanding rural population contributed to decreasing yields, probably because of the expansion of smallholder subsistence farming, suffering from to limitations in other farming resources. Therefore, even if climate change may benefit cassava production, other factors create severe limitations on improving yields. However, the positive response of the crop to rising temperatures is a clear sign that it is a useful choice for food security under climate change and would deserve more support from agricultural policymakers in Eastern Africa. Full article

Considering the rapid iteration of you-only-look-once (YOLO)-series algorithms, this paper aims to provide a data-driven performance spectrum and selection guide for the latest YOLO series algorithm (YOLOv8 to YOLOv13) in printed circuit board (PCB) automatic optical inspection (AOI) through systematic benchmarking. A comprehensive evaluation of the six state-of-the-art YOLO series algorithms is conducted on a standardized dataset containing six typical PCB defects: missing hole, mouse bite, open circuit, short circuit, spur, and spurious copper. An innovative dual-cycle comparative experiment (100 rounds and 500 rounds) is designed, and a systematic assessment is performed across multiple dimensions, including accuracy, efficiency, and inference speed. The experimental results have revealed significant variations in algorithm performance with training cycles: under short-term training (100 rounds), YOLOv13 achieves leading detection performance (mAP50 = 0.924, mAP50-95 = 0.484) with the fewest parameters (2.45 million); after full training (500 rounds), YOLOv10 achieves the highest overall accuracy (mAP50 = 0.946, mAP50-95 = 0.526); additionally, YOLOv11 shows the optimal speed-accuracy balance after long-term training, while YOLOv12 excels in short-term training; moreover, “open circuit” and “spur” are evaluated as the most challenging defect categories to detect. The findings given in this paper indicate the absence of a universally applicable “all-in-one” algorithm and propose a clear algorithm selection roadmap: YOLOv10 is recommended for offline analysis scenarios prioritizing extreme accuracy; YOLOv13 is the top choice for applications requiring rapid iteration with tight training time constraints; and YOLOv11 is the best option for high-throughput online inspection PCB production lines. Full article

Sugar beet, one of the most important natural sources of sugars in the world, is well known as a recalcitrant crop for genetic transformation. In the present study, several key components of Agrobacterium-mediated transformation of sugar beet have been studied. The correct choice of explant and plant regeneration potential of domestic breeding lines was evaluated; however, most attention was paid to the search for the most efficient selectable marker gene and selection agents. To produce transgenic plants, we applied a method based on the agrobacterial inoculation of wounded morphogenic structures previously initiated on in vitro cultivated leaves. Four selective marker genes conferring antibiotic or herbicide resistance were evaluated. In the case of selection using kanamycin or G418 (nptII gene controlled by the nos promoter), no transgenic plants were obtained, while the addition of the aminoglycoside antibiotic hygromycin (hpt gene, driven by the nos promoter) to the medium ensured the successful production of transgenic plants from three breeding lines with a frequency ranging from 1.5 to 5.1%. The selection of transgenic tissues using herbicides such as phosphinothricin and glyphosate after transformation with the bar and cp4-epsps genes (both controlled by the CaMV 35S promoter) also ensured the obtaining of transgenic plants, but the transformation efficiency was significantly low, reaching only 1.0 and 0.4%, respectively. Primary transgenic sugar beet plants grown in the greenhouse demonstrated enhanced resistance to herbicides in dosages commonly used in the field. In addition, after self-pollination of the primary T0 transgenic lines, homozygous T2 offspring were successfully selected, which demonstrated stable resistance to glyphosate due to the constitutive expression of the introduced cp4-epsps gene. Full article

This study investigates the use of the fine fraction of Brazilian residual kaolin, a material with no pozzolanic activity according to the modified Chapelle test, as a partial cement replacement in rendering mortars. The kaolin was classified into three granulometric fractions (coarse: 150–300 µm, intermediate: 75–150 µm, and fine: <75 µm) and incorporated at two filler contents (10% and 20% by weight). Mineralogical and chemical analyses revealed that the fine fractions contained higher proportions of kaolinite and accessory oxides, while medium and coarse fractions were dominated by quartz. Intensity ratios from XRD confirmed greater structural disorder in the fine fraction, which was associated with higher water demand but also improved particle packing and pore refinement. Fresh state tests showed that mortars with fine kaolin maintained higher density and exhibited moderate increases in air content, whereas medium and coarse fractions promoted greater entrainment. In the hardened state, fine kaolin reduced water absorption by immersion and capillary rise, while medium and coarse fractions led to higher porosity. Mechanical tests confirmed these trends: although compressive and flexural strengths decreased with increasing substitution, mortars containing the fine kaolin fraction consistently exhibited more moderate strength losses than those with medium or coarse fractions, reflecting their enhanced packing efficiency and pore refinement. Tensile bond strength results further highlighted the positive contribution of the kaolin additions, as the mixtures with 10% coarse kaolin and 20% fine kaolin achieved adhesion values only about 7% and 4% lower, respectively, than the control mortar after 28 days. All mixtures surpassed the performance requirements of NBR 13281, demonstrating that the incorporation of residual kaolin—even at higher substitution levels—does not compromise adhesion and remains compatible with favorable cohesive failure modes in the mortar layer. Despite the lack of pozzolanic activity, residual kaolin was used due to its filler effect and capacity to enhance particle packing and pore refinement in rendering mortars. A life cycle assessment indicated that the partial substitution of cement with residual kaolin effectively reduces the environmental impacts of mortar production, particularly the global warming potential, when the residue is modeled as a by-product with a negligible environmental burden. This highlights the critical role of methodological choices in assessing the sustainability of industrial waste utilization. Full article

Consumer choice, liking, and preference can be assessed in different ways. We tested the application of a novel method called Hedonext^® for the measurement of consumer liking and preference for extra virgin olive oil (EVOO). Consumers were instructed that they would be presented with up to eight olive oils and invited to taste each of them in sequence until they found the oil that they liked or preferred, thus ending the test, and that they would receive that oil as their reward. We compared the outcomes of the Hedonext Method to hedonic ratings on the nine-point hedonic scale of all eight oils, which were then analyzed by preference mapping. A total of 139 and 141 consumers, who consumed EVOO at least once a week and were evenly distributed by age (18–65 years old) and gender (60% women, 40% men), evaluated the set of olive oils from Italy, Spain, or California with Hedonext or the nine-point hedonic scale, respectively. The oils that were chosen most often by consumers in the Hedonext procedure were also the oils that received the highest mean hedonic ratings on the nine-point hedonic scale, and those picked the least often with Hedonext also received the lowest hedonic ratings. Traditional preference mapping from hedonic ratings and an alternative preference mapping approach through Hedonext also produced similar outcomes. The Hedonext Method was shorter to administer and was enjoyed by the consumers who experienced it because of its game-like nature. It does require, though, that the product under testing be perceived as valuable by consumers, as it serves as the reward for their participation. We conclude that the Hedonext Method represents a novel and valuable alternative to the 9-point hedonic scale, particularly for the evaluation of premium or luxury consumer products. Full article

Concrete is the most carbon-intensive sector of building and construction. It leads to severe project results due to poor distribution. Cost increases, project delays, and the production of greenhouse gases. Machine learning techniques may be helpful when looking at complicated construction data; however, the issue with machine learning is the “black box” issue, and this causes a big trust issue between the project manager and the prediction model, and, thus, no one will make a choice based on the model. For that, we have Explainable AI. It brings together the power of XGBoost’s predictions with the interpretability of SHAP. We used it on the data from our four mega projects, and we got a very nice R-squared of 0.922. By looking at the SHAP analysis result, we can see that Electricity Consumption per Unit Concrete (ECUC) is the main driver, and there is a threshold for ECUC, which is 40.3 kWh/m³. If ECUC is greater than 40.3 kWh/m³, then resource waste will increase in a nonlinear way. And we transform these conclusions into a three-level optimization plan to indicate that it may be possible to reduce resources that do not fit by 38.6%. This study gives a new “prediction–interpretation–optimization” model, instead of prediction only, it gives practical and transparent decisions in construction that can use resources properly. Full article

Packaging plays a crucial role in product preservation and distribution but also constitutes a major source of environmental burden. In the beverage sector, where unit value is low, secondary and tertiary packaging significantly influence the environmental profile of the final product. This study quantifies the environmental trade-offs between conventional single-use and reusable packaging systems for aluminum cans, identifying the operational thresholds that justify a transition to circular models. A standardized Life Cycle Assessment (LCA) approach is applied to five packaging configurations: three current market scenarios and two alternative solutions based on reusable plastic crates (RPCs). System boundaries include production, distribution, end-of-life, and, where applicable, reverse logistics. A functional unit of one fully packaged 0.33 L aluminum can is adopted. Results reveal that while single-use cardboard solutions achieve favorable performance under certain impact categories, reusable systems outperform them when a sufficient number of reuse cycles is achieved and reverse logistics are efficiently managed. Sensitivity analyses highlight the critical influence of transport distances and reuse frequency on overall impacts, with performance deteriorating for reusable systems beyond 200 km or below 50 reuse cycles. These findings offer concrete, evidence-based guidance for supply-chain and logistics decision-makers to optimize packaging choices and distribution network design. The study also provides robust quantitative insights for policymakers and industry stakeholders by defining the precise operational conditions under which reusable systems deliver real environmental benefits. By presenting a comprehensive, system-level comparison of complete packaging systems, this research closes a critical gap in LCA studies and sets out a practical pathway for implementing circular, low-impact packaging strategies consistent with emerging EU regulations. Full article

Individual actions play a pivotal role in climate change, one of the most urgent global challenges, as daily behaviors generate substantial greenhouse gas emissions. Saudi Arabia, in particular, demonstrates its strong commitment to environmental sustainability through the Saudi Green Initiative and Middle East Green Initiative, aiming for net-zero emissions by 2060 and advancing reforestation, land conservation, and renewable energy under Vision 2030. However, many Saudi individuals remain unaware of the environmental consequences of their choices, including transportation, energy consumption, and lifestyle habits. To address this gap, this study developed GreenKSA, the first Arabic-supported gamified mobile application designed to promote pro-environmental behavior within the Saudi culture. The app integrates gamification elements grounded in Self-Determination Theory (SDT) and Trans-Theoretical Model (TTM) in an attempt to bridge the gap between theory and practice. GreenKSA delivers multimedia content—short videos and infographics—demonstrating sustainable routines in households, workplaces, and mobility. The design and user experience of GreenKSA were evaluated in a pilot study of 10 participants. The results indicated high usability (SUS = 91.25) and a positive overall user experience. By combining theory-driven design with culturally relevant gamification elements, this study contributes to digital sustainability interventions and aligns with the global Sustainable Development Goals SDG 12: Responsible Consumption and Production, and SDG 13: Climate Action. Full article

This study presents a production-ready AI pipeline for audio content processing, implemented within the Youth Radio platform, which serves as an extension of the European School Radio initiative. The system uses a multi-server architecture: an AI Server that runs batch/offline jobs, orchestrated by Apache Airflow, and two Web Servers that deliver all the Backend as well as the Frontend applications, configured with load balancing and redundancy to ensure high availability and fault tolerance. The implemented AI Pipeline includes tasks such as preprocessing, transcription, audio classification and topic modeling. Processed Podcasts are indexed in a Qdrant vector database to facilitate both dense and sparse retrieval while a recommendation system enriches the user’s experience. We summarize design choices and report system-level metrics and task-level indicators (ASR quality after correction, retrieval effectiveness) to guide similar deployments. Full article

The final stage of the drinking water treatment process yields two distinct outputs: treated water and the resulting sludge. This sludge is composed of raw water impurities, coagulation and flocculation agents, and various other additives. In any volume of processed drinking water, the continuous production of sludge is not negligible, leading to a significant environmental impact. This is particularly concerning when aluminium-based agents are used, as these compounds are strongly implicated in potential detrimental health risks. This situation is significantly worsened when raw water temperature approaches zero, as the treatment process efficiency is greatly diminished. Drinking water treatment at low temperatures faces a culmination of adverse effects, including a lower rate of hydrolysis and a reduced floc size, both of which negatively impact sedimentation. An effective strategy for suppressing the high dosing of chemicals is the suitable choice of ratio between acidity and the basicity of the treated water. Simply maintaining the pH value that was optimised for higher temperatures is detrimental, leading to, among other issues, increased sludge accumulation. Therefore, attention should instead be concentrated on the pOH value. A simple algebraic relation is proposed for converting the optimised pH value for higher temperatures to an optimum value for more moderate or low-temperature conditions. The application of this method results in a reduction in the amount of chemical agents required and consequently a reduction in the volume of sludge produced. Full article

The combined application of straw biochar and nitrogen fertilizer is an increasingly studied strategy to enhance soil fertility and crop yield. Optimizing the biochar-nitrogen interaction could be a choice for increasing nitrogen use efficiency (NUE) and reducing nitrogen loss in dryland agriculture. However, the mechanisms by which it regulates nitrogen allocation and absorption in foxtail millet (Setaria italica) are still limited in terms of mechanical understanding. Based on preliminary experiments, the optimal biochar-nitrogen interaction for soil nutrient absorption was identified. A field experiment was conducted with six treatments in an arid region of northwestern China: N1C1 (N1: 130 kg ha⁻¹ + C1: 100 kg ha⁻¹, control group), N2C4 (N2: 195 kg ha⁻¹ + C4: 250 kg ha⁻¹), N3C1 (N3: 260 kg ha⁻¹ + C1: 100 kg ha⁻¹), N3C2 (N3: 260 kg ha⁻¹ + C2: 150 kg ha⁻¹), N3C3 (N3: 260 kg ha⁻¹ + C3: 200 kg ha⁻¹), and N3C4 (N3: 260 kg ha⁻¹ + C4: 250 kg ha⁻¹). The results demonstrated that the biochar–nitrogen ratio significantly influenced topsoil total nitrogen, microbial biomass carbon (SMBC), and microbial biomass nitrogen (SMBN). All biochar-to-nitrogen combinations sharply increased soil total nitrogen by 133.11–151.52% compared to pre-sowing levels, providing a fundamental base for microbial-driven nitrogen transformation. Low nitrogen addition is more conducive to biomass accumulation, with N2C4 significantly increasing by 62.82%. Although a high biochar-to-nitrogen ratio reduced leaf relative chlorophyll content (SPAD) by 5.72–16.18% and net photosynthetic rate (Pn) by 16.09–52.65% at the heading stage, these did not compromise final yield. Importantly, N2C4, N3C1, and N3C4 significantly increased spike ¹⁵N abundance by 71.45%, 13.21%, and 19.43%, respectively. N2C4 grain production increases by 53.77–110.57% in two years and was positively correlated with spike ¹⁵N abundance, reflecting high nitrogen partial factor productivity. In conclusion, a reasonable biochar-nitrogen interaction enhances nitrogen allocation and grain yield by stimulating microbial activity and strengthening soil–plant synergy, the certified strategy effectively supports sustainable dryland agriculture by simultaneously increasing productivity and improving soil health. Full article

Shiitake mushrooms (Lentinula edodes) are widely consumed as a key health food in the Republic of Korea. However, they face declining production value and consumption, necessitating a shift from production-focused research to an understanding of consumer demand. The aim of this study was to quantify Korean consumers’ trade-offs among key shiitake attributes and to derive actionable marketing strategies to expand domestic consumption. We conducted an online survey (n = 500) to quantify consumer utility for four key attributes: cap size (two levels), cap color (two levels), origin (two levels: domestic (Korean) and imported (Chinese)), and price (four levels per 500 g). The results identified price as the most important attribute (relative importance = 46.41%), followed by origin (19.85%), cap color (17.10%), and cap size (16.64%). Utility analysis (part-worths) revealed a distinct dual preference: consumers value both low-priced shiitake (KRW 4000 (USD 2.9)/500 g) for personal consumption and high-priced options (KRW 13,000 (USD 9.5)/500 g) for gifting. Consumers showed a clear preference for dark-colored caps, while the aggregate-level utility difference between origin levels was small. A Logit model simulation indicated the highest predicted shares for profiles priced at KRW 13,000 (15.9%) and KRW 4000 (15.7%), consistent with a polarized value–premium structure. These findings indicate that Korean producers should adopt a dual strategy: developing low-cost products to stimulate general consumption while simultaneously marketing high-quality, dark-colored, domestically produced shiitake as premium gift items, thereby establishing effective food choice strategies in a competitive market. Although the empirical setting is the Republic of Korea (with ‘Chinese’ included only as an imported-origin level representing the main foreign competitor), the findings speak to broader specialty-food contexts where import competition and dual-purpose purchasing (everyday use vs. gifting) shape attribute trade-offs. Full article

The global demand for argan oil has grown considerably in recent years, creating economic opportunities while raising concerns about ecosystem degradation and the sustainability of production systems. To support long-term viability, several initiatives have promoted environmentally friendly practices and fair value-chain models. However, the effective market integration of these initiatives depends on understanding consumer behavior and preferences toward sustainable products. This study aims to identify the determinants influencing consumers’ purchase intention for sustainable argan oil using an extended framework of the Theory of Planned Behavior (TPB). A structural equation modeling approach was applied to analyze responses from adult consumers with a minimum education level of secondary education. The results show that consumer attitude, perceived behavioral control, and willingness to pay have significant positive effects on purchase intention, while ecological literacy exerts an indirect influence through attitude, social norms, perceived behavioral control, and willingness to pay. In contrast, ecological literacy has no significant direct impact. These findings improve the understanding of behavioral mechanisms underlying green product consumption and offer insights into designing marketing strategies that align with sustainability values and promote responsible consumer choices. Full article