Search Results (4,999)

In the rock–soil–biology–water ecosystem, rock weathering provides essential plant nutrients. However, its supply is insufficient for rising crop demands under population growth and climate change, while excessive fertilizer causes soil degradation and pollution. This study innovatively irrigated with carbonate rock leachates to enhance soil nutrient availability. A pot experiment with lettuce showed that irrigation significantly increased soil NO₃⁻-N (+102.20%), available K (+16.45%), available P (+17.95%), Ca (+6.04%), Mg (+11.65%), and Fe (+11.60%), and elevated the relative abundance of Firmicutes. Lettuce biomass per plant rose by 23.78%, with higher leaf minerals (P, K, Ca, and Mg) and antioxidants (carotenoids and ascorbic acid). A field experiment further confirmed improvement of soil nutrient availability and peanut yield. This carbonate rock leachate irrigation technique effectively enhances soil quality and crop productivity/quality, offering a sustainable approach for green agriculture. Full article

Urban vegetation monitoring is essential for sustainable city planning but is often constrained by the high cost and limited frequency of field-based inventories. This study evaluates the use of the Normalized Difference Vegetation Index (NDVI), derived from Sino-Brazilian CBERS-4A satellite imagery, as a spatially explicit and low-cost proxy for urban tree census data. CBERS-4A provides medium-resolution multispectral data freely accessible across South America, yet remains underutilized in urban environmental applications. Focusing on Aracaju, a metropolitan region in northeastern Brazil, we compared NDVI-based classification results with official municipal tree census data from 2022. The analysis revealed a strong spatial correlation, supporting the use of NDVI as a reliable indicator of canopy presence at the urban block scale. In addition to mapping vegetation distribution, the NDVI results identified areas with insufficient canopy coverage, directly informing urban greening priorities. By validating remote sensing data against field inventories, this study demonstrates how CBERS-4A imagery and vegetation indices can support municipal tree management and serve as scalable tools for environmental planning and policy. Full article

Conspicuous declines in native grassland habitats have triggered sharp reductions in grassland birds, dragonflies, butterflies, and native plant populations and diversity. We compared these biotic groups among three crop type treatments: corn, alfalfa, and a perennial native grass, Virginia wild rye, (Elymus virginicus L.) or VWR. This crop type had 2-3X higher bird, dragonfly, butterfly and plant species richness, diversity, and faunal abundance relative to alfalfa and corn types. VWR crop fields also support more obligate grassland bird species and higher populations of dragonfly and butterfly species associated with grasslands and wet meadows. In contrast, the corn and alfalfa types support few or no obligatory grassland birds and mostly non-native insects such as the white cabbage looper (Artogeia rapae L.), the common yellow sulfur butterfly (Colias philodice Godart.), and the mobile and migratory common green darner dragonfly (Anax junius Drury.). In sum, the VWR perennial native grass crop type offers a special opportunity to improve the diversity and abundance of grassland bird species, beneficial insect species, and many native plant species within agricultural landscapes. Full article

Fungal lytic polysaccharide monooxygenases (LPMOs) have revolutionized the field of biomass degradation by introducing an oxidative mechanism that complements traditional hydrolytic enzymes. These copper-dependent enzymes catalyze the cleavage of glycosidic bonds in recalcitrant polysaccharides such as cellulose, hemicellulose, and chitin, through the activation of molecular oxygen (O₂) or hydrogen peroxide (H₂O₂). Their catalytic versatility is intricately modulated by structural features, including the histidine brace active site, surface-binding loops, and, in some cases, appended carbohydrate-binding modules (CBMs). The oxidation pattern, whether at the C1, C4, or both positions, is dictated by subtle variations in loop architecture, amino acid microenvironments, and substrate interactions. LPMOs are embedded in a highly synergistic fungal enzymatic system, working alongside cellulases, hemicellulases, lignin-modifying enzymes, and oxidoreductases to enable efficient lignocellulose decomposition. Industrial applications of fungal LPMOs are rapidly expanding, with key roles in second-generation biofuels, biorefineries, textile processing, food and feed industries, and the development of sustainable biomaterials. Recent advances in genome mining, protein engineering, and heterologous expression are accelerating the discovery of novel LPMOs with improved functionalities. Understanding the balance between O₂- and H₂O₂-driven mechanisms remains critical for optimizing their catalytic efficiency while mitigating oxidative inactivation. As the demand for sustainable biotechnological solutions grows, this narrative review highlights how fungal LPMOs function as indispensable biocatalysts for the future of the Circular Bioeconomy and green industrial processes. Full article

Aquatic vegetation plays a crucial role in freshwater ecosystems by providing habitats, regulating water quality, and supporting biodiversity. This study aims to monitor and analyze the dynamics of aquatic vegetation in Chimaditida Shallow Lake, Greece, using Sentinel-2 satellite imagery, with validation from field measurements. Data processing was performed using Google Earth Engine and QGIS. The study focuses on discriminating and mapping two classes of aquatic surface conditions: areas covered with Floating and Emergent Aquatic Vegetation and open water, covering all seasons from 1 March 2024, to 28 February 2025. Spectral bands such as B04 (red), B08 (near infrared), B03 (green), and B11 (shortwave infrared) were used, along with indices like the Modified Normalized Difference Water Index and Normalized Difference Vegetation Index. The classification was enhanced using Otsu’s thresholding technique to distinguish accurately between Floating and Emergent Aquatic Vegetation and open water. Seasonal fluctuations were observed, with significant peaks in vegetation growth during the summer and autumn months, including a peak coverage of 2.08 km² on 9 September 2024 and a low of 0.00068 km² on 28 December 2024. These variations correspond to the seasonal growth patterns of Floating and Emergent Aquatic Vegetation, driven by temperature and nutrient availability. The study achieved a high overall classification accuracy of 89.31%, with producer accuracy for Floating and Emergent Aquatic Vegetation at 97.42% and user accuracy at 95.38%. Validation with Unmanned Aerial Vehicle-based aerial surveys showed a strong correlation (R² = 0.88) between satellite-derived and field data, underscoring the reliability of Sentinel-2 for aquatic vegetation monitoring. Findings highlight the potential of satellite-based remote sensing to monitor vegetation health and dynamics, offering valuable insights for the management and conservation of freshwater ecosystems. The results are particularly useful for governmental authorities and natural park administrations, enabling near-real-time monitoring to mitigate the impacts of overgrowth on water quality, biodiversity, and ecosystem services. This methodology provides a cost-effective alternative for long-term environmental monitoring, especially in regions where traditional methods are impractical or costly. Full article

We summarize our present knowledge of the regulation of photostasis and photosynthetic performance versus photoprotection in response to vernalization and conclude that the enhanced photosynthetic performance of winter crops is due to an inherent increase in photosynthetic energy conversion efficiency induced by vernalization which translates into high seed yield in the field as well as under controlled environment conditions. This is consistent with the published data for enhanced photosynthetic performance of the only two extant terrestrial angiosperms, Colobanthus quitensis and Deschampsia antarctica, native to the frigid conditions of terrestrial Antarctica. The Cold Binding factor family of transcription factors (CBFs/DREBs) governs the enhanced photosynthetic performance of winter cereals as well as the Antarctic angiosperms. In contrast to winter crops, spring varieties survive cold environments by stimulating photoprotection at the expense of photosynthetic performance like that observed for green algae and cyanobacteria. Consequently, this minimizes the photosynthetic energy conversion efficiency of spring varieties and limits their seed yield upon cold acclimation. This review provides critical insights into the regulation of photostasis and the balance between photosynthetic performance and photoprotection in plants and how vernalization has enhanced photosynthetic energy conversion, which is essential for understanding plant adaptation to cold environments and optimizing agricultural productivity for improving crop resilience and yield in challenging climates. Full article

Monitoring crop damage caused by wildlife remains a significant challenge in agricultural management, particularly in the case of large-scale monocultures such as maize. The given study presents a semi-automated process for detecting wildlife-induced damage using RGB imagery acquired from unmanned aerial vehicles (UAVs). The method is designed for non-specialist users and is fully integrated within the QGIS platform. The proposed approach involves calculating three vegetation indices—Excess Green (ExG), Green Leaf Index (GLI), and Modified Green-Red Vegetation Index (MGRVI)—based on a standardized orthomosaic generated from RGB images collected via UAV. Subsequently, an unsupervised k-means clustering algorithm was applied to divide the field into five vegetation vigor classes. Within each class, 25% of the pixels with the lowest average index values were preliminarily classified as damaged. A dedicated QGIS plugin enables drone data analysts (Drone Data Analysts—DDAs) to adjust index thresholds, based on visual interpretation, interactively. The method was validated on a 50-hectare maize field, where 7 hectares of damage (15% of the area) were identified. The results indicate a high level of agreement between the automated and manual classifications, with an overall accuracy of 81%. The highest concentration of damage occurred in the “moderate” and “low” vigor zones. Final products included vigor classification maps, binary damage masks, and summary reports in HTML and DOCX formats with visualizations and statistical data. The results confirm the effectiveness and scalability of the proposed RGB-based procedure for crop damage assessment. The method offers a repeatable, cost-effective, and field-operable alternative to multispectral or AI-based approaches, making it suitable for integration with precision agriculture practices and wildlife population management. Full article

High-quality green gardens can markedly enhance the quality of life and mental well-being of their users. However, health and lifestyle constraints make it difficult for people to enjoy urban gardens, and traditional methods struggle to offer the high-fidelity experiences they need. This study introduces a 3D scene reconstruction and rendering strategy based on implicit neural representation through the efficient and removable neural radiation fields model (NeRF-RE). Leveraging neural radiance fields (NeRF), the model incorporates a multi-resolution hash grid and proposal network to improve training efficiency and modeling accuracy, while integrating a segment-anything model to safeguard public privacy. Take the crabapple tree, extensively utilized in urban garden design across temperate regions of the Northern Hemisphere. A dataset comprising 660 images of crabapple trees exhibiting three distinct geometric forms is collected to assess the NeRF-RE model’s performance. The results demonstrated that the ‘harvest gold’ crabapple scene had the highest reconstruction accuracy, with PSNR, LPIPS and SSIM of 24.80 dB, 0.34 and 0.74, respectively. Compared to the Mip-NeRF 360 model, the NeRF-RE model not only showed an up to 21-fold increase in training efficiency for three types of crabapple trees, but also exhibited a less pronounced impact of dataset size on reconstruction accuracy. This study reconstructs real scenes with high fidelity using virtual reality technology. It not only facilitates people’s personal enjoyment of the beauty of natural gardens at home, but also makes certain contributions to the publicity and promotion of urban landscapes. Full article

Early crop yield prediction is a major challenge in precision agriculture, and efficient and rapid yield prediction is highly important for sustainable fruit production. The accurate detection of major fruit characteristics, including flowering, green fruiting, and ripening stages, is crucial for early yield estimation. Currently, most crop yield estimation studies based on the YOLO model are only conducted during a single stage of maturity. Combining multi-growth period data for crop analysis is of great significance for crop growth detection and early yield estimation. In this study, a new network model, YOLOv8-RL, was proposed using citrus multigrowth period characteristics as a data source. A citrus yield estimation model was constructed and validated by combining network identification counts with manual field counts. Compared with YOLOv8, the number of parameters of the improved network is reduced by 50.7%, the number of floating-point operations is decreased by 49.4%, and the size of the model is only 3.2 MB. In the test set, the average recognition rate of citrus flowers, green fruits, and orange fruits was 95.6%, the mAP@.5 was 94.6%, the FPS value was 123.1, and the inference time was only 2.3 milliseconds. This provides a reference for the design of lightweight networks and offers the possibility of deployment on embedded devices with limited computational resources. The two estimation models constructed on the basis of the new network had coefficients of determination R² values of 0.91992 and 0.95639, respectively, with a prediction error rate of 6.96% for citrus green fruits and an average error rate of 3.71% for orange fruits. Compared with network counting, the yield estimation model had a low error rate and high accuracy, which provided a theoretical basis and technical support for the early prediction of fruit yield in complex environments. Full article

The age of entrepreneurship calls for the evolving of learning and development (L&D) models to meet the dynamic demands of innovation, sustainability, and technology innovation. This study examines the trends and issues of L&D models for entrepreneurs, more so focusing on how these models influence business success in a rapidly changing global landscape. The research employs bibliometric analysis, VOSviewer cluster analysis, and co-citation analysis to explore the literature from 1994 to 2024. Data collected from the Web of Science Core Collection database reflect significant trends in entrepreneurial L&D, with particular emphasis on the use of digital tools, sustainability processes, and governance systems. Findings emphasize the imperative role of L&D in fostering entrepreneurship, more so in areas such as digital transformation and the adoption of new technologies. The study also identifies central regions propelling this field, such as UK and USA. Future studies will be centered on the role of digital technologies, innovation, and green business models within entrepreneurial L&D frameworks. This study provides useful insight into the future of L&D within the entrepreneurial domain, guiding academia and companies alike in the planning of effective learning strategies to foster innovation and sustainable business growth. Full article

Urban blue-green infrastructure (UBGI) is a comprehensive solution that balances environmental, social, and economic development objectives and has emerged as a critical approach for fostering urban resilience and sustainable development. This paper conducts a systematic bibliometric analysis of 975 academic articles published between 2000 and 2023 in the Web of Science Core Collection, focusing specifically on the ecosystem services associated with UBGI. Employing CiteSpace visualization technology, this study elucidates the major research trends, thematic clusters, and international collaboration patterns shaping this field. The research delves into the diverse range of ecosystem services provided by blue-green infrastructure and analyzes their contributions to urban well-being. Findings indicate that regulatory services—particularly climate regulation, biodiversity enhancement, and water resource management—have become central research foci within the contexts of urban green infrastructure (UGI), urban blue infrastructure (UBI), and UBGI. Co-citation and keyword analyses reveal that nature-based solutions, hybrid green–gray infrastructure, and the application of urban resilience frameworks are gaining increasing scholarly attention. By summarizing the evolutionary trajectory and priority directions of UBGI research, this study provides significant insights for future interdisciplinary research aimed at enhancing the supply of urban environmental ecosystem services. Full article

The equivalent source method (ESM) is a core algorithm in integrated radiation-propagation acoustic field modeling. However, in challenging marine environments, including deep-sea and polar regions, where sound speed profiles exhibit strong vertical gradients, the ESM must increase waveguide stratification to maintain accuracy. This causes computational costs to scale exponentially with the number of layers, compromising efficiency and limiting applicability. To address this, this paper proposes a modal equivalent source (MES) model employing normal modes as basis functions instead of free-field Green’s functions. This model constructs a set of normal mode bases using full-depth hydroacoustic parameters, incorporating water column characteristics into the basis functions to eliminate waveguide stratification. This significantly reduces the computational matrix size of the ESM and computes acoustic fields in range-dependent waveguides using a single set of normal modes, resolving the dual limitations of inadequate precision and low efficiency in such environments. Concurrently, for the construction of basis functions, this paper also proposes a fast computation method for eigenvalues and eigenmodes in waveguide contexts based on phase functions and difference equations. Furthermore, coupling the MES method with the Finite Element Method (FEM) enables integrated computation of underwater target radiation and propagation fields. Multiple simulations demonstrate close agreement between the proposed model and reference results (errors < 4 dB). Under equivalent accuracy requirements, the proposed model reduces computation time to less than 1/25 of traditional ESM, achieving significant efficiency gains. Additionally, sea trial verification confirms model effectiveness, with mean correlation coefficients exceeding 0.9 and mean errors below 5 dB against experimental data. Full article

The intersection of sports and natural forests and green spaces represents an emerging interdisciplinary field with implications for public health, environmental science, and sustainable land management and refers to the variety of cultural ecosystem services demanded by people from ecosystems. This manuscript presents a systematic bibliometric and thematic analysis of 148 publications for the period 1993–2024 identified through Web of Science and Scopus, aiming to evaluate the current state of research on sports activities conducted in natural forest environments. Findings indicated a marked increase in scientific interest of this topic over the past two decades, with key contributions from countries such as England, Germany, China, and the United States. Researchers most frequently examined sports such as hiking, trail running, mountain biking, and orienteering for their capacity to provide physiological and psychological benefits, reduce stress, and enhance mental well-being. The literature analysis highlights ecological concerns, particularly those associated with habitat disturbance, biodiversity loss, and conflicts between recreation and conservation. Six principal research themes were identified: sports in urban forests, sports tourism, hunting and fishing, recreational sports, health benefits, and environmental impacts. Keyword and co-authorship analyses revealed a multidisciplinary knowledge base with evolving thematic focuses. In conclusion, the need for integrated approaches that incorporate ecological impact assessment, stakeholder perspectives, and adaptive forest governance to ensure sustainable recreational use of natural forest ecosystems is underlined. Full article

This study aims to develop a preliminary list of indicators suitable for green restaurants in Taiwan. The research methodology includes expert consensus (Delphi method) and incorporates interviews with field experts. An analysis of the responses provided by these industry experts led to the identification of five dimensions of evaluation indicators for green restaurants. The K–S test involves using a z-test on ordinal variables for single samples to determine whether the sample distribution diverges from the frequency distribution. This study analyzed the responses provided by the interviewed experts to identify and extract evaluation indicators for green restaurants. The extracted indicators comprise five dimensions (resource management, ingredient and product selection, environmental and indoor quality, green certification and management, and customer awareness and participation), 15 sub-dimensions, and 70 detailed indicators. The research results can serve as a reference for course planning in related programs at universities and colleges, as well as for industry planning of green restaurants, and as a reference for the promotion of national sustainable environmental policies in Taiwan. Therefore, based on the results of this study, recommendations are provided for educational institutions related to green restaurants, official organizations related to green restaurants, the industry related to green restaurants, and future researchers. Full article

Demand for mental health support has exerted unprecedented pressure on statutory services. Innovative solutions such as Green or Nature-Based Social Prescribing (NBSP) programmes may help address unmet need, improve access to personalised treatment, and support the sustainable delivery of primary services within a prevention model of population health. We piloted an innovative health economics-informed Social Return on Investment (SROI) analysis and forecast of a ‘Making Well’ therapeutic craft and horticulture programme for mental health between October 2021 and March 2022. Quantitative and qualitative outcome data were collected from participants with mild-to-moderate mental health conditions at baseline and nine-weeks follow-up using a range of validated measures, including the Short Warwick–Edinburgh Mental Well-being Scale, ICEpop CAPability measure for Adults (ICECAP-A), General Self-Efficacy Scale (GSES), and a bespoke Client Service Receipt Inventory (CSRI). The acceptability and feasibility of these measures were explored. Results indicate that the Making Well programme generated well-being-related social value in the range of British Pound Sterling (GBP) GBP 3.30 to GBP 4.70 for every GBP 1 invested. Our initial pilot forecast suggests that the programme has the potential to generate GBP 5.40 to GBP 7.70 for every GBP 1 invested as the programme is developed and delivered over a 12-month period. Despite the small sample size and lack of a control group, our results contribute to the evidence-base for the effectiveness and social return on investment of NBSP as a therapeutic intervention for improving health and well-being and provides an example of the use of health economic well-being outcome measures such as ICECAP-A and CSRIs in social value analysis. Combining SROI evaluation and forecast methodologies with validated quantitative outcome measures used in the field of health economics can provide valuable social cost–benefit evidence to decision-makers. Full article