Search Results (1,352)

Soilborne diseases caused by Rhizoctonia solani, Fusarium oxysporum f. sp. betae, Aphanomyces cochlioides, and Pythium spp. constrain sugar-beet production worldwide, with yield losses exceeding 50% in severely affected fields. These pathogens frequently co-occur, yet most biological control and microbiome studies address them individually, and recommendations from model crops often fail to translate to sugar beet’s distinctive root biology and rotation systems. This critical review synthesises evidence on the rhizosphere microbiome as a plant protection resource, organising the literature by agronomic applicability: crop rotation, organic amendments, soil physicochemical management, microbial inoculants and synthetic communities, and microbiome-informed breeding and diagnostics. For each strategy, we state the evidence directness (direct sugar-beet field trials, greenhouse data, cross-crop extrapolation, or mechanistic inference) and evaluate the gap between experimental efficacy and field-ready recommendations. Direct field evidence remains limited: the best-characterised example is Rhizoctonia-suppressive soil linked to non-ribosomal peptide synthetase (NRPS)-producing Pseudomonadaceae and Burkholderiaceae, with 2,4-DAPG-producing Pseudomonas populations also being correlated with disease suppression in sugar-beet seedlings, plus one integrated fungicide-biocontrol field trial. We identify multi-pathogen challenge experiments, multi-site field validation of synthetic communities, and microbiome-informed breeding as priority research gaps. Rhizosphere microbiome management should be integrated into existing disease programmes rather than deployed as a stand-alone replacement. Full article

Grounded in a human–land coupling framework, this study takes Purple Mountain, a representative composite urban mountain heritage site, as the research object. It integrates historical archives, field survey data, and multi-source geospatial data, and adopts a set of GIS-based spatial statistical methods, including the nearest neighbour index, kernel density estimation, standard deviational ellipse, coupling coordination degree model, and Geodetector. This paper systematically explores the spatial differentiation, spatiotemporal evolution, human–land coupling patterns, and multidimensional driving mechanisms of four heritage types: geomorphological relics, ritual architecture, modern commemorative heritage, and eco-scenic heritage. The results show that: (1) Heritage resources across Purple Mountain display statistically significant clustering, with ritual architectural heritage exhibiting the highest agglomeration degree; heritage sites form an east–west high-density corridor along the southern foothills, presenting a consistent northeast–southwest spatial orientation. (2) Purple Mountain heritage has undergone multi-stage diachronic evolution. Jointly driven by topographic constraints and socio-cultural forces, its heritage quantity, spatial coverage, and functions fluctuated across dynasties, with an overall expanding trend. (3) A total of 63.07% of the study area’s grid units are in a near-dissonant human–land coupling state, while highly coordinated units are concentrated in the southern core corridor of the Ming Xiaoling Mausoleum, Sun Yat-sen Mausoleum, and Linggu Temple, with remarkable disparities among heritage types in coupling patterns among the four heritage categories. (4) Historical and cultural aggregation density dominates heritage spatial differentiation, while topographic factors show weak explanatory power, and all influencing factor interactions present prominent non-linear enhancement effects. This study establishes a three-level quantitative framework of “spatial pattern—coupling coordination—driving mechanism”, enriching the theoretical framework of human–land coupling for urban mountain heritage, and provides scientific support for refined coordinated governance of mountain heritage embedded in high-density urban environments. Full article

The synergistic regulatory mechanism of current planting patterns on cotton agronomic traits, boll source–sink development and fiber quality remains unclear. Therefore, this study used 11 upland cotton parents and 36 F1 progenies as materials. Three planting patterns, namely, one film–three rows, one film–four rows and one film–six rows, were established from 2024 to 2025. The dynamic changes in the boll morphology and dry-fresh-weight accumulation of each boll component were monitored at eight stages from 10 to 60 days after anthesis, and agronomic traits and fiber quality were measured simultaneously. The Logistic growth model was adopted to fit cotton boll growth parameters to analyze the regulatory effects of planting patterns on the developmental process and dry-matter accumulation of upland cotton. The results showed that boll morphological stability gradually decreased with the increase in planting density. The maximum cumulative boll volume (Wm) under the one-film–three-rows pattern ranged from 29.19 to 30.97 cm³, higher than those under one film–four rows (28.35–30.77 cm³) and one film–six rows (28.74–30.86 cm³). Vegetative growth indicators, including plant height, height of the first fruiting node and number of fruiting branches, declined with increasing density. The one-film–six-rows treatment exhibited a significantly higher proportion of empty fruiting branches and a lower boll-setting rate. The one-film–three-rows pattern presented prominent single-boll sink capacity, yet suffered insufficient population photosynthetic supply, leading to assimilate allocation biased toward vegetative organs. Under high-density competition stress, the one-film–six-rows pattern possessed poor source–sink stability and inhibited dry-matter accumulation in reproductive organs. The one-film–four-rows pattern achieved the highest dry-matter translocation efficiency from boll shell to cottonseed and fibers, with the maximum cumulative fiber dry weight (Wm) of 2.40–2.62 g, and obtained optimal fresh-weight accumulation and allocation of fibers. Synthesizing all indicators, the one-film–four-rows pattern is more suitable for cotton growth in southern Xinjiang, which can balance population boll-setting potential and boll dry-matter allocation efficiency. These results are only derived from two-year field-located experiments in southern Xinjiang. Multi-site trials are required in further research to clarify the applicable scope of this cultivation pattern in other cotton-producing regions. Full article

Green manuring may improve crop performance on acidic, low-fertility soils, although its effects depend on the incorporated species and mineral fertilization regime. This study evaluated the effects of five green manure crops and mineral fertilization on winter wheat during the 2021/2022 growing season at the Agricultural Research and Development Station Livada, northwestern Romania. A two-factor split-plot field experiment was conducted at a single location during one growing season (2021/2022) using three replicate blocks. Six main-plot treatments—wheat, triticale, pea, narrow-leafed lupine, oilseed rape, and a non-sown control with spontaneous vegetation—were combined with two subplot regimes: with and without combined N–P mineral fertilization. The green manure × mineral fertilization interaction was significant for grain yield (p = 0.008). Under mineral fertilization, pea produced the highest numerical grain yield (8018 ± 116 kg ha⁻¹; mean ± SE, n = 3), compared with 6730 ± 244 kg ha⁻¹ in the corresponding fertilized control. Without mineral fertilization, pea and lupine produced 5427 ± 187 and 5009 ± 237 kg ha⁻¹, respectively, compared with 3419 ± 108 kg ha⁻¹ in the corresponding non-fertilized control. Wheat and triticale green manures were associated with lower subsequent wheat yields than their corresponding controls under both fertilization regimes. Under the conditions of this single-site, single-season experiment, pea and narrow-leafed lupine were associated with favorable grain-yield responses, particularly relative to the corresponding non-sown controls. Further multi-year and multi-location experiments are required to determine the stability of these responses under contrasting soil and climatic conditions. Full article

This study conceptualizes RE100 not merely as a voluntary corporate campaign, but as an evolving socio-technical system that intersects with South Korea’s path-dependent energy regime. Applying BERTopic to a comprehensive corpus of 21,901 raw news articles (reduced to 13,507 analytically relevant articles after noise filtering; January 2019–October 2025), we trace the systemic evolution and multi-layered governance of RE100. Grounded in social constructionism and institutional systems theory, the research reveals how the global sustainability norm becomes structurally embedded in South Korea’s industrial and economic systems through a partially sequential evolutionary process of externalization, objectivation, and internalization. BERTopic identified 39 analytically meaningful topics, subsequently organized into four interpretive clusters: (1) local government-centered construction, (2) spatial reconfiguration and industrial-policy formation, (3) corporate-led market institutionalization, and (4) ESG-driven corporate governance. Collectively, these clusters demonstrate that RE100 has evolved from a peripheral international initiative into a multilayered governance norm embedded across local governance, industrial infrastructure, corporate strategy, and ESG systems. The findings hold theoretical and policy implications for energy-transition governance and climate communication. This progression is recursive rather than strictly linear: corporate-level internalization (Cluster 4) is conceptually linked to, and may interact with, regional and industrial-policy externalization (Clusters 1–2), consistent with a non-linear reading of institutionalization in which corporate site-selection criteria shape local-government infrastructure competition. Cluster 1’s prominence reflects local governments’ discursive visibility rather than substantive policy authority. Notably, RE100’s “normalization” denotes routinized corporate compliance practices, not political consensus on its legitimacy relative to alternatives such as carbon-free 100% or nuclear power. Full article

In the field of architectural heritage, industrial built heritage plays an important role. Traditional research methods such as literature studies and field surveys have gradually evolved into digital-twin and machine-learning-based approaches. However, the study of industrial heritage remains a challenge. This study employs the PRISMA framework to conduct a systematic review of the existing literature, aiming to elucidate the impact of GIS on industrial heritage sites and its potential limitations. This study conducts a systematic review of GIS-based research on industrial heritage, focusing on studies published between 2000 and 2025. Among the 2166 records initially retrieved from Scopus and the 1771 records initially retrieved from Web of Science, 77 papers were ultimately retained after screening and deduplication. A total of 32 studies were selected based on thematic screening criteria, all of which focused on analysing the spatial characteristics of industrial heritage sites using GIS technology. Among these, 12 core studies were further selected for in-depth qualitative and methodological analysis. These documents form the foundation for exploring research hotspots, methodological approaches, and technological evolution. This review contributes a five-dimensional analytical framework that systematically classifies GIS-based industrial heritage research and identifies eight structural research gaps. The findings indicate that GIS applications remain predominantly focused on spatial mapping and distribution analysis, while their integration with ecological assessment, social and participatory approaches, archaeology, and multi-source technologies remains limited. This review provides a roadmap for integrating advanced spatial analysis tools into future industrial heritage research and planning. Full article

Electric vehicles (EVs) are attracting choice and adoption as a travel mode in global transportation systems, driven by technological innovation, economic considerations, and advancing sustainable urban development. The planning, development, design, and location of EV charging stations are challenging tasks for underdeveloped countries such as Pakistan. To propose the site location for an EV charging station, this study comprises Multi-Criteria Decision Analysis and Geographic Information Systems. The study adopts a mixed-methods design, combining qualitative expert input with quantitative spatial analysis to investigate technical, social, and infrastructural criteria. The study considers indicators, including site suitability, population density, interaction between land use and transport, road network, transportation interactions, existing electricity grid infrastructure, and existing fueling and charging stations. This research presents pairwise expert comparisons, indicating that grid capacity (0.28) and demand (0.30) are important factors to consider. A composite suitability Index (CSI) through GIS-weighted overlay was used to classify the area into low, medium, and high suitability zones. According to the CSI, 26% of the area falls in highly suitable areas for EV infrastructure in Islamabad, and 41% falls in medium-to-high suitable areas. The remaining 33% area lies in low-suitability peripheral zones near the hilly region of Islamabad city, which is not considered suitable for EV infrastructure. A total of 67% of the city’s area is suitable for EV infrastructure. Full article

Conventional biosensor coatings face considerable challenges in reconciling high loading capacity, antifouling performance, and long-term stability. Metal–organic frameworks (MOFs), with their ultrahigh surface areas, tunable pores, and abundant unsaturated metal sites, have become important functional coating materials for advanced sensing interfaces. This review focuses on interface engineering strategies for MOF-based biosensor coatings and systematically compares three core construction approaches, namely defect engineering, MOF-on-MOF heterostructures, and interface-assisted fabrication, examining their distinct interfacial regulation logics and applicability under engineering constraints including substrate compatibility, film uniformity, and scalability. The multifaceted interfacial roles of MOF coatings are then categorized across electrochemical, photoelectrochemical, colorimetric, optical fiber, and dual-signal biosensors, covering enrichment-confinement, catalytic transduction, biorecognition protection, and smart gating. Notably, most reported systems remain at the proof-of-concept stage, with insufficient validation in complex biofluids, ambiguous signal transduction mechanisms, and a notable deficiency in systematic assessments of coating adhesion and durability. Future efforts should focus on establishing standardized failure evaluation protocols, adopting AI-driven rational design, and advancing toward multi-target integrated and flexible wearable platforms to bridge the gap between laboratory research and practical diagnostic applications. Full article

Background: Stroke is the third leading cause of death and a major cause of long-term disability in Malaysia, where the continuity of post-stroke care depends heavily on unpaid, untrained informal family caregivers. These caregivers face a well-documented “discharge cliff,” assuming complex medical and rehabilitative responsibilities with minimal preparation. The locally developed “CaknaStrok” mobile health (mHealth) application was designed to bridge this support gap. However, the existence of a tool does not guarantee its use; sustained adoption depends on whether caregivers find the application acceptable and are willing to integrate it into an already demanding caregiving routine. Objectives: This protocol describes a study designed to determine the levels of acceptability and willingness to use the CaknaStrok application, to examine the associated predictors (effort expectancy, ability, digital health literacy, and intervention coherence), and to test the central mediating role of acceptability through a novel Integrated Acceptability–Willingness (IAW) Framework. Methods: An explanatory sequential mixed-methods design will be conducted at the Stroke Ward of Hospital Canselor Tuanku Muhriz (HCTM), a World Stroke Organization-certified Advanced Stroke Centre. In Phase I, a target of 200 informal primary caregivers will be recruited through consecutive sampling and surveyed using a validated, bilingual (Malay/English) self-administered questionnaire that operationalises the IAW constructs through three established instruments (UTAUT, the Digital Health Literacy Instrument, and the Theoretical Framework of Acceptability). Following a standardised facilitated onboarding, caregivers use the application ad libitum for four to six weeks before completing the questionnaire. Expected Results: The study will quantify caregiver acceptability and willingness to use, identify which factors most strongly drive acceptance, and empirically test whether acceptability mediates the relationship between the predictors and willingness to use. Qualitative themes will contextualise the statistical pathways, surfacing culturally specific mechanisms of adoption that single-method designs typically miss. Ethical approval was obtained from the UKM Research Ethics Committee (JEP-2024-392). Conclusions: This study is expected to generate context-sensitive evidence to guide the design of caregiver-facing mHealth interventions and inform future multi-site implementation and policy development efforts within the Malaysian stroke-care pathway. Full article

In the primary spruce-fir-Korean pine forest affected by historical windthrow, soil water-holding capacity shows complex spatial associations with forest microenvironment and soil physicochemical properties. However, its spatial variability and multi-factor hierarchical association pathways remain poorly understood. Taking the primary spruce-fir-Korean pine forest on a historically windthrow-affected site in the Liangshui National Nature Reserve, Xiaoxing’an Mountains, China as the research object, geostatistics and partial least-squares structural equation modeling were used to analyze the spatial pattern of topsoil (0–20 cm) water-holding capacity and its environmental association pathways. The results showed saturated, capillary and field water-holding capacities of topsoil exhibited moderate variability and strong spatial autocorrelation (all nugget to sill ratios < 25%), showing a patchy distribution. No significant direct association was detected between windthrow mechanical disturbance intensity and topsoil water-holding capacity. Bulk density (path coefficient = −0.685, p < 0.001) and soil porosity (path coefficient = 0.273, p < 0.001) had significant direct associations with soil water-holding capacity, whereas soil particle size distribution showed no significant effect (p > 0.05). Canopy structure and understory microclimate exerted indirect associations with soil water-holding capacity via soil structure; litter showed no significant associative effect (p > 0.05). These results indicate that soil water-holding capacity on the historically windthrow-affected site was not randomly distributed, but presented an ordered patchy pattern closely related to in-plot micro-environmental factors. Full article

While previous reviews have largely focused on individual crops or single target-site mechanisms, the full-chain comparative landscape across major cereal crops remains unexplored. Here, we fill this critical gap by providing the first systematic, cross-crop comparative review that spans herbicide targets, resistance mechanisms, and breeding applications across four major cereals—rice, maize, wheat, and sorghum. Weed infestation is a serious constraint on crop production. Chemical weed control faces challenges such as herbicide resistance evolution and ecological risks. Developing herbicide-resistant varieties is a fundamental approach to achieve green and sustainable weed management. This review systematically summarizes research progress on herbicide resistance genes from three aspects: herbicide classification, resistance mechanisms, and crop breeding applications. It highlights key differences among four major cereal crops (rice, maize, wheat, and sorghum) in resistance-gene discovery and translational progress. Rice has the richest target-site resistance-gene resources. Maize leads in commercialization of transgenic herbicide resistance. Wheat focuses on endogenous precise editing due to genome complexity and regulatory constraints. Sorghum relies on specific mutations to serve cereal–legume intercropping systems. Based on this comparison, this review identifies the core trends in resistance breeding: from single-gene to multi-gene stacking, and from exogenous gene introduction to endogenous gene editing. It also points out common bottlenecks, including insufficient systematic mining of resistance-gene resources, lagging elucidation of non-target-site resistance regulatory networks, and strong genotype dependence in genetic transformation. Future efforts should focus on exploring broad-spectrum resistance genes, optimizing precise editing technologies, and developing sustainable resistance management strategies. This review provides a theoretical framework and practical references for molecular breeding of herbicide-resistant crops. Full article

Proper municipal solid waste (MSW) management is vital for mitigating environmental degradation and protecting public health. Landfill site selection remains a complex spatial decision-making challenge, balancing ecological, social, and economic parameters. This study presents a comprehensive systematic review of 175 peer-reviewed articles published between 2016 and 2026, evaluating the evolution of Geographic Information Systems (GIS) and Multi-Criteria Decision Analysis (MCDA) frameworks. The findings indicate that road accessibility (93.7%), surface and groundwater protection (91.4%), slope gradients (84.6%), and settlement buffer zones (78.9%) represent the most critical and universally applied siting criteria. Digital Elevation Models (81.9%) and geological maps (57.3%) serve as foundational geospatial datasets. While the Analytic Hierarchy Process (AHP) remains the dominant weighting technique (63.41%), recent trends show an increasing adoption of hybrid multi-criteria models and optimisation algorithms. Geographically, research output is led by India, Iran, and Turkey, peaking significantly in 2025. Crucially, this review exposes prominent methodological shortcomings, notably a heavy reliance on subjective expert validation (73.8%), whereas quantitative validation, sensitivity analysis, and uncertainty assessment remain critically underutilised. In contrast to earlier reviews, this review offers a thorough and critical synthesis of GIS- and MCDA-based approaches to landfill site selection by carefully evaluating methodological advancements, examining the advantages, disadvantages, and limitations of current approaches, and incorporating statistical trends with a structured methodological framework. This approach highlights important research gaps and offers evidence-based suggestions for creating more transparent, reliable, and sustainable techniques for landfill site selection by selecting, screening, and including relevant articles. To foster sustainable urban planning, future research must prioritise standardised evaluation frameworks, rigorous uncertainty quantification, and the integration of artificial intelligence and machine learning with spatial modelling. Full article

Geohazards are present at every stage of a mine’s life cycle (initial exploration, site investigations, active operations, closure, reclamation, legacy management). This study has reviewed the literature covering mining and geohazards gathered from the Scopus bibliographic database. Quantitative metadata analysis was conducted on keyword co-occurrence within the 150 selected publications, and thematic clustering was mapped. In addition, five case studies were analysed to add further in-depth analysis. The publication volume shows a sharp uptrend starting around 2015, and 45% of the articles indicate a corresponding author from China. Publications more often cover geohazards in underground mines than open-pit/surface mining. AI methods are a rapidly evolving subject. Overall, the review reveals an imbalance in research attention across different stages of the mine life cycle. While only approximately 6% of the literature addresses exploration-stage geohazards, the case studies demonstrate that early identification is critical. In conclusion, technical capabilities for geohazard monitoring have advanced dramatically, especially with interferometric synthetic aperture radar (InSAR) deformation analysis, machine learning classification, and multi-sensor data fusion; however, the field suffers from systematic integration of geohazards across the mine life cycle. Full article

Excessive chemical fertilization causes orchard soil degradation and fruit quality decline. Organic amendments serve dual functions in nutrient supply and ecological restoration. Yet the causal pathway through which they modulate fruit quality via the rhizosphere microbiome remains poorly understood. This review proposes a cascade framework: “soil amendment → microbiome restructuring → root response → quality formation.” Regulatory evidence at each step is synthesized across organic amendment types. Results indicate that evidence for improvements in soil organic matter and aggregate stability is relatively well established. Shifts in microbial community composition are widely confirmed, yet their associations with soil functions remain predominantly correlative. The causal chain from microbiome to fruit quality has been validated in only a few cases; most underlying mechanisms remain hypothetical. These effects are modulated by tree species, rootstock, soil type, climate, and application regime, and are accompanied by risks of pathogen introduction and heavy metal accumulation. Priority research directions are proposed, including nutrient-matched controls, isotope tracing, re-inoculation of synthetic microbial communities, and multi-site long-term field trials. These directions aim to provide a scientific basis for reducing chemical fertilizer use while enhancing production efficiency in orchards. Full article

The rapid global expansion of solar photovoltaic (PV) capacity has increased the operational need for accurate generation forecasting to support grid balancing, dispatch, and market participation. Artificial intelligence (AI) and machine learning (ML) methods now dominate this research area, but the resulting literature is large and methodologically fragmented, making it difficult to establish which methods are used, what data they require, and where the principal gaps lie. This paper combines a bibliometric analysis of 3111 records retrieved from the Web of Science Core Collection (2010–2026) with a technical synthesis of 27 highly cited studies published from 2022 onward, combining the most highly cited works with targeted additions from 2024–2025 covering specific methodological gaps. The bibliometric analysis shows exponential growth in annual output, from three publications in 2010 to 609 in 2025, with keyword evolution tracing a clear methodological trajectory from classical and fuzzy-logic approaches, through shallow and deep neural networks, to transformer- and attention-based architectures since 2023. The technical synthesis finds that classical machine learning remains competitive for day-ahead forecasting with well-structured numerical weather prediction inputs, that convolutional neural network–long short-term memory (CNN-LSTM) hybrids dominate the deep-learning literature, and that graph-based and transformer architectures address multi-site and multi-horizon forecasting, respectively. A comparison of reported results shows that absolute error metrics are not directly comparable across studies due to heterogeneous datasets, metrics, temporal resolutions, and climates, although relative improvements within controlled comparisons are directionally consistent. Seven research gaps are identified, including the absence of standardized benchmarks, limited public dataset availability, weak cross-region generalization, and underdeveloped uncertainty quantification. Full article