Search Results (222)

Sugarcane is a high-value crop in Egypt, yet weed communities in the understudied Upper Egypt region have not been systematically characterized. This study provides a comprehensive analysis of weed floristic composition, phytogeographical affinities, and the edaphic and canopy light factors governing vegetation structure across contrasting Nile Valley clay and reclaimed desert lands in Qena Governorate. Fourteen stands were surveyed during the 2024/2025 sugarcane growing season, recording 110 species from 33 families (68 annuals and 42 perennials), which were dominated by Poaceae, Asteraceae, Fabaceae, Euphorbiaceae, and Amaranthaceae (54.6% of the flora recorded). Therophytes were the most abundant life form (60.9%), and 51.8% of species belonged to Neotropical, Palaeotropical, Cosmopolitan, and Pantropical chorotypes. Diversity indices showed high and balanced species diversity, with no dominance by any single species. Seasonal variation showed that species richness peaked in spring, decreased through summer and autumn, and correlated with light intensity under the canopy. TWINSPAN identified four vegetation groups, which were merged into three primary vegetation groups (A, B, and C) via DCA and CCA ordinations and linked to microhabitats shaped by elevation and soil physicochemical properties. CCA revealed that Group C (stands in the Nile Riverbank lands) had the highest diversity, which was associated with organic matter, clay, and field capacity. In contrast, Group A (stands of reclaimed desert land) had low richness linked to high levels of Total Dissolved Solids (TDS), Electrical Conductivity (EC), Na, K, Mg, CaCO₃, and sandy soils. Group B (stands of Nile clay lands) was an intermediate transitional community between groups A and C. These findings establish edaphic factors as the primary determinant of weed community structure, with salinity as the critical constraint in reclaimed lands and seasonal light variation as a secondary diversity filter. Full article

Deltas are highly susceptible to biological invasions because of strong hydrological connectivity, frequent disturbance, and intense human use. Here, we synthesise coordinated monitoring observations and literature evidence on invasive alien plant species (IAS) recorded in four Black Sea riparian protected areas located across five countries, surveyed under the IASON/IASON+ initiatives (Danube Delta, Nestos Delta and Lake Vistonida, Kızılırmak Delta, Chorokhi Delta and Kolkheti National Park). Across the study sites, 17 IAS were documented, mainly represented by taxa native to North America and characterised by high propagule production and/or strong vegetative regeneration. Woody riparian invaders (e.g., Amorpha fruticosa, Robinia pseudoacacia, Acer negundo, Gleditsia triacanthos and Ailanthus altissima) exploited nutrient-rich floodplain soils and disturbances. In contrast, annual weeds (e.g., Ambrosia artemisiifolia, Sicyos angulatus and Xanthium orientale) remained associated with disturbed habitat edges. Aquatic dominance was confined to the Danube Delta, where Elodea nuttallii and Elodea canadensis formed dense submerged stands. Species were assigned to broad range expansion categories (slowly, moderately and rapidly spreading species) based on project observations and supporting records. We discuss shared invasion syndromes linked to reproductive and dispersal traits and outline management implications for Black Sea deltas, emphasising pathway prevention, early detection and rapid response for localised taxa, and sustained control combined with restoration for dominant invaders. Full article

Aquatic ecosystems worldwide are increasingly threatened by invasive species, with water hyacinth [Eichhornia crassipes (Mart.) Solms] being among the most destructive aquatic weeds. Despite numerous regional studies, a global assessment integrating climatic and hydrological drivers remains lacking. Here, we assessed current and future invasion risks across 55,945 freshwater lakes using the maximum entropy (MaxEnt) model. Climatic variables and key aquatic parameters, including biological oxygen demand (BOD), water depth, and discharge, were incorporated under two shared socioeconomic pathways (SSP2-4.5 and SSP5-8.5). Annual mean temperature, annual precipitation, and BOD were the strongest predictors of habitat suitability. Under current conditions, 5524 lakes, primarily in tropical and subtropical regions, were identified as being suitable habitats, with medium-sized lakes exhibiting the highest proportional suitability (16.54%). Although small lakes were most frequently classified as suitable due to their abundance, larger lakes showed higher suitability intensity. Future projections indicated marked habitat expansion, especially under SSP5-8.5, with suitable lake surface area increasing to 18.12% by 2061–2080. Moreover, 543 currently unsuitable lakes, including Lake Erie, Lake Huron, and Lake Ontario, were projected to face elevated invasion risk, particularly in Africa, South Asia, Southeast Asia, and North America. This global, lake-specific assessment supports early warning, targeted management, and climate-responsive policy planning. Full article

Weed control of solanaceous weeds growing with solanaceous crops is a constant challenge. Infected by viruses, they can also act as virus reservoirs, complicating this problem further. Viromes of annual Solanum nigrum, Datura stramonium, and Solanum dulcamara, a perennial climbing shrub, were investigated using RNA sequencing and validated using RT-PCR, revealing infection with nine viruses. Broad bean wilt virus 1 (BBWV1), cucumber mosaic virus (CMV), and potato virus M (PVM) were found to infect S. nigrum. Investigating only 46 plants revealed infection with Solanum dulcamara yellow fleck virus (SDYFV) not only in S. dulcamara but in a new host, D. stramonium, which also represents a new host of turnip yellows virus (TuYV). We described the first presence of a potato virus H (PVH)-like, and Oxybasis rubra mitovirus 1 (OxruMV1)-like virus in Europe, in S. dulcamara as a new host. Our results highlight the unexpected complexity of the viromes of solanaceous weeds, which should be considered during reliable and efficient plant protection strategies, in order to alleviate the virus reservoir role of the weeds. Full article

Using high-resolution field data from the Yunnan Provincial Grassland Pest Survey and an optimized MaxEnt model, we compared the climate-driven habitat dynamics of two invasive Asteraceae weeds (Chromolaena odorata, Ageratina adenophora) and a native weed (Cirsium japonicum). We assessed whether invasive and native weeds differ in environmental responses, future range dynamics, and management strategies, and three novel patterns were revealed. First, the invasive Chromolaena odorata exhibits a sustained positive response to mean annual temperature (contribution 67.6%), while the native Cirsium japonicum shows a strictly unimodal response with a narrow optimum (0–10 °C, contribution 46.4%) and high-temperature sensitivity, projecting over 50% habitat loss by the 2050s under high emissions. Second, the invasive Ageratina adenophora displays a southern contraction versus northern expansion pattern under high emissions (current highly suitable area ~9.12 × 10⁴ km²), suggesting that extreme warming may enable it to breach high-altitude barriers. Third, all three species show unimodal responses to human disturbance with species-specific optima. Overall, the invasive species, leveraging broad ecological amplitudes and strong adaptability, are poised for continued expansion of their potential suitable habitat, while the native species, constrained by a narrow niche and limited dispersal capacity, faces systemic habitat loss. These findings provide a mechanistic basis for differentiating management strategies between invasive and native problematic weeds in Yunnan grasslands. Full article

Cover crops (CCs) provide key ecosystem services, including nitrogen (N) retention and increased soil organic carbon (SOC), although their short-term benefits may be limited in dry continental climates. This study assessed a conservation system combining CC and non-inversion tillage (MT+CC) over a full crop rotation (sunflower–winter wheat–corn–sunflower) in south-eastern Romania, compared with plough-based tillage (PT). A randomized block design was conducted on a clay loam Luvisol, and N retention was estimated annually from soil mineral N and the biomass and N content of CC and weeds. MT+CC increased N retention during the first three years (+20.30 kg ha⁻¹ before corn; +26.67 kg ha⁻¹ before sunflower), but this advantage declined, and in year four PT showed higher N retention due to intensive weed growth. MT+CC reduced corn and sunflower yields, likely because of water competition and temporary N immobilization, but increased winter wheat yields. After four years, SOC was significantly higher under MT+CC (1.42%) than PT (1.37%), while total N remained unchanged, resulting in a higher C:N ratio. Consequently, in continental climates, CC use has a limited N retention potential, and excessively late CC sowing and termination is risky in crop rotations dominated by high-N-demand spring crops. Full article

Reservoir operation under climate change poses significant challenges for hydropower-dependent countries, particularly in cascade reservoir systems. This study aims to derive optimal future operating rule curves for the Nam Khan 2 and Nam Khan 3 cascade reservoirs in Lao PDR to maximize hydropower generation under climate change. Genetic Algorithm (GA), Invasive Weed Optimization (IWO), and Harmony Search (HS) were integrated with a reservoir simulation model to optimize monthly upper and lower rule curves. Future reservoir inflows were generated using climate projections from the INM-CM5-0 climate model’s SSP245 scenario for 2025–2050. The aim was to maximize average annual electricity generation for the entire cascade system while ensuring practicable reservoir operation. The optimized rule curves obtained from all three algorithms exhibited similar seasonal patterns, reflecting regional hydrological characteristics. The proposed rule curves significantly improved hydropower performance compared to the existing operating policies. For Nam Khan 2, average annual electricity generation increased from 324.089 GWh under current operations to 788.246, 787.100, and 786.561 GWh using GA, IWO, and HS. Similarly, Nam Khan 3 achieved substantial improvements, with average annual generation increasing from 156.029 GWh to 270.049, 266.840, and 266.547 GWh. The optimized rule curves also contributed to better storage regulation and reduced variability in energy production. The findings demonstrate that integrating metaheuristic optimization techniques with reservoir simulation models provides an effective framework for adaptive hydropower-oriented reservoir operation under future climate uncertainty. Full article

Tree intercropping systems with leguminous cover crops and aromatic plants may provide sustainable yields, which could be improved by beneficial microbes (BMs) and zeolite, while their effects on young tree growth remain unclear. We tested whether such systems enhance early growth in young carob trees compared with conservation tillage (TLG) trees growing under rainfed semi-arid conditions. Intercropping included carobs with (i) Lathyrus ochrus, Trifolium squarrosum, and Lens culinaris combined (CC-System), (ii) Thymbra capitata planted between legumes (CCT-System), and soil amended with (iii) BM (Micosat-F-Olivo) and zeolite. All systems outperformed TLG in annual tree height increase with the CC-System excelling (TLG +13%, CC-System +42%; p < 0.05). The CC-System also significantly outpaced TLG in stem thickening (TLG 62%, CC-System 167%; p < 0.01) with BM and/or zeolite also appearing as beneficial. Improved performance was related to significantly higher dry season soil moisture, while a high L. ochrus abundance reduced thyme survival (p < 0.01). The CCT-System was also found to be less capable in weed suppression during a wet year. Thus, applying our legume intercropping system (with BM/zeolite) represents an effective nature-based solution for enhancing young carob tree growth under rainfed conditions, while adding thyme may somewhat trade productivity for biodiversity and associated ecosystem services. Full article

Continuous cropping leads to declines in soil productivity and biodiversity, as well as a deterioration of overall phytosanitary conditions. What if we rotate the intercrops instead of the main crops? In a stationary three-year field experiment, maize was intercropped with Fabaceae (faba bean, crimson and Persian clovers, and blue-flowered alfalfa), Poaceae (winter rye, annual ryegrass, spring barley, and common oat), and Brassicaceae (white mustard, spring oilseed rape, oilseed radish, and spring Camelina) intercrops in separate growing seasons. Fabaceae intercrops developed slowly and competed poorly with weeds. The highest air-dried biomass (ADM) was produced by Persian and crimson clovers (approx. 86 g m⁻²). Intercrops of the Poaceae family, particularly rye and oats, as well as ryegrass, which was the most productive at 200 g m⁻² ADM, germinated faster and competed effectively with weeds. Brassicaceae intercrops also developed rapidly, especially mustard, Camelina, and radish (the most productive 206 g m⁻² ADM). Most intercrops competed with maize and reduced its biomass productivity; however, their competitive effects were weaker than those of weeds. A strong negative correlation between maize and weed biomass was detected (max. r = −0.946; p < 0.01). Complex evaluation index (CEI) showed that the crimson clover–annual ryegrass–spring oilseed rape rotation (CC-AR-SR) was the most productive and was effective in suppressing major weeds Echinochloa crus-galli, Chenopodium album, Polygonum lapathifolium, and Cirsium arvense, less competitive with maize (CEI 4.82), and can be used as an Integrated Pest Management tool. Full article

Bidens pilosa L. is a cosmopolitan and invasive weed that strongly impacts agricultural systems in tropical regions. In Veracruz, Mexico, its presence extends mainly across mid-elevation zones where coffee, maize, and sugarcane are cultivated. This study characterized the bioclimatic and edaphic determinants of B. pilosa distribution using 581 georeferenced occurrences combined with 19 bioclimatic variables, elevation, and soil data. A Maxent model revealed the highest habitat suitability (0.65–1.0) in the central mountainous region between 800 and 1500 m.a.s.l., particularly under temperate–humid climates (Cfa, Cfb) and Acrisol–Leptosol soils. Principal component and redundancy analyses showed that annual precipitation (BIO12), precipitation of the driest month (BIO14), and temperature seasonality (BIO4) explained 74.7% of the total environmental variance. Cluster analysis identified four distinct ecological groups, confirming broad ecological plasticity. These findings indicate that B. pilosa is not randomly distributed but structured along climatic and soil gradients, with precipitation and elevation as major determinants of its ecological niche. Understanding these relationships provides a quantitative framework for predicting its expansion under future climate scenarios and for designing targeted management strategies in tropical agroecosystems. Full article

The global food crises and growing population necessitate efficient agricultural land use. Weeds cause up to 40% yield loss in major crops, resulting in over USD 100 billion in annual economic losses. Camera-equipped UAVs offer a solution for automatic weed detection, but the high computational and energy demands of deep learning models limit their use to expensive, high-end UAVs. In this paper, we present a low-cost UAV system built from off-the-shelf components, featuring a custom-designed on-board computing system based on the NVIDIA Jetson Nano. This system efficiently manages real-time image acquisition and inference using the energy-efficient Squeeze U-Net neural network for weed detection. Our approach ensures the pipeline operates in real time without affecting the drone’s flight autonomy. We also introduce the AgriAdapt dataset, a novel collection of 643 high-resolution aerial images of salad crops with weeds, which fills a key gap by providing realistic UAV data for benchmarking segmentation models under field conditions. Several deep learning models are trained and validated on the newly introduced AgriAdapt dataset, demonstrating its suitability for effective weed segmentation in UAV imagery. Quantitative results show that the dataset supports a range of architectures, from larger models such as DeepLabV3 to smaller, lightweight networks like Squeeze U-Net (with only 2.5 M parameters), achieving high accuracy (around 90%) across the board. These contributions distinguish our work from earlier UAV-based weed detection systems by combining a novel dataset with a comprehensive evaluation of accuracy, latency, and energy efficiency, thus directly targeting deep learning applications for real-time UAV deployment. Our results demonstrate the feasibility of deploying a low-cost, energy-efficient UAV system for real-time weed detection, making advanced agricultural technology more accessible and practical for widespread use. Full article

Cyperus esculentus is a very destructive perennial weed, rapidly propagating and spreading through large amounts of daughter tubers. Successful control relies on depleting the soil tuber bank. This study investigated the effect of different control measures, applied across several cropping systems, on tuber bank dynamics over time. Therefore, 52 infested fields were monitored over 3 consecutive years, with annual quantification of the C. esculentus tuber bank. In maize monocropping systems, substantial 3-year tuber bank reductions (>90%) are achievable with preplant incorporation of dimethenamid-P or S-metolachlor, followed by a post-emergence application of mesotrione and pyridate at the 4–5 leaf stage, combined with delayed sowing (after 20 May) or mechanical measures (e.g., hoeing, harrowing). On non-maize fields, effective strategies (median tuber bank reductions of 57–70%) include intensive black fallow with at least four control timings or winter cereal cropping followed by intensive control (at least three measures) during the stubble phase. Established, fertilized grasslands also offer moderate reductions (17–67%) via intensive grazing or mowing. These results demonstrate that significant C. esculentus reductions are possible across different crops, but control remains challenging, requiring intensive, repeated strategies over multiple years. Less intensive approaches may undermine previous efforts. Full article

Species distribution models (SDMs) grapple with uncertainty. To address this, a parameter-optimized MaxEnt model was used to predict habitat suitability for Elsholtzia densa, a predominant agricultural weed on the Tibetan Plateau. Through multiparameter optimization with 149 occurrence points and three climate variable sets, we systematically evaluated how the three MaxEnt extrapolation approaches (Free Extrapolation, Extrapolation with Clamping, No Extrapolation) influenced model outputs. The results showed the following: (1) Model optimization using the Kuenm R package version (1.1.10) identified seven critical bioclimatic variables (Feature Combinations = LQTH, Regularization Multipliers = 2.5), with optimized models demonstrating high accuracy (Area Under Curve > 0.9). (2) Extrapolation approaches exhibited negligible effects on variable selection, though four bioclimatic variables “bio1 (annual mean temperature)”, “bio12 (annual precipitation)”, “bio2 (mean diurnal range)”, and “bio7 (temperature annual range)” predominantly drove model predictions. (3) Current high-suitability areas are clustered in the eastern and southern regions of the Tibetan Plateau, and with Free Extrapolation yielding the broadest current distribution. Climate change projections suggest habitat expansion, particularly under conditions of No Extrapolation. (4) Multivariate Environmental Similarity Surface (MESS) and Most Dissimilar Variable (MoD) are not affected by the extrapolation method, and extrapolation risk analyses indicate that future climate anomalies are mainly concentrated in the western and southern parts of the Tibetan Plateau and that future warming will further increase the unsuitability of these regions. (5) Variance analysis showed that the extrapolation methods did not significantly affect the 10-replicate results but influenced the parameter and emission scenarios, with No Extrapolation methods showing minimal variance changes. Our findings validate that multiparameter optimization improves species distribution model robustness, systematically characterizes extrapolation impacts on distribution projections, and provides a conceptual framework and early warning systems for agricultural weed management on the Tibetan Plateau. Full article

Organic annual vegetable farming systems often rely on intensive tillage for weed management due to the prohibition of synthetic herbicides. Regenerative organic agriculture aims to improve soil health and reduce the frequency and intensity of soil tillage by using cover crops as high-residue mulches to suppress weeds. In southern coastal California, the moderate climate supports year-round vegetable production, discouraging many growers from integrating cover crops into their operation and leaving sustainability-minded growers with few strategies to produce organic vegetables outside of reliance on tillage. This study evaluates standard organic tillage practices versus high-residue cover-crop mulch system on squash, peppers, and eggplant over two seasons. We assessed treatment effects on soil health indicators, weed pressure, and crop production. Soil under the cover-crop system improved soil organic matter, organic carbon and nitrogen, microbially active carbon, and water infiltration compared to bare soil. Weed biomass was substantially lower under the high-residue mulch due to persistent surface cover. Crop yield was 82%, 169%, and 189% higher in the cover-crop plots for squash, pepper, and eggplant, respectively. These findings demonstrate that high-residue cover-crop systems can enhance soil health, reduce weed pressure, and substantially increase yields, providing evidence-based strategies for implementing regenerative organic practices in vegetable systems. Full article

The objective of this study was to evaluate the impact of two nitrogen doses in combination with strong creeping fescue (Festuca rubra L. ssp. rubra Gaudin) and Chewing’s red fescue (Festuca rubra L. ssp. commutata Gaudin) used as living mulches on the weed community in an apple tree (Malus domestica Borkh.) orchard. The cover grasses were sown in the tree rows, and herbicide fallow served as the control. Grass living mulches effectively reduced the number and share of annual weed cover and limited the spread of perennial plants compared with herbicide fallow. Use of F. rubra L. subspecies did not favor the biodiversity of the orchard agroecosystem flora, due to the effective soil surface coverage by sod in the tree rows. Living mulch sod was characterized by lower variability in weed taxa compared with the abundant weed composition in the herbicide fallow, which also exhibited the highest number of weed taxa each year. Dominant species in the orchard across all treatments included Trifolium repens L. and Taraxacum spp. Doubling the nitrogen fertilization rate, while limiting the application area to the tree canopy, did not increase the perennial weed population in the living mulch sod. Both subspecies are useful as living mulch in a young apple orchard, but from the perspective of sod durability and weed control, strong creeping red fescue offers better prospects. Full article