Search Results (374)

Precision agriculture is a key technology for addressing challenges such as increasing food demand, labour shortages, and the environmental impact of intensive agrochemical use. In this context, selective weed management remains a critical issue due to its direct effect on crop productivity and sustainability. This article presents a simulation-based framework for the design and evaluation of an agricultural robotic module for the detection, classification, and selective intervention of weeds. The proposed system integrates convolutional neural networks and the kinematic model of a 2DOF robot manipulator with 5 links for weed classification and treatment. The system is evaluated in a virtual environment, where camera calibration, perception accuracy, and the performance of the kinematic model are analysed. Quantitative results include detection accuracy, localization error, and intervention success rate under simulated field conditions. The results demonstrate selective weed management and the feasibility of simulation for developing weed control systems, while also identifying the main challenges for real-world deployment. Full article

Under maize–soybean rotation systems, weeds and crops at the seedling stage in dryland fields exhibit high similarity in morphological structure, scale distribution, and spatial arrangement. In addition, complex illumination conditions, occlusion, and background interference further complicate accurate weed discrimination. To address these challenges, this study proposes an improved YOLOv11n-based weed detection method for seedling-stage crops under dryland rotation conditions, aiming to enhance detection accuracy and robustness in UAV-acquired field images. Three key improvements were introduced to enhance model performance: (1) the incorporation of Dynamic Convolution (DynamicConv) to adaptively strengthen feature representation for weeds with varying morphologies and scales in low-altitude remote sensing imagery; (2) the design of a SlimNeck lightweight feature fusion architecture to improve multi-scale feature propagation efficiency while reducing computational cost; (3) the cascaded group attention mechanism (CGA) is integrated into the C2PSA module, thereby improving discrimination capability under complex background conditions. These results represent consistent improvements over baseline models, including YOLOv5, YOLOv6, YOLOv8, YOLOv11, and YOLOv12. Specifically, detection performance for broadleaf weeds and Poaceae weeds reached mAP@0.5 values of 87.2% and 73.9%, respectively. Overall, the proposed method demonstrates superior detection accuracy and stability for seedling-stage weed identification under rotation conditions, providing reliable technical support for variable-rate herbicide application and precision field management. Full article

Reliable identification of weed species is essential for effective and sustainable weed management. In this study, we explored the use of hyperspectral imaging to distinguish nine weed species based on their spectral signatures. Although the species showed similarities in their spectral curves due to comparable growing conditions, clear differences emerged related to morphological traits and pigment composition. We analysed the spectral data using five classification algorithms: Random Forest, Support Vector Machine, Artificial Neural Network, Maximum Entropy, and SIMCA. Model performance was assessed using per-class and overall accuracy. Random Forest outperformed the other methods, achieving 93.5% accuracy despite limited and imbalanced training data. This work contributes to the development of a spectral library for weed species and demonstrates the value of machine learning for species identification across different crops and environmental conditions. Expanding such spectral databases can enhance the speed and accuracy of weed monitoring, reduce herbicide reliance, and reduce environmental impact. The proposed approach shows strong potential for integration into precision agriculture and agroecological monitoring systems, supporting more efficient and environmentally responsible farmland management. Full article

Teff [Eragrostis tef (Zucc.) Trotter] is attracting growing interest in Europe due to its nutritional qualities, gluten-free nature, and drought tolerance; however, its cultivation is hindered by its limited yield potential and the lack of authorised herbicides. This study evaluated chemical and mechanical weed-control strategies using two sowing methods to identify effective and sustainable solutions under central Italian conditions. Two field trials were conducted in 2023 and 2024 using a randomised block design. Post-emergence herbicides and mechanical control (split-hoe and finger-weeder) were assessed for weed suppression, crop selectivity, biomass production, and grain yield, comparing broadcast and wide-row sowing. The results showed that chemical control was the most effective option. The florasulam + fluroxypyr + pyroxsulam mixture achieved a nearly complete weed suppression with only mild and temporary phytotoxicity. Mechanical control provided a moderate and variable efficacy. The sowing pattern significantly influenced the crop performance: broadcast sowing reduced the weed competition and resulted in higher yields, whereas wide-row sowing led to a higher weed density and lower productivity. Despite the varying levels of infestation between years, teff maintained a remarkable competitive ability, with untreated plots often achieving acceptable yields. Integrating selective herbicides with appropriate sowing practices supports the development of efficient and sustainable weed-management strategies for teff cultivation. Full article

Weed management is crucial for the sustainable production of rice (Oryza sativa L.), although herbicides such as Imazamox (IZX) can persist in soils, posing risks to soils and water resources. This two-year study evaluated the effects of soil physicochemical properties under different irrigation and tillage practices, with and without compost derived from olive mill waste, on IZX behavior. The treatments implemented were as follows: no-tillage and sprinkler (NT-S), conventional tillage and sprinkler (T-S), conventional tillage and flooding (T-F), and the corresponding regimes with compost amendment (NT-SC, T-SC, and T-FC). Sorption–desorption, dissipation, and leaching of the herbicide were assessed. The IZX adsorption was lower under soil collected from sprinkler irrigation, especially in NT-S, while compost reduced the adsorption under T-SC and T-FC. Dissipation was faster in NT-S and T-S soils, in which the half-life of IZX declined up to 30% relative to T-F. Furthermore, compost further accelerated herbicide dissipation, correlating with higher organic carbon content and microbial activity. The IZX losses via leaching were significantly reduced in soils irrigated by sprinkler in combination with compost, with values ≤ 48.5% of the IZX applied. These results indicate that the irrigation regime and organic amendment strongly influence soil physicochemical properties, then influencing the environmental fate of IZX. Integrated management using sprinkler irrigation and compost can mitigate IZX persistence and leaching, improve soil health, and reduce the risk of water contamination, representing a sustainable strategy for rice cultivation. Full article

Climate change, together with intensifying human activities, is reshaping global plant invasion dynamics and increasingly threatening ecosystem stability and biodiversity. Cockleburs are highly invasive weeds with strong ecological plasticity and dispersal capacity, causing widespread impacts on agricultural systems and native ecosystems. Here, we used the maximum entropy (MaxEnt) model to assess the current (2001–2020) and future (2021–2040, 2041–2060, and 2061–2080) potential distributions, key driving factors, and centroid shifts of four invasive cocklebur species—Cyclachaena xanthiifolia (=Iva xanthiifolia), Xanthium chinense, Xanthium italicum, and Xanthium spinosum—at the global scale under current climate conditions and three Shared Socioeconomic Pathway scenarios (SSP126, SSP245, and SSP585). Species occurrence records were integrated with climatic, topographic, and anthropogenic variables to project habitat suitability. Model performance was robust, with mean training and testing area under the receiver operating characteristic curve (AUC) values > 0.8 for all species and mean true skill statistic (TSS) values > 0.8 for three species (0.660 for Xanthium spinosum). Suitable habitats were jointly shaped by climatic and anthropogenic factors, although the dominant drivers differed among species. Cyclachaena xanthiifolia and Xanthium spinosum were primarily constrained by temperature and precipitation, whereas Xanthium italicum and Xanthium chinense were more strongly associated with human activity. At present, suitable habitat areas for Cyclachaena xanthiifolia, Xanthium chinense, Xanthium italicum, and Xanthium spinosum were 1196.92 × 10⁴, 358.76 × 10⁴, 888.34 × 10⁴, and 1985.14 × 10⁴ km², respectively. Future projections indicated overall contractions in suitable habitat, with pronounced interspecific variation. Xanthium chinense showed the largest mean decline (−161.23 × 10⁴ km² relative to the present), whereas Cyclachaena xanthiifolia experienced the smallest reduction (−53.15 × 10⁴ km² on average). Centroid analyses further suggested overall shifts toward higher latitudes and elevations under warming scenarios. Despite uncertainties related to climate scenario variability and assumptions inherent in species distribution modelling, these findings provide quantitative evidence to support global invasion risk assessment and climate-adaptive management of invasive cockleburs. Full article

Herbicides have been pivotal tools but decreasing their use is currently a political and societal priority to minimize the risk for human health and the environment and to hinder the evolution of herbicide resistance. A 3-year experiment was conducted to compare three weed management strategies in winter wheat fields in northern Italy: (1) sole chemical control, (2) sole mechanical control, or (3) their combination. Agronomic and economic performances of the three strategies were assessed. Large variability of weed presence and crop yield was observed across the three years. Higher weed biomass was observed in the mechanical management, while the lowest weed presence and cost for weed control was estimated for the chemical management. Conversely, no differences were observed across the three management strategies in terms of crop yield or net return. The results confirmed that herbicides are currently the most cost-effective control tools, but the continuous variation in prices and costs can modify this situation. Thus, the economic assessment should be periodically updated to remain valid. However, the lack of differences between managements in terms of wheat grain yield or net profit suggested that mechanical or combined weed control can be sustainable alternatives for wheat production in northern Italy. Nevertheless, to ensure the long-term sustainability of weed management strategies with low or no herbicide use, a more holistic approach should be considered, involving a diversified set of control tactics arranged throughout the whole crop rotation. Full article

The potential withdrawal of glyphosate necessitates a comprehensive evaluation of alternative weed control strategies that balances human health safety with environmental concerns. This study applied a decision-support grid to compare the impacts of glyphosate-based reference strategies against chemical and non-chemical alternatives across four Belgian case studies: pome fruit orchards, grassland renewal, arable weed patches, and railways. The assessment integrated twelve risk indicators including human, environmental and biodiversity risk, and life cycle assessment for global warming potential (GWP) into a Final Scenario Score (FSS). The results indicated that only one alternative strategy, the chemical alternative in local weed patch control, achieved the FSS threshold (<0.75) required to justify substitution (FSS = 0.70). Chemical alternatives in other case studies frequently shifted burdens; for instance, bio-herbicides in railways increased risks to residents and aquatic organisms compared to the reference. Conversely, mechanical and thermal alternatives eliminated chemical toxicity but resulted in GWP increases up to 32 times higher than glyphosate-based practices. These findings demonstrate that chemical substitutes often maintain toxicity risks while non-chemical strategies trade them for increased climate impacts. Consequently, a ban on glyphosate is currently unsupported by the environmental performance of available alternatives in these temperate high-intensity systems. Sustainable progress requires a transition period where optimized conventional strategies remain available within integrated weed management, while innovations in electrification and precision technology are accelerated to resolve current trade-offs. Full article

Ornamental horticulture represents one of the dominant pathways for the introduction of alien plant species and has played a central role in shaping current and future invasion dynamics. Many ornamental plants escape cultivation after long lag phases, driven by high propagule pressure, human-mediated selection of functional traits, and increasing climatic suitability. As a result, ornamental species contribute substantially to Europe’s invasion debt, with many future invasions already “locked in” under ongoing global change. In this review, we synthesize current knowledge on the invasive risk of ornamental plants in Europe, examining introduction pathways, biological traits promoting invasiveness, the role of climate change, and the ecological, economic, and social impacts associated with ornamental plant invasions. We highlight that beyond biodiversity loss, invasive ornamental plants pose underappreciated threats to agriculture and related activities, including increased management costs, weed problems in managed landscapes, and disruption of water management and irrigation infrastructure, particularly through invasive aquatic species. We further review tools for risk assessment and prevention, including weed risk assessment frameworks, green lists, horizon scanning, and climate-informed spatial forecasting, emphasizing the importance of proactive, pathway-based approaches. Where prevention fails, management of established invasive ornamentals relies on integrated strategies combining mechanical, chemical, and biological control, often generating large quantities of biomass and long-term economic costs. We discuss the emerging but still limited potential of invasive plant biomass valorization as a complementary management option, highlighting both opportunities and constraints. Finally, we discuss implications for horticultural practices, policy development, and future research, arguing that reconciling ornamental horticulture with biodiversity conservation and sustainable agriculture will require anticipatory governance, stakeholder engagement, and climate-aware decision-making. By aligning horticultural innovation with invasion risk awareness, it may be possible to reduce future invasions while maintaining the social and economic benefits of ornamental plant use in Europe. Full article

In recent years, agriculture has begun to transform thanks to the arrival of robots and autonomous vehicles capable of performing complex operations such as weeding and spraying in an intelligent and targeted manner. In fact, new-generation agricultural robots use artificial intelligence (AI), cameras, and sensors to recognise weeds, analyse crop conditions, and apply plant protection products only where necessary, thus reducing waste and environmental impact. Some systems combine drones and ground vehicles to achieve even more accurate results. This systematic review synthesises recent advances in agricultural robotics for weed and pest management through a PRISMA-based approach. Literature was collected from major scientific databases (Scopus, Web of Science, IEEE Xplore, Google Scholar) and complementary sources, leading to the inclusion of 83 eligible studies. The selected evidence was structured into four application domains: (i) weed detection and mapping, (ii) robotic and non-chemical weed control (mechanical and laser-based approaches), (iii) selective/variable-rate spraying for pest and disease management, and (iv) integrated weeding–spraying solutions, including cooperative Unmanned Aerial Vehicle–Unmanned Ground Vehicle (UAV–UGV) systems. Overall, the reviewed studies confirm rapid progress in real-time perception (deep learning-based detection), navigation/localization (e.g., GNSS/RTK, LiDAR, sensor fusion) and targeted actuation (spot spraying and precision interventions), while also revealing persistent limitations: heterogeneous evaluation protocols, limited system-level comparisons in terms of work rate, scalability, costs and robustness under variable field conditions, and an often unclear distinction between prototype platforms and solutions close to commercialization. However, the large-scale spread of these technologies is still hampered by high costs, technical complexity, and cultural resistance. The review highlights how the integration of automation, sustainability, and accessibility is key to the agriculture of the future. Full article

Laser radiation constitutes a promising technological advancement within the integrated weed management toolbox but is hindered by low energy use efficiency. This study investigated the efficiency of a pulsed blue diode laser for controlling small weed seedlings and seeds under controlled conditions. Dose–response experiments were conducted on three grasses (Poa annua, Echinochloa crus-galli, Digitaria sanguinalis) and three dicotyledonous species (Solanum nigrum, Chenopodium album, Senecio vulgaris). For seedlings, the effects of species, growth stage (cotyledon, 2-leaf), and leaf wetness (dry, wet) were tested. For seeds, burial depth (0 mm, 2 mm) and imbibition status (non-imbibed, imbibed) were examined. Biological efficiency was assessed through plant survival, aboveground dry biomass, leaf area, and seed viability. Laser application caused significant, dose-dependent reductions in biomass accumulation and plant survival, with up to 100% mortality. Seedlings were most sensitive at the cotyledon stage and when foliage was dry, requiring up to 68 and 52% lower energy doses compared to older or wet targets, respectively. Species-specific responses were observed, with dicotyledonous species generally requiring 80 to 99% lower energy doses than grasses. Laser exposure was also effective in reducing the viability of non-imbibed, surface-exposed seeds, requiring up to 64 and 99% lower energy doses than imbibed or buried seeds, respectively. These results confirm that laser efficiency is strongly influenced by species traits, developmental stage, surface moisture, and seed water status. Optimising and tailoring laser parameters to these factors enhances weed control efficacy while maximising energy efficiency, improving the performance and sustainability of laser-based weeding. Full article

Agroecosystems comprise various components, including weeds, insects, and microorganisms, which interact with one another and play distinct roles in achieving sustainable agriculture. This balance is essential for both agricultural productivity and environmental preservation. This study explores the relationship between diversity and ecological functions of weed species and the entomofauna present in a pasture under rotational grazing and organic management in Otavalo, Ecuador. Sampling was conducted over an area of 2.5 hectares. We identified and counted weeds using 65 quadrats, each measuring 4 m². To capture insects, we employed chromatic traps, pitfall traps, and entomological nets. The results indicated a medium level of biodiversity, as shown by the Margalef index (4.85) and the Shannon–Wiener index (2.23), which also suggested a medium to dispersed evenness (Pielou_J = 0.23). Additionally, the ecosystem exhibited low species dominance, indicated by the Simpson index (D = 0.20). In total, we recorded 55 species belonging to 24 different botanical families. The most abundant families were Fabaceae (39%), Poaceae (21%), and Plantaginaceae (14.6%). For the entomofauna, a rich community was identified, comprising twelve orders and fifty families, with the order Diptera being predominant. Crucially, these findings demonstrate that agroecological practices foster a significant presence and diversity of both weed plants and associated insects, contributing to the agroecosystem’s resilience. We emphasize the role of diverse weed flora as refuges and resource providers for beneficial insects, such as those from the highly abundant Tachinidae family (Diptera), which are key natural regulators. This research highlights the importance of integrating weed conservation into pasture management for enhancing biodiversity, natural pest regulation, and promoting sustainable local transformation in highland agricultural landscapes. Full article

Carvone-rich essential oils (EOs), and carvone specifically, exhibit a broad spectrum of protective effects against major agricultural threats. They display strong antifungal and moderate antibacterial effects, effectively inhibiting numerous phytopathogenic fungi. EOs exhibit significant insecticidal, acaricidal, and repellent activity against various insects and mites, and some EOs are highly effective against agricultural nematodes, suppressing mobility and egg hatching. Crucially, the EOs demonstrate a strong capacity to suppress the germination and initial growth of different weed species, highlighting their viability as natural herbicides. This review analyzes the chemical composition, biological effects, and potential agricultural applications of carvone and carvone-rich essential oils, primarily sourced from Mentha spicata (Lamiaceae), Carum carvi (Apiaceae), and Anethum graveolens (Apiaceae). The biological activity of these EOs is significantly influenced by their specific composition, which varies among plant species and chemotypes. While EOs’ inherent volatility limits direct field application, this challenge is being successfully addressed by innovative formulation technologies, such as nanoemulsification and encapsulation, which enhance stability, bioavailability, and targeted delivery. In conclusion, carvone-rich EOs offer effective, environmentally low-risk agents for the integrated management of pathogens, pests, and weeds in sustainable agriculture. They help reduce reliance on synthetic chemicals and minimize the potential for resistance development. Full article

Agriculture must balance productivity with greenhouse gas emissions, biodiversity, and resource concerns. This study examined how tillage (conventional, CT; minimum, MT), nitrogen fertilisation (0–221 kg N ha⁻¹), and herbicide rates (0–100%) interactively affected soil CO₂ emissions, vegetation vigour, and weed diversity in maize production during 2022. A factorial experiment was conducted on a 1 ha with 40 plots monitored soil temperature, moisture, penetration resistance, normalised difference vegetation index (NDVI), weed diversity (Simpson’s Index), and CO₂ emissions (closed-chamber method). Minimum tillage increased soil water retention (9.3 ± 6.5% vs. 5.4 ± 4.3%), soil temperature (28.0 ± 1.5), and compaction (0.6 ± 0.3 vs. 0.1 ± 0.0 MPa), while enhancing weed diversity (0.53–0.80 vs. 0.38–0.67). MT produced higher CO₂ emissions than CT, especially at 147 kg N ha⁻¹ (49.9 ± 15.7 vs. 29.1 ± 11.6 μmol m⁻² s⁻¹), peaking under MT-147 kg N ha⁻¹-H75 (79.4 ± 1.2 μmol m⁻² s⁻¹). NDVI responses varied between tillage systems; under CT, vegetation vigour peaked at 75% herbicide application, while under MT vegetation was more responsive to nitrogen and more sensitive to herbicide, highlighting nitrogen × herbicide interaction trade-offs. Overall, MT enhanced water conservation and weed diversity but increased short-term CO₂ emissions. This study reports first-year, site-specific results from an ongoing multi-year field experiment; therefore, the findings were interpreted as short-term, season-specific responses. This highlights the need for site-specific, climate-smart management that integrates emissions, soil health, biodiversity, and productivity. Full article

Soil management is crucial for addressing soil-borne pathogens, weeds, and pests, ensuring sustainable crop productivity. Traditional chemical fumigants, such as methyl bromide, have been effective but pose serious environmental risks, including ozone depletion and reduced soil biodiversity. Consequently, attention has shifted toward more sustainable alternatives. Techniques like soil solarization, anaerobic soil disinfestation (ASD), biofumigation, and the use of biological control agents (BCAs) offer environmentally friendly options for managing soil-borne diseases. Steam and microwave disinfestation are also promising techniques; however, further development is required to improve their practical efficiency. Integrated management approaches, which combine multiple interventions, have proven particularly effective, offering flexibility and enhancing control through complementary techniques. Additionally, emerging technologies such as artificial intelligence and hyperspectral imaging provide new opportunities for real-time monitoring and decision-support to optimize the timing and targeting of pest management interventions. This review emphasizes the potential of sustainable soil pest control methods to reduce reliance on chemical fumigants, improve crop yield and quality, and support environmentally responsible farming practices. It also examines the challenges associated with scalability, cost, and variable effectiveness, while outlining the strengths, weaknesses, and mechanisms of each method. Further research on regional adaptation, technological integration, and long-term impacts is essential to fully optimize these innovative solutions for food security and sustainable agriculture. Full article