Search Results (515)

The cultivation of edible lilies is highly susceptible to weed infestation during its growth period, and the application of herbicides is often impractical, leading to the rampant growth of diverse weed species. Laser weeding, recognized as an efficient and precise method for field weed management, presents a novel solution to the weed challenges in lily fields. The accurate localization of weed regions and the optimal selection of laser targeting points are crucial technologies for successful laser weeding implementation. In this study, we propose a two-stage weed detection and localization method specifically designed for lily fields. In the first stage, we introduce an enhanced detection model named YOLO-Morse, aimed at identifying and removing lily plants. YOLO-Morse is built upon the YOLOv8 architecture and integrates the RCS-MAS backbone, the SPD-Conv spatial enhancement module, and an adaptive focal loss function (ATFL) to enhance detection accuracy in conditions characterized by sample imbalance and complex backgrounds. Experimental results indicate that YOLO-morse achieves a mean Average Precision (mAP) of 86%, reflecting a 3.2% improvement over the original YOLOv8, and facilitates stable identification of lily regions. Subsequently, a ResNet-based segmentation network is employed to conduct semantic segmentation on the detected lily targets. The segmented results are utilized to mask the original lily areas in the image, thereby generating weed-only images for the subsequent stage. In the second stage, the original RGB field images are first converted into weed-only images by removing lily regions; these weed-only images are then analyzed in the HSV color space combined with morphological processing to precisely extract green weed regions. The centroid of the weed coordinate set is automatically determined as the laser targeting point.The proposed system exhibits superior performance in weed detection, achieving a Precision, Recall, and F1-score of 94.97%, 90.00%, and 92.42%, respectively. The proposed two-stage approach significantly enhances multi-weed detection performance in complex environments, improving detection accuracy while maintaining operational efficiency and cost-effectiveness. This method proposes a precise, efficient, and intelligent laser weeding solution for weed management in lily fields. Although certain limitations remain, such as environmental lighting variation, leaf occlusion, and computational resource constraints, the method still exhibits significant potential for broader application in other high-value crops. Full article

This study addresses the agricultural requirement for flexible adjustment of planting spacing in seed breeding corn, designing an active rotating in-film hole-forming mechanism driven by an independent motor. The mechanism allows flexible regulation of planting spacing by adjusting the motor speed. The study first optimized the structure of the hole-forming device, selecting a rhombic duckbill as its core component and analyzing its motion trajectory and hole-forming shape. Single-factor experiments were conducted to determine the structural parameter ranges affecting film hole length. Using discrete element and multibody dynamics co-simulation, experiments were carried out with duckbill number, duckbill bottom width, and duckbill bottom height as experimental factors, and film hole length as the response variable, employing a three-factor, three-level orthogonal experimental method. Simulation results indicated that the factors influencing film hole length, in descending order of impact, were duckbill number, duckbill bottom height, and duckbill bottom width. The optimized best structural parameters were: 9 duckbills, bottom height of 351 mm, and bottom width of 22 mm, ensuring film hole length control within the range of 25–40 mm, meeting planting requirements, preventing weed growth, and ensuring a seed growth environment. Furrow testing validated the adaptability and planting performance of the mechanism under different spacing conditions, providing a theoretical basis and practical reference for the promotion of small-scale breeding and the sowing technology on the film for field seed production. Full article

Essential oils are increasingly recognized as promising agents for sustainable weed control due to their selectivity and complex modes of action. This study evaluated the effects of Acorus calamus essential oil (SEO) on mitosis in two Fabaceae species (Vicia faba, Lupinus luteus) and two Brassicaceae species (Brassica napus, Arabidopsis thaliana) treated with species-specific IC₅₀ concentrations (0.03%, 0.025%, 0.01%, and 0.005%, respectively). Previous research showed that SEO induces oxidative stress and S-phase delay via genome instability. Here, SEO consistently disrupted mitosis across all species, reducing mitotic index by 50–60%, decreasing Cdc2 (CDKA homolog) levels, and causing chromosomal aberrations, including uneven chromatin condensation, sticky chromosomes, bridges, and micronuclei. Cells accumulated in metaphase and exhibited abnormal karyokinetic and cytokinetic spindles. Immunolabeling revealed thick, tightly packed microtubules and actin filaments, indicating excessive stabilization and impaired reorganization. Epigenetic regulation was also affected: H3T3 phosphorylation was abnormally strong, widely distributed, and persistent into anaphase/telophase, while H3S10Ph intensity was weakened. These results suggest that SEO targets multiple components of mitotic machinery and epigenetic control, regardless of species. The observed selectivity depends on dosage, not mechanism. This multi-targeted action may limit the development of plant resistance, supporting the potential of SEO as a bioherbicide in sustainable agriculture. 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

Turfgrass provides significant functional, environmental, recreational and aesthetic benefits; however, its high management inputs raise sustainability concerns due to intensive irrigation, fertilization and mowing. The aim of this study is to evaluate whether adopting a new mowing technology can support or enhance current low-input strategies in turfgrass management, such as reducing synthetic fertilization and deficit irrigation. This study was conducted from September 2023 to October 2024 at the Centre for Research on Turfgrass for Environment and Sports (CeRTES) in Pisa, Italy. Two turf compositions, pure tall fescue and tall fescue–microclover mixture, were managed using an autonomous mower operating daily at three mowing heights, 20, 40 and 60 mm. Turf quality, color, the NDVI, weed cover, leaf morphology, and clover presence were assessed throughout the growing season, including a drought and recovery period. The experimental design consisted of a two-factor split-plot randomized complete block design with four replications, and the statistical approach used was two-way and one-way ANOVAs with Fisher’s LSD at p = 0.05. The results of the study indicated that, under conditions where an autonomous mower was set to operate on a daily basis, the selected mowing height had minimal influence on drought response or recovery when water availability was a limiting factor. Furthermore, when subjected to the lowest mowing heights, the legume species included in the turfgrass mix demonstrated strong resilience, maintaining its presence and performance. In addition, when mowing with a high mowing frequency and at low mowing heights, the overall quality of the turfgrass appeared enhanced. These results serve as an important starting point for considering autonomous mowing technology as an innovative strategy in advancing toward turf management systems that prioritize sustainability and efficient use of resources. Full article

Development of new sustainable pesticides represents a real challenge for researchers due to environmental issues and public health aspects. In fact, the overuse of chemical pesticides has led to environmental damage, loss of biodiversity, and pesticide-resistant pests. In a framework characterized by the necessity of new sustainable agricultural practices, this study investigates the plant Genista ulicina as a producer of bioactive compounds for potential application as eco-friendly biopesticides. First, both roots and aerial parts of G. ulicina were extracted and the main compounds in the crude extracts were identified via GC-MS. Subsequently, the crude extracts were submitted to antifungal and phytotoxic assays. In particular, the antifungal effects were evaluated on three common phytopathogenic fungi, Fusarium oxysporum, Alternaria alternata, and Botrytis cinerea, while phytotoxic activity was evaluated on two weed species: Euphorbia peplus L. and Oxalis corniculata L. Further insights were obtained on the herbicidal potential of phytochemical compounds produced by G. ulicina through in silico investigations. In particular, molecular docking analyses were performed against three key enzymes involved in essential plant metabolic pathways: acetohydroxyacid synthase (AHAS), 4-hydroxyphenylpyruvate dioxygenase (HPPD), and protoporphyrinogen oxidase (PPO). Among the compounds identified, linolelaidic acid methyl ester, 1-monolinolein, stearic acid, and palmitic acid derivatives showed promising binding affinities and favorable interaction patterns compared to reference ligands. Selected phytochemicals from G. ulicina show potential as inhibitors of key herbicide targets, suggesting their value as promising leads in the development of sustainable bio-based weed control agents. Full article

Growing interest in organic food, along with European regulations limiting chemical usage, and the declining effectiveness of herbicides due to weed resistance, are all contributing to the growing trend towards mechanical weeding. For mechanical weeding to be effective, tools must pass near the crops in both the inter- and intra-row areas. The use of AI-based computer vision can assist in detecting crop lines and accurately guiding weeding tools. Additionally, AI-driven image analysis can be used for selective intra-row weeding with mechanized blades, distinguishing crops from weeds. However, until now, there have been two separate systems for these tasks. To enable simultaneous in-row weeding and row alignment, YOLOv8n and YOLO11n were trained and compared in a lettuce field (Lactuca sativa L.). The models were evaluated based on different metrics and inference time for three different image sizes. Crop lines were generated through linear regression on the bounding box centers of detected plants and compared against manually drawn ground truth lines, generated during the annotation process, using different deviation metrics. As more than one line appeared per image, the proposed methodology for classifying points in their corresponding crop line was tested for three different approaches with different empirical factor values. The best-performing approach achieved a mean horizontal error of 45 pixels, demonstrating the feasibility of a dual-functioning system using a single vision model. Full article

Weeds are one of the main problems in cultivation of medicinal and aromatic plants (MAPs); they negatively affect yield (herba and essential oil), and the overall quantity and quality of biomass, flowers, roots, seeds, and secondary metabolites. This review evaluates mulching as a sustainable, non-chemical method for weed management in the cultivation of MAPs and examines how effectively organic, synthetic, and living mulches reduce weeds and increase yields. Regarding different mulch materials such as straw, sawdust, bark, needles, compost, polyethylene, and biodegradable films, the basic processes of mulch activity, including light interception, physical suppression, and microclimate adjustment, are examined. The review further analyzes the impact of mulching on soil parameters (moisture, temperature, pH, chlorophyll content) and the biosynthesis of secondary metabolites. The findings consistently indicate that mulching substantially reduces weed biomass, improves crop performance, and supports organic farming practices. However, there are still issues with cost, material availability, and possible soil changes, and the efficacy is affected by variables including cultivated plant species, mulch type, and application thickness. The review highlights the importance of further research to optimize the selection of mulch and MAPs and their application across various agroecological conditions, and indicates that mulching is a potential, environmentally friendly technique for weed control in MAP cultivations. Full article

Weed management remains a critical challenge in the U.S. container ornamental production industry, where weeds not only compete with crops for limited resources but also harbor pests and pathogens, thereby diminishing plant quality and marketability. The paper explores the economic impact of weed infestations, herbicide resistance development, and the limited availability of selective herbicides for ornamental crops in the United States. This review synthesizes current chemical weed control tactics, focusing not only on both preemergence and postemergence herbicides commonly used in ornamental nurseries, but also organic alternatives and integrated weed management (IWM) approaches as complementary strategies by evaluating their effectiveness, crop safety, and usage. There is a critical need for research in the areas of alternative chemical options such as insecticides, miticides (e.g., Zerotol and Tetra Curb Max), and organic products for liverwort control in greenhouses. Although essential oils and plant-based extracts show some potential, their effectiveness and practical use remain largely unexplored. Full article

The objective of this study was to evaluate the efficacy of selected herbicides permitted for use in sustainable agriculture, specifically targeting spring rye and spring barley in a no-till farming system. The application of chemical herbicide protection in the cultivation of spring rye and barley significantly increased the yield and improved the quality parameters of the harvested grain, with the most pronounced effect observed in spring barley. The effectiveness of the herbicide treatment in reducing the number of weeds was 99.4% for spring rye and 82.39% for spring barley. The study demonstrated that the application of chemical herbicide protection had a positive impact on the quality parameters of spring barley grain. Both the thousand-grain weight and protein content were significantly higher in the grain collected from protected plots compared to the control plots. By utilizing herbicides permitted for use in integrated production (IP) in a sustainable manner, we protect the environment while minimizing the impact on crop yields and maintaining the quality of the harvested produce. Full article

The primary aim of this study was to explore the influence of abiotic factors on weed development in maize fields, with the goal of informing more effective weed management practices. We focused on identifying key environmental, edaphic, and agricultural variables that contribute to weed infestations, particularly before the application of spring herbicide treatments. Field investigations were conducted from 2018 to 2021 across selected maize-growing regions in Hungary. Over the four-year period, a total of 51 weed species were recorded, with Echinochloa crus-galli, Chenopodium album, Portulaca oleracea, and Hibiscus trionum emerging as the most prevalent taxa. Collectively, these four species accounted for more than half (52%) of the total weed cover. Altogether, the 20 most dominant species contributed 95% of the overall weed coverage. The analysis revealed that weed cover, species richness, and weed diversity were significantly affected by soil properties, nutrient levels, geographic location, and tillage systems. The results confirm that the composition of weed species was influenced by several environmental and management-related factors, including soil parameters, geographical location, annual precipitation, tillage method, and fertilizer application. Environmental factors collectively explained a slightly higher proportion of the variance (13.37%) than farming factors (12.66%) at a 90% significance level. Seasonal dynamics and crop rotation history also played a notable role in species distribution. Nutrient inputs, particularly nitrogen, phosphorus, and potassium, influenced both species diversity and floristic composition. Deep tillage practices favored the proliferation of perennial species, whereas shallow cultivation tended to promote annual weeds. Overall, the composition of weed vegetation proved to be a valuable indicator of site-specific soil conditions and agricultural practices. These findings underscore the need to tailor weed management strategies to local environmental and soil contexts for sustainable crop production. Full article

This study aimed to evaluate the forage yield, quality, and weed suppression potential of narbon vetch (Vicia narbonensis L.) and Italian ryegrass (Lolium multiflorum L.) grown as sole crops and in mixtures under organic farming conditions in Bilecik, Turkey, during the 2020–2021 growing season. The experiment included 15 treatments comprising monocultures and mixed sowing at different ratios. Measurements included morphological traits, forage yield components (green herbage, hay, and crude protein), fiber content, botanical composition, and weed biomass. The results reveal significant differences among treatments in terms of growth parameters and forage performance. Monocultures of IFVN 567 and Bartigra showed the highest green and hay yields, while mixtures such as IFVN 567 + Trinova and IFVN 567 + Bartigra outperformed in terms of land equivalent ratio (LER) and protein yield, demonstrating a clear advantage in land use efficiency. Furthermore, these mixtures showed superior weed suppression compared to monocultures. Overall, the findings suggest that carefully selected vetch–ryegrass combinations can enhance forage productivity, nutritional quality, and weed management under organic systems. Full article

Sorghum halepense (L.) Pers. (common name Johnson grass) is a perennial invasive weed that causes great harm worldwide, and its allelopathy has been demonstrated in a series of experiments. The present study offers new insights into its organ-specific phytochemical profiles using state-of-the-art metabolomic technology and explores the effects of a methanol extract of S. halepense rhizomes (ShER) and its major bioactive compounds (p-hydroxybenzoic acid and chlorogenic acid) on three noxious weed species. The phytotoxic effects of ShER are reflected through the inhibition of seed germination and reduced seedling growth, which are accompanied by changes in the antioxidant system of seedlings. Phytotoxicity is species specific and concentration dependent, and it is more pronounced against Chenopodiastrum murale (L.) S. Fuentes, Uotila & Borsch and Datura stramonium L. than highly tolerant Amaranthus retroflexus L. Catalase (CAT) is most likely the major mediator in the removal of reactive oxygen species, which are generated during germination and early seedling growth of Ch. murale exposed to ShER. The results of the present study imply the high potential of ShER in the management of amaranthaceous and solanaceous weeds, such as Ch. murale and D. stramonium, respectively. The present study offers an environmentally friendly solution for the biological control of weeds belonging to the families Amaranthaceae and Solanaceae. Also, the results of this research highlight the possibility of effective management of S. halepense by using it as a feedstock for bioherbicide production. Full article

Salvia pratensis L. is a valuable medicinal plant rich in bioactive compounds, yet its allelopathic potential remains underexplored. This study evaluated allelopathic effects and total phenolic (TPC) and flavonoid (TFC) contents of water extracts from the dry aboveground biomass of S. pratensis. To assess their selectivity and potential application in sustainable weed management, extracts at five different concentrations were tested on the germination and early growth of lettuce, radish, tomato, and carrot. The results demonstrated that the phytotoxic effects of S. pratensis extracts were both concentration- and species-dependent. Higher extract concentrations significantly inhibited germination and seedling growth, while lower concentrations of extracts stimulated shoot elongation by up to 30% compared to the control. Phytochemical analysis revealed that S. pratensis extracts contain notable TPC and TFC contents, with their concentrations increasing consistently with the extract concentration. Correlation analysis showed that higher TPC and TFC contents were strongly negatively correlated with germination and seedling growth parameters. Radish exhibited the highest sensitivity to the extracts, while lettuce was the most tolerant. Further research under field conditions is needed to assess the efficacy, selectivity, and practical potential of S. pratensis extracts in sustainable crop production systems. Full article

Soybean production in Thailand faces significant challenges from malignant weed competition, potentially reducing yields by up to 37% and incurring annual economic losses of approximately USD 3.8 billion. Pre-emergence herbicides are critical for integrated weed management, but their efficacy varies depending on local conditions and soybean varieties. This study evaluates the performance of three pre-emergence herbicides, pendimethalin (1875 g a.i. ha⁻¹), s-metolachlor (900 g a.i. ha⁻¹), and flumioxazin (125 g a.i. ha⁻¹), on weed control efficiency (WCE), soybean growth, phytotoxicity, and yield in Northeast Thailand using a randomised complete block design with two varieties (CM60 and Morkhor60) across rainy (2023) and dry (2024/2025) seasons. Herbicide performance varied seasonally: s-metolachlor showed optimal rainy season results (61.54% weed control efficiency at 63 days after herbicide application (DAA), with a yield of 1036 kg ha⁻¹), while flumioxazin excelled in dry conditions (64.32% WCE, <4% phytotoxicity, and 1243 kg ha⁻¹ yield). Pendimethalin performed poorly under wet conditions but improved in drier weather. Among five dominant weed species, Cyperus rotundus proved the most resilient. CM60 demonstrated superior herbicide tolerance and yield stability, particularly under rainy conditions. These results emphasise that season-specific herbicide selection and variety matching are crucial for herbicide resistance management and effective weed control in Thailand’s rainfed soybean systems. Full article