Search Results (1,138)

Amaranthus is appointed as a common weed associated with crops. The research was designed to survey the Amaranth existence pattern throughout the Fayoum Depression, Egypt, accompanied with a community vegetation analysis. The study was extended to collect and analyze associated soil samples. The obtained results figured out the prevalence of dicot families, herb growth forms, therophyte followed by phanerophyte life forms, the Pantropical monoregional chorotype, and the Mediterranean and Sudano-Zambezian followed by the Irano-Turanian pluri-regional chorotype. Multilevel pattern analysis stated that Gossypium barbadense, Corchorus olitorius, Sorghum bicolor, Sesamum indicum, and Zea mays are indicator species most related to Amaranth occurrence and prediction. NMDS analysis denoting that the Ibshaway, Youssef Al Seddik, Itsa, and Fayoum districts are the most representative districts for Amaranth existence on the basis of edaphic resources. Itsa and Youssef Al Seddik, in addition to Itsa and Fayoum, resemble each other in species composition. High pH and CaCO₃ percentages were discriminatory in Ibshaway, Itsa, and Youssef Al Seddik. Ni was the cornerstone for districts partitioning in pruned trees. Finally, Amaranth was flourishing in both comfortable and harsh habitats with cultivated crops and orchards, as well as on the outskirts. The findings are considered to be valorized by decision makers in arable land management. Full article

The accuracy of classification and localization of plants on images obtained from the board of an unmanned aerial vehicle (UAV) is of great importance when implementing precision farming technologies. It allows for the effective application of variable rate technologies, which not only saves chemicals but also reduces the environmental load on cultivated fields. Machine learning algorithms are widely used for plant classification. Research on the application of the YOLO algorithm is conducted for simultaneous identification, localization, and classification of plants. However, the quality of the algorithm significantly depends on the training set. The aim of this study is not only the detection of a cultivated plant (soybean) but also weeds growing in the field. The dataset developed in the course of the research allows for solving this issue by detecting not only soybean but also seven weed species common in the fields of Kazakhstan. The article describes an approach to the preparation of a training set of images for soybean fields using preliminary thresholding and bound box (Bbox) segmentation of marked images, which allows for improving the quality of plant classification and localization. The conducted research and computational experiments determined that Bbox segmentation shows the best results. The quality of classification and localization with the application of Bbox segmentation significantly increased (f1 score increased from 0.64 to 0.959, mAP50 from 0.72 to 0.979); for a cultivated plant (soybean), the best classification results known to date were achieved with the application of YOLOv8x on images obtained from the UAV, with an f1 score = 0.984. At the same time, the plant detection rate increased by 13 times compared to the model proposed earlier in the literature. Full article

Similarly to conventional field crops, weeds often pose significant problems in the cultivation of medicinal plants. To date, no comprehensive documentation exists regarding weed infestation levels in these crops in Serbia. The objective of this study was to provide a valuable foundation for developing effective, site-specific weed management strategies in medicinal crop production. Weeds in five medicinal crops (lemon balm, fennel, peppermint, ribwort plantain, German chamomile), were surveyed based on the agro-phytosociological method between 2019 and 2024, and across 59 plots. A total of 109 weed species were recorded, belonging to 29 families and 88 genera. Among them, 75 were annuals and 34 perennials, including 93 broadleaved species, 10 grasses, and one parasitic species. All surveyed plots were heavily infested with perennial weeds such as Elymus repens, Cirsium arvense, Convolvulus arvensis, Lepidium draba, Rumex crispus, Sorghum halepense, Taraxacum officinale, etc. Also, several annual species were found in high abundance and frequency, including Amaranthus retroflexus, Chenopodium album, Galium aparine, Lactuca serriola, Lamium amplexicaule, L. purpureum, Papaver rhoeas, Stellaria media, Veronica hederifolia, V. persica, etc. The most important ecological factors influencing the composition of weed vegetation in investigated medicinal crops were temperature and light for fennel and peppermint plots, soil reaction for lemon balm and ribwort plantain plots, and nutrient content for German chamomile plots. A perspective for exploitation of these results is the development of effective weed control programs tailored to this specific cropping system. Weed control strategies should consider such information, targeting the control of the most frequent, abundant, and dominant species existing in a crops or locality. Full article

The role of rhizosphere bacteria in facilitating plant invasion is increasingly acknowledged, yet the influence of specific microbial functional traits remains insufficiently understood. This study addresses this gap by isolating two bacterial strains, Bacillus sp. ScRB44 and Pseudomonas sp. ScRB22, from the rhizosphere of the invasive weed Solidago canadensis. We assessed their nitrogen utilization capacity and indoleacetic acid (IAA) production capabilities to evaluate their ecological functions. Our three-stage experimental design encompassed strain promotion, nutrient stress, and competition phases. Bacillus sp. ScRB44 demonstrated robust IAA production and significantly improved the nitrogen utilization efficiency, significantly enhancing S. canadensis growth, especially under nutrient-poor conditions, and promoting a shift in biomass allocation toward the roots, thereby conferring a competitive advantage over native species. Conversely, Pseudomonas sp. ScRB22 exhibited limited functional activity and a negligible impact on plant performance. These findings underscore that the ecological impact of rhizosphere bacteria on invasive weeds is closely linked to their specific growth-promoting functions. By enhancing stress adaptation and optimizing resource allocation, certain microorganisms may facilitate the establishment of invasive weeds in adverse environments. This study highlights the significance of microbial functional traits in invasion ecology and suggests novel approaches for microbiome-based invasive weed management, with potential applications in agricultural soil health improvement and ecological restoration. Full article

Field bindweed (Convolvulus arvensis L.) is a competitive herbaceous perennial weed that reduces productivity in irrigated pastures. Grazing might reduce competition by field bindweed when it begins growth in the spring, thereby encouraging encroachment by desirable grass species during the summer. To test this hypothesis, a two-year study was conducted in two adjacent, privately owned, irrigated, warm-season perennial grass pastures (replicates) that were heavily infested with field bindweed. Study sites were near Tucumcari, NM, USA. The fields were grazed with exclosures to evaluate ungrazed management. Aboveground biomass of field bindweed, other weeds, and perennial grass were measured, and field bindweed plants were counted in May of 2018 and 2019. There was no difference between years for any variable. Other weed biomass and field bindweed biomass and plant numbers were reduced (p < 0.05) by grazing (61.68 vs. 41.67 g bindweed biomass m⁻² for ungrazed and grazed management, respectively, and 108.5 and 56.8 bindweed plants m⁻² for ungrazed and grazed management, respectively). Otherwise, perennial grass production was unaffected by either year or management. These results indicate that grazing can be an effective tool to reduce field bindweed competition in warm-season perennial grass pastures. Full article

Weed infestation contributes significantly to global agricultural yield loss and increases the reliance on herbicides, raising both economic and environmental concerns. Effective weed detection in agriculture requires high accuracy and architectural efficiency. This is particularly important under challenging field conditions, including densely clustered targets, small weed instances, and low visual contrast between vegetation and soil. In this study, we propose GTDR-YOLOv12, an improved object detection framework based on YOLOv12, tailored for real-time weed identification in complex agricultural environments. The model is evaluated on the publicly available Weeds Detection dataset, which contains a wide range of weed species and challenging visual scenarios. To achieve better accuracy and efficiency, GTDR-YOLOv12 introduces several targeted structural enhancements. The backbone incorporates GDR-Conv, which integrates Ghost convolution and Dynamic ReLU (DyReLU) to improve early-stage feature representation while reducing redundancy. The GTDR-C3 module combines GDR-Conv with Task-Dependent Attention Mechanisms (TDAMs), allowing the network to adaptively refine spatial features critical for accurate weed identification and localization. In addition, the Lookahead optimizer is employed during training to improve convergence efficiency and reduce computational overhead, thereby contributing to the model’s lightweight design. GTDR-YOLOv12 outperforms several representative detectors, including YOLOv7, YOLOv9, YOLOv10, YOLOv11, YOLOv12, ATSS, RTMDet and Double-Head. Compared with YOLOv12, GTDR-YOLOv12 achieves notable improvements across multiple evaluation metrics. Precision increases from 85.0% to 88.0%, recall from 79.7% to 83.9%, and F1-score from 82.3% to 85.9%. In terms of detection accuracy, mAP:0.5 improves from 87.0% to 90.0%, while mAP:0.5:0.95 rises from 58.0% to 63.8%. Furthermore, the model reduces computational complexity. GFLOPs drop from 5.8 to 4.8, and the number of parameters is reduced from 2.51 M to 2.23 M. These reductions reflect a more efficient network design that not only lowers model complexity but also enhances detection performance. With a throughput of 58 FPS on the NVIDIA Jetson AGX Xavier, GTDR-YOLOv12 proves both resource-efficient and deployable for practical, real-time weeding tasks in agricultural settings. Full article

Within the framework of organic acid alternatives to chemical herbicides, pre-emergence weed control research is scarce. Citric acid (CA) and lactic acid (LA), considered significantly less effective than pelargonic acid (PA) and acetic acid (AA) from post-emergence (foliar spraying) studies, have largely been disregarded. This in vitro study was aimed at comparing the effects of 5–20% AA, AA + essential oils, PA, CA, and LA on radicle emergence inhibition (direct spraying of seeds) and shoot emergence inhibition (application to peat) on both weeds (perennial ryegrass, green foxtail, common vetch and chicory) and crops (soft wheat, alfalfa and millet). All tested compounds demonstrated concentration-dependent and species-specific effects on shoot emergence inhibition, with CA and LA (IC₅₀ range: 3.4–19.3%) showing a comparable efficacy to PA and AA (IC₅₀ range: 3.1–35.9%). The results also showed that CA and, to a lesser extent, LA were less inhibitory to soft wheat (CA IC₅₀ = 62.5%; LA IC₅₀ = 35.9%) and alfalfa (CA IC₅₀ = 57.8%; LA IC₅₀ = 44.1%) shoot emergence. CA and LA show potential promise for pre-emergence weed control in field testing, either on a stale seedbed in pre-crop sowing or concurrently with soft wheat and alfalfa sowing. Investigating organic compound herbicidal effects on crops of interest warrants attention. Full article

Dodders (Cuscuta spp.; Convolvulaceae) are parasitic weeds that pose major challenges to agriculture due to their ability to infect a wide range of host plants, extract nutrients, and transmit pathogens. Their control is especially challenging because of the seed longevity, resistance to herbicides, and the capacity for vegetative regeneration. Mechanical methods such as hand-pulling or mowing are labour-intensive and often ineffective for large infestations. Chemical control is limited, as systemic herbicides often affect the host species equally, or even worse than the parasite. Current research is exploring biological control methods, including allelopathic compounds, host-specific fungal pathogens, and epiparasitic insects, though these methods remain largely experimental. An integrated approach that combines prevention, targeted mechanical removal, and biological methods offers the most promising path for long-term management. Continued research is essential to develop effective, sustainable control strategies while exploring possible beneficial uses of these complex parasitic plants. The present review aims to thoroughly summarise the existing literature, emphasising the most recent advances and discussing future perspectives. Full article

Weeds represent increasingly troublesome threats to modern wheat production. Jiangsu Province, China, is one of the largest wheat-planting areas, characterized by a high level of agricultural mechanization, in the country. In 2024, we surveyed weed communities of 924 wheat lands from 308 sites in Jiangsu and compared them with historical data surveyed in 1999–2000 in this province. A total of 156 weed species belonging to 103 genera and 39 families were recorded. Compositae and Poaceae showed the highest species richness, with 26 and 23 species, respectively. Poaceae weeds accounted for 54.3% of the overall weeds in dominance values. Beckmannia syzigachne showed the highest proportion of the overall weeds in dominance values (19.2%). Compared with the historical data, weed diversity increased by 33.3% in species, and by 62.5% in families; grassy weeds such as Beckmannia syzigachne, Alopecurus japonicus, and Alopecurus myosuroides became more dominant, while several low-growing grassy weeds became less dominant. The dominance of broadleaf weeds, such as Galium spp., Vicia spp., and Veronica spp., decreased greatly, and a clear trend of weed homogenization among different areas and types of wheat lands was observed. This is the first investigation of weed community succession against the background of agricultural modernization in China. 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

Asia minor bluegrass (Polypogon fugax), a widespread Poaceae weed, exhibits broad tolerance to abiotic stresses. Validated reference genes (RGs) for reliable RT-qPCR normalization in this ecologically and agriculturally significant species remain unidentified. This study identified eight candidate RGs using transcriptome data from seedling tissues. We assessed the expression stability of these eight RGs across various abiotic stresses and developmental stages using Delta Ct, BestKeeper, geNorm, and NormFinder algorithms. A comprehensive stability ranking was generated using RefFinder, with validation performed using the target genes COR413 and P5CS. Results identified EIF4A and TUB as the optimal RG combination for normalizing gene expression during heat stress, cold stress, and growth stages. EIF4A and ACT were most stable under drought stress, EIF4A and 28S under salt stress, and EIF4A and EF-1 under cadmium (Cd) stress. Furthermore, EIF4A and UBQ demonstrated optimal stability under herbicide stress. Additionally, application of validated RGs revealed higher acetyl-CoA carboxylase gene (ACCase) expression in one herbicide-resistant population, suggesting target-site gene overexpression contributes to resistance. This work presents the first systematic evaluation of RGs in P. fugax. The identified stable RGs provide essential tools for future gene expression studies on growth and abiotic stress responses in this species, facilitating deeper insights into the molecular basis of its weediness and adaptability. Full article

Glyphosate has been used for roadside weed control in southern Spain for over 40 years, and most populations of goldentop (Lamarckia aurea L.) Moench have putatively developed resistance to this active ingredient. The physiological and biochemical basis for glyphosate resistance in this weed has been investigated. Dose–response studies indicated that the resistant biotype (R) was almost 13 times more resistant to glyphosate compared to a known susceptible biotype (S). Studies of foliar glyphosate retention and ¹⁴C-glyphosate uptake/translocation showed no significant differences between both L. aurea biotypes. Basal 5-enolpyruvylshikimate-3-phosphate synthase (EPSPS) activity (µmol µg⁻¹TSP min⁻¹) showed similar values between R (0.82 ± 0.04) and S (0.75 ± 0.05) biotypes. On the other hand, the resistance factor (I₅₀R/I₅₀S) did not show a difference between the two biotypes. Therefore, it was concluded that target-site (TSR) resistance mechanisms are not involved in glyphosate resistance in this weed species. The metabolism of glyphosate to form the non-toxic metabolites aminomethylphosphonic acid (AMPA), glyoxylate, and sarcosine was greater and faster in the R compared to the S biotype; thus, glyphosate resistance is due to non-target-site resistance (NTSR) mechanisms. This paper is the first report of glyphosate resistance in L. aurea in the world. Full article

False cleavers (Galium spurium L.) is a broadleaf weed species that affects wheat productivity because of its strong competition for resources. It has developed resistance to acetolactate synthase (ALS) inhibitors, such as sulfonylureas and triazolopyrimidines, which are herbicides widely used in durum wheat. Integrated weed management programs can contribute to the control of this species and delay the evolution of herbicide resistance. Thus, a two-year field experiment was conducted to evaluate the effects of sowing time, variety, and herbicides on crop yield, density, and dry weight of a false cleavers population with resistance to ALS inhibitors. In both growing seasons, a split-split-plot design was used with three replicates. The sowing date was chosen as the main plot factor, durum wheat varieties as the subplot factor, and herbicides as the sub-subplot factor. The herbicide treatments were: (1) metsulfuron-methyl/bensulfuron-methyl (4/50 g a.i. ha⁻¹), (2) aminopyralid/florasulam (9.9/4.95 g a.i. ha⁻¹), (3) pyroxsulam and florasulam/2,4-D (18.75 + 4.725/225 g a.i. ha⁻¹), (4) 2,4-D/bromoxynil (633.15/601.2 g a.i. ha⁻¹), non-treated control, and hand-weeded control for the first season, while in the second season one more herbicide treatment (halauxifen-methyl/florasulam, 5.6/5.15 g a.i. ha⁻¹) was added. Herbicide application was performed on 10 March 2021 and 28 March 2022, when the crop was at the end of tillering and the beginning of stem elongation. The results showed that the density of false cleavers was not affected by the variety or sowing time. However, its dry weight was 17.3–23.4% higher in early sowing (16 November in 2020 and 8 November 2021) than in late sowing (24 December 2020 and 2 December 2021). Among the herbicides tested, 2,4-D/bromoxynil and halauxifen-methyl/florasulam effectively controlled false cleavers, showing greater efficacy in late sowing (>88%), which ultimately led to a higher yield. In conclusion, our two-year findings demonstrate that delayed sowing as part of an integrated weed management strategy can contribute to controlling resistant populations of false cleavers to ALS-inhibiting herbicides without affecting the quantity and quality of durum wheat yield in areas with a Mediterranean climate. Full article

Common ragweed, Ambrosia artemisiifolia (Asteraceae), is an invasive weed that causes problems in cropping systems and to human health both in its native range in North and Central America and the introduced range in Europe, Asia, Africa, and Australia. Ophraella communa, an herbivorous chrysomelid beetle from North America, was accidentally introduced into East Asia and Europe, where it significantly reduces weed populations and pollen production. Despite extensive research on its host specificity and risk assessment, the potential environmental risk of this biological control agent in southeastern Central Europe, one of the most heavily invaded areas by A. artemisiifolia, remains to be determined. This literature review attempts to summarize the results of host-range testing conducted so far and identifies plant taxa native to southeastern Central Europe that have not been tested yet. The results suggest that the host range of O. communa is not yet entirely clear, but may include some plant species from the tribes Heliantheae, Inuleae, Anthemideae, Cardueae, Astereae, and/or Coreopsideae. So far, only some of the 21 genera from those tribes with species in southeastern Central Europe have been tested. We therefore suggest further host specificity studies with representatives of these plant genera to fully assess the potential non-target risks by O. communa in agricultural and natural habitats. Full article

Common ragweed (Ambrosia artemisiifolia L.) has been identified as one of the most harmful invasive weed species in Europe due to its allergenic pollen and competitive growth in diverse habitats. In the first part of this review [Common Ragweed—Ambrosia artemisiifolia L.: A Review with Special Regards to the Latest Results in Biology and Ecology], its biological characteristics and ecological behavior were described in detail. In the current paper, control strategies are summarized, focusing on integrated weed management adapted to the specific habitat where the species causes damage—arable land, semi-natural vegetation, urban areas, or along linear infrastructures. A range of management methods is reviewed, including agrotechnical, mechanical, physical, thermal, biological, and chemical approaches. Particular attention is given to the spread of herbicide resistance and the need for diversified, habitat-specific interventions. Among biological control options, the potential of Ophraella communa LeSage, a leaf beetle native to North America, is highlighted. Furthermore, innovative technologies such as UAV-assisted weed mapping, site-specific herbicide application, and autonomous weeding robots are discussed as environmentally sustainable tools. The role of legal regulations and pollen monitoring networks—particularly those implemented in Hungary—is also emphasized. By combining traditional and advanced methods within a coordinated framework, effective and ecologically sound ragweed control can be achieved. Full article