Search Results (1,784)

Weeds pose a significant threat to the production of the medicinal crop Ophiopogon japonicus. Due to the scarcity of registered herbicides for this crop, farmers heavily rely on manual weeding. This study evaluated a novel acetochlor nanocapsule formulation for weed control in Sichuan O. japonicus fields, comparing it to a conventional acetochlor emulsifiable concentrate (EC). Treatments included manual weeding (weed-free control), conventional EC (900 g a.i. ha⁻¹), and three nanocapsule doses (450, 900, and 1800 g a.i. ha⁻¹). Weed control efficacy was assessed at 15, 30, 45, and 60 days after application, followed by the measurement of agronomic traits, yield, and the content of bioactive compounds (saponins, flavonoids, and polysaccharides) post-harvest. The high-dose nanocapsules (1800 g a.i. ha⁻¹) provided excellent weed control (96.54% at 45 days), which was better than the EC and lower nanocapsule doses, and extended the control duration. It did not negatively affect key agronomic traits, root tuber morphology, final yield, nor the content of key bioactive compounds compared to the weed-free control. In conclusion, acetochlor nanocapsules, especially at 1800 g a.i. ha⁻¹, offer an effective and safe weed management strategy for O. japonicus. They provide superior, prolonged weed control without harming crop yield or quality. Full article

Cover crop management in vineyards under a semiarid Mediterranean environment needs strategies that enhance soil C and N status and microbial functioning without increasing disturbance. This study compared cover crops biomass incorporation (harrowing, HR; rotary tillage; RT) and non-incorporation (NI, residues left on the topsoil) into the soil in a 12-year Grecanico dorato vineyard. Traditional vineyard soil management (continuously tilled for weeds control) was also used as a control. Soil samples from 0 to 20 and 20 to 40 cm were analyzed for total organic carbon (TOC), total nitrogen (TN), microbial biomass carbon (MBC) and nitrogen (MBN), and enzyme activities. NI and HR raised TOC and TN in the topsoil versus TR, with NI frequently maintaining advantages at depth. NI also maximized MBC/MBN and reduced the metabolic quotient (qCO₂), indicating improved microbial C-use efficiency; RT showed intermediate chemistry but depressed subsoil MBC and altered MBC/MBN. Enzyme profiles reflected contrasting mechanisms: RT boosted β-glucosidase in the topsoil, TR peaked for urease and arylsulfatase but alongside lower biomass and higher specific enzyme activities, while NI supported greater overall functioning via larger biomass and lower per-C enzyme demand. The calculated geometric mean enzyme (GMea) index emphasized transient TR flush versus steadier conservation functioning. Strong vertical stratification occurred for all indices, yet NI transmitted some benefits to 20–40 cm. We conclude that residue retention or moderate incorporation promotes larger, more efficient microbial population and more balanced nutrient cycling, whereas repeated rotary tillage risks subsoil inefficiencies. In semi-arid Mediterranean vineyards, low-disturbance cover-crop incorporation (HR) or, preferably, residue retention at the topsoil (NI) offer a simple, scalable route to sustain soil quality and long-term fertility. Full article

Trials were carried out to investigate the effects of light and temperature on C. rotundus seeds and tubers under two conditions: (i) in vitro and (ii) after sowing in soil. In the latter, seedling emergence was evaluated after sowing at increasing depths in different soil textures. While dormancy was evident in over 50% of the seeds, which also required light for germination, in contrast, tubers showed a significantly shorter period of dormancy that was independent of light. Seed burial strongly hindered seedling emergence, showing an “active” seed bank only in the shallowest soil layer (few mm). In contrast, tubers showed a marked ability to emerge from a depth exceeding 40 cm. Emergence capacity was found to be proportional to the size of the tubers, attributable to the greater energy reserves needed during autotrophic pre-emergence growth. Seedling emergence from both seeds and tubers, sown at increasing depths, was inhibited to a greater extent in a clay soil texture. A lower inhibitory effect was reported for sandy soils. Tuber vitality was significantly reduced or eliminated within a few days from progressive drying following exposure to solar rays during summer periods. Finally, the data were discussed within the context of planning the agronomic management of C. rotundus, in terms of soil tillage modalities, to ensure sustainable control of this strongly invasive and persistent weed. Full article

Argemone mexicana L. is considered a weed; however, it contains secondary metabolites that can control phytopathogenic fungi in vitro, with the potential to adapt its effectiveness in the field. In the present study, leaf extracts of A. mexicana (hexane and methanol) were prepared, and their chemical profiles were analyzed using gas chromatography–mass spectrometry (GC-MS). The in vitro antifungal activity of each extract was evaluated at different concentrations (500, 1000, 2000, 4000, and 8000 mg L⁻¹) against phytopathogens such as Monilinia fructicola, Colletotrichum gloeosporioides, Fusarium oxysporum, and Sclerotinia sclerotiorum. Based on their chemical profiles, 14 compounds were identified in the hexanic extract, and 11 compounds were identified in the methanolic extract. These compounds included those with antifungal activity, such as Benzene; 1.3-bis(1.1-dimethylethyl)-; pentanoic acid; 5-hydroxy-, 2,4-di-1-butylphenyl esters; 1,2,4-Triazol-4-amine; and N-(2-thienylmethyl). The hexanic extract demonstrated fungistatic activity on the four fungi tested, while the methanolic extract exhibited fungicidal activity against C. gloeosporioides and F. oxysporum. The results of the Probit analysis showed variations in the sensitivity of phytopathogenic fungi to the treatments evaluated. In M. fructicola, the hexane extract presented an EC₅₀ of 317,146 mg L⁻¹ and an EC₉₀ of 400,796 mg L⁻¹. For C. gloeosporioides, the EC₅₀ was 2676 mg L⁻¹ and the EC₉₀ was 888,177 mg L⁻¹, while in F. oxysporum an EC₅₀ of 34,274 mg L⁻¹ and an EC₉₀ of 1528 mg L⁻¹ were estimated. In the case of S. sclerotiorum, an EC₅₀ of 560 mg L⁻¹ and an EC₉₀ of 7776 mg L⁻¹ were obtained. Finally, for the commercial fungicide Captan^®, an EC₅₀ of 1.19 mg L⁻¹ and an EC₉₀ of 1.67 mg L⁻¹. These results suggest that extracts from A. mexicana could provide a natural alternative for the control of phytopathogenic fungi. Full article

The increasing demand for sustainable agricultural practices has led researchers to explore alternative methods for controlling plant diseases and pests. Among these alternatives, essential oils (EOs) derived from various plant species have gained significant attention due to their broad-spectrum antimicrobial properties, which can be utilized in plant protection. Essential oils are volatile compounds that possess strong aromatic characteristics and are found in many medicinal and aromatic plants. They are known for their antifungal, antibacterial, and insecticidal activities, making them viable candidates for eco-friendly pest and disease management strategies. In this research, six essential oils—pine, patchouli, geranium, spruce, coriander, and eucalyptus oil—have been tested in vitro for controlling mycelium growth of Sclerotinia sclerotiorum, Botrytis cinerea, Alternaria brassicicola, and Cylindrosporium concentricum. The study also covers experiments in controlling pollen beetle and cabbage seed weevil (laboratory trials). In greenhouse conditions, the phytotoxicity of EOs to oilseed rape (Brassica napus L.) and the effect of these substances on the control of cornflower (Centaurea cyanus) were also tested. The results obtained indicate a large diversity of different essential oils in terms of their action on pathogens, pests, weeds, and winter rapeseed. Differences in their effectiveness were also found, depending on the applied dose. Full article

Vision navigation systems provide significant advantages in agricultural scenarios such as pesticide spraying, weeding, and harvesting by interpreting crop row structures in real-time to establish guidance lines. However, the delay introduced by image processing causes the path and pose information relied upon by the controller to lag behind the actual vehicle state. In this study, a hierarchical delay-compensated cooperative control framework (HDC-CC) was designed to synergize Model Predictive Control (MPC) and Sliding Mode Control (SMC), combining predictive optimization with robust stability enforcement for agricultural navigation. An upper-layer MPC module incorporated a novel delay state observer that compensated for visual latency by forward-predicting vehicle states using a 3-DoF dynamics model, generating optimized front-wheel steering angles under actuator constraints. Concurrently, a lower-layer SMC module ensured dynamic stability by computing additional yaw moments via adaptive sliding surfaces, with torque distribution optimized through quadratic programming. Under varying adhesion conditions tests demonstrated error reductions of 74.72% on high-adhesion road and 56.19% on low-adhesion surfaces. In Gazebo simulations of unstructured farmland environments, the proposed framework achieved an average path tracking error of only 0.091 m. The approach effectively overcame vision-controller mismatches through predictive compensation and hierarchical coordination, providing a robust solution for vision autonomous agricultural machinery navigation in various row-crop operations. Full article

Echinochloa crus-galli and E. crus-galli var. mitis are two of the most troublesome rice weeds. Florpyrauxifen-benzyl is one of the most important post-emergence rice herbicides that has been pervasively applied in many countries since 2018. We collected 70 E. crus-galli and 158 E. crus-galli var. mitis populations from rice fields in eastern China in 2022 and tested their sensitivities to florpyrauxifen-benzyl through whole-plant bioassays. A total of 21 days after treatment with florpyrauxifen-benzyl label dose (36 g ai ha⁻¹), 71.4% of E. crus-galli and 70.9% of E. crus-galli var. mitis populations were completely controlled. The GR₅₀ doses (doses causing 50% fresh weight reductions in aboveground parts) of florpyrauxifen-benzyl applied to E. crus-galli populations ranged from 1.4 to 36.9 g ai ha⁻¹, with a baseline sensitivity dose of 4.9 g ai ha⁻¹; those for E. crus-galli var. mitis populations ranged from 1.3 to 97.6 g ai ha⁻¹, with a baseline sensitivity dose of 5.0 g ai ha⁻¹. No significant differences between E. crus-galli and E. crus-galli var. mitis were found in GR₅₀ values. Among 70 E. crus-galli populations, 61.4%, 35.7%, and 2.9% showed no, low, and moderate resistance to florpyrauxifen-benzyl, while among 158 E. crus-galli var. mitis populations, 54.4%, 36.1%, 1.9%, and 1.9% showed no, low, moderate, and high resistance to florpyrauxifen-benzyl, respectively. Moreover, the frequency of florpyrauxifen-benzyl-resistant populations of E. crus-galli var. mitis tended to be higher in southwestern areas. Full article

The aim of this study was to evaluate the effectiveness of 2.45 GHz microwave application in inhibiting the germination of Portulaca oleracea seeds. Four different soil substrate types were used to establish whether their different properties and composition might influence the microwave heating and inhibition of the seed germination process. Our results show the efficacy of the treatments and suggest the fundamental importance of defining specific microwave treatment protocols to be applied to the affected soil substrate. In this study, we report complete inhibition of germination of P. oleracea seeds in four exposed soil substrates and propose that microwave application could be integrated into an agricultural management system to control a weed such as P. oleracea, which is widespread in many areas of the world. The microwave treatment may represent an ecological and innovative solution that contributes to reducing the dependence on chemical herbicides and promotes greater agricultural sustainability. Full article

Soybean (Glycine max (L.) Merr.) is an essential legume crop in Thailand, valued for its high protein content and economic significance. However, weed competition can reduce yields by up to 82% if not managed effectively. This study evaluates the efficacy of post-emergence herbicides for weed control and their impact on soybean yield. A field experiment was conducted during the 2023 rainy and 2024/2025 dry seasons at Khon Kaen University using a split-plot design with four replications. Weed management treatments included hand weeding, an untreated control, and three herbicides, fluazifop-P-butyl + fomesafen, clethodim + fomesafen, and quizalofop-P-tefuryl + fomesafen, applied to two soybean varieties (Morkhor60 and CM60). Quizalofop-P-tefuryl + fomesafen was found to be the most effective herbicide, achieving 87.66% weed control efficiency (WCE) in the dry season and 72.43% in the rainy season. Hand weeding produced the highest yield (1324.00 kg ha⁻¹), followed by quizalofop-P-tefuryl + fomesafen (1148.90 kg ha⁻¹). Morkhor60 outperformed CM60 in yield and growth performance. These findings highlight the importance of selecting suitable herbicide treatments to optimize weed control and enhance soybean productivity under different seasonal conditions. Full article

Weed infestation severely impairs foxtail millet growth, while new herbicide development faces long cycles and high costs. This study examined cyhalofop-butyl (effective against Echinochloa crus-galli (E. crus-galli) in paddy fields) to assess its effects on agronomic traits, antioxidant enzyme activities, malondialdehyde (MDA) content of Jingu 21, and weed control efficacy in foxtail millet fields, aiming to screen safe, effective concentrations. Results showed that sole cyhalofop-butyl inhibited foxtail millet growth: high-dose treatments retained significant agronomic trait inhibition 30 days post-spray. Early post-spray, superoxide dismutase (SOD) and peroxidase (POD) activities showed a “first increase then decrease” pattern, catalase (CAT) a “first decrease then increase” trend, and MDA content rose; index differences from the water control narrowed over time, though 90 g a.i./hm² still caused higher leaf SOD activity and MDA content in later stages. For weed control, cyhalofop-butyl effectively controlled E. crus-galli (control effect “first increase then decrease,” 90 g a.i./hm² optimal) and Digitaria sanguinalis (D. sanguinalis) (control effect rising over time) in foxtail millet fields. On the whole, 22.5 g a.i./hm² and 45 g a.i./hm² of cyhalofop-butyl are safe for Jingu 21, and 67.5 g a.i./hm² is also a safe concentration, so 45–67.5 g a.i./hm² can be preferred for comprehensive weed control. Full article

Agricultural management in Europe faces increasing pressure to reduce its environmental footprint. Implementing precision agriculture for weed management could offer a solution and minimize the use of chemical products. High spatial resolution imagery from real time kinematic (RTK) unmanned aerial vehicles (UAV) in combination with supervised convolutional neural network (CNNs) models have proven successful in making location specific treatments. This site-specific advice limits the amount of herbicide applied to the field to areas that require action, thereby reducing the environmental impact and inputs for the farmer. To develop performant CNN models, there is a need for sufficient high-quality labelled data. To reduce the labelling effort and time, a new labelling method is proposed whereby image subsection pairs are labelled based on their relative differences in weed pressure to train a CNN ordinal regression model. The model is evaluated on detecting weed pressure in potato (Solanum tuberosum L.). Model performance was evaluated on different levels: pairwise accuracy, linearity (Pearson correlation coefficient), rank consistency (Spearman’s (r_s) and Kendal (τ) rank correlations coefficients) and binary accuracy. After hyperparameter tuning, a pairwise accuracy of 85.2%, significant linearity (r_s = 0.81) and significant rank consistency (r_s = 0.87 and τ = 0.69) were found. This suggests that the model is capable of correctly detecting the gradient in weed pressure for the dataset. A maximum binary accuracy and F1-score of 92% and 88% were found for the dataset after thresholding the predicted weed scores into weed versus non-weed images. The model architecture allows us to visualize the intermediate features of the last convolutional block. This allows data analysts to better evaluate if the model “sees” the features of interest (in this case weeds). The results indicate the potential of ordinal regression with relative labels as a fast, lightweight model that predicts weed pressure gradients. Experts have the freedom to decide which threshold value(s) can be used on predicted weed scores depending on the weed, crop and treatment that they want to use for flexible weed control management. Full article

In resource-constrained edge agricultural environments, the accurate recognition of toxic weeds poses dual challenges related to model lightweight design and the few-shot generalization capability. To address these challenges, a multi-strategy recognition framework is proposed, which integrates a lightweight backbone network, a pseudo-labeling guidance mechanism, and a contrastive boundary enhancement module. This approach is designed to improve deployment efficiency on low-power devices while ensuring high accuracy in identifying rare toxic weed categories. The proposed model achieves a real-time inference speed of 18.9 FPS on the Jetson Nano platform, with a compact model size of 18.6 MB and power consumption maintained below 5.1 W, demonstrating its efficiency for edge deployment. In standard classification tasks, the model attains 89.64%, 87.91%, 88.76%, and 88.43% in terms of precision, recall, F1-score, and accuracy, respectively, outperforming existing mainstream lightweight models such as ResNet18, MobileNetV2, and MobileViT across all evaluation metrics. In few-shot classification tasks targeting rare toxic weed species, the complete model achieves an accuracy of 80.32%, marking an average improvement of over 13 percentage points compared to ablation variants that exclude pseudo-labeling and self-supervised modules or adopt a CNN-only architecture. The experimental results indicate that the proposed model not only delivers strong overall classification performance but also exhibits superior adaptability for deployment and robustness in low-data regimes, offering an effective solution for the precise identification and ecological control of toxic weeds within intelligent agricultural perception systems. Full article

The increasing implementation of drift-reduction regulations in agriculture has driven the widespread adoption of drift-reducing spray nozzles. However, concerns remain about their impact on the biological efficacy of foliar-applied herbicides, particularly at early weed growth stages. This study evaluated the bio-efficiency of various drift-reducing flat-fan nozzles across three weed species (Chenopodium album, Solanum nigrum, and Echinochloa crus-galli), two growth stages, and six herbicides differing in mode of action and formulation properties. Dose–response bioassays were conducted using eight nozzle–pressure combinations under controlled greenhouse conditions. Spray characteristics, including droplet size distribution, coverage, contact angle, and surface tension, were quantified to elucidate interactions affecting herbicide efficacy. The results showed that nozzle effects were more pronounced for high-surface-tension formulations and poorly wettable weed targets. Several coarser droplet drift-reducing nozzles (e.g., ID3, APTJ) showed inferior performance in controlling small C. album and S. nigrum targets with bentazon and erectophile E. crus-galli targets with cycloxydim. At the same time, nozzle choice was less critical for tembotrione and nicosulfuron spray solutions, which have low surface tension. Across weed species, growth stages, and herbicides, nozzles producing finer, slower droplets demonstrated superior and more consistent performance compared to those producing larger, faster droplets. These findings offer science-based guidance for selecting nozzle types that balance drift mitigation with effective weed control under current and future regulatory constraints. Full article

Microbial herbicides, recognized for their target specificity, environmental compatibility, and simple production processes, hold promising potential for sustainable agriculture. This study isolated a strain of Alternaria gaisen (designated GD-011) from infected Medicago sativa L. in Qinghai Province, China, and evaluated its herbicidal potential through systematic development and efficacy assessment. Using single-factor and orthogonal experimental designs, the optimal sporulation substrate was identified as wheat bran, and the fermentation medium was optimized to consist of 14.5 g wheat bran, 19.4 g wheat middlings, 1.5 g rapeseed cake, and 14.6 g corn flour. Based on colony diameter and OD₆₀₀ measurements, diatomite was selected as the most suitable carrier, while bentonite, humic acid, and polyvinyl alcohol were chosen as the stabilizer, protectant, and dispersant, respectively. Pot trials under controlled conditions demonstrated strong herbicidal activity of GD-011 against three common weed species: Chenopodium album L., Elsholtzia densa Benth., and Galium aparine L. The highest efficacy was observed against C. album, with disease incidence and fresh weight inhibition reaching 80.83% and 79.87%, respectively. Inhibition rates for both E. densa and G. asparine exceeded 60%. A wettable powder formulation developed from GD-011 showed particularly effective control of C. album and E. densa, providing a practical foundation for the application of GD-011 as a novel bioherbicide. Full article

Typical fertilizer applicators are often restricted in performance due to non-uniformity in distribution, required labor and time intensiveness, high discharge rate, chemical input wastage, and fostering weed proliferation. To address this gap in production agriculture, an automated variable-rate fertilizer applicator was developed for the cotton crop that is based on deep learning-initiated electronic control unit (ECU). The applicator comprises (a) plant recognition unit (PRU) to capture and predict presence (or absence) of cotton plants using the YOLOv7 recognition model deployed on-board Raspberry Pi microprocessor (Wale, UK), and relay decision to a microcontroller; (b) an ECU to control stepper motor of fertilizer metering unit as per received cotton-detection signal from the PRU; and (c) fertilizer metering unit that delivers precisely metered granular fertilizer to the targeted cotton plant when corresponding stepper motor is triggered by the microcontroller. The trials were conducted in the laboratory on a custom testbed using artificial cotton plants, with the camera positioned 0.21 m ahead of the discharge tube and 16 cm above the plants. The system was evaluated at forward speeds ranging from 0.2 to 1.0 km/h under lighting levels of 3000, 5000, and 7000 lux to simulate varying illumination conditions in the field. Precision, recall, F1-score, and mAP of the plant recognition model were determined as 1.00 at 0.669 confidence, 0.97 at 0.000 confidence, 0.87 at 0.151 confidence, and 0.906 at 0.5 confidence, respectively. The mean absolute percent error (MAPE) of 6.15% and 9.1%, and mean absolute deviation (MAD) of 0.81 g/plant and 1.20 g/plant, on application of urea and Diammonium Phosphate (DAP), were observed, respectively. The statistical analysis showed no significant effect of the forward speed of the conveying system on fertilizer application rate (p > 0.05), thereby offering a uniform application throughout, independent of the forward speed. The developed fertilizer applicator enhances precision in site-specific applications, minimizes fertilizer wastage, and reduces labor requirements. Eventually, this fertilizer applicator placed the fertilizer near targeted plants as per the recommended dosage. Full article