<?xml version="1.0" encoding="utf-8"?>
    <rss version="2.0">
      <channel xmlns:content="http://purl.org/rss/1.0/modules/content/">
        <title>Frontiers in Agronomy | Weed Management section | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/agronomy/sections/weed-management</link>
        <description>RSS Feed for Weed Management section in the Frontiers in Agronomy journal | New and Recent Articles</description>
        <language>en-us</language>
        <generator>Frontiers Feed Generator,version:1</generator>
        <pubDate>2026-05-14T17:11:47.474+00:00</pubDate>
        <ttl>60</ttl>
        <item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1706873</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1706873</link>
        <title><![CDATA[Enhancing weed detection in wheat with hybrid attention mechanism CBAM: a comparative study with deep learning approaches]]></title>
        <pubdate>2026-05-07T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author> Ritika</author><author>Savita Kumari Sheoran</author><author>Arjun Singh</author><author>Dilip Kumar</author>
        <description><![CDATA[IntroductionWeed infestation is a major constraint on wheat growing, yet traditional detection methods are hampered by the close visual similarity between weeds and crops under field conditions. Although convolutional neural networks (CNN) have a strong potential for automated weed detection, their efficacy remains limited by challenges in feature selection and computational demands. Existing attention-based approaches apply channel and spatial attention in sequence, creating inter-relationship dependencies that limit the quality of the representation of features. This study addresses this gap by proposing a parallel configuration of the CBAM (Convolution Block Attention Module) for the classification of wheat and weed.MethodsA dataset of 1 260 field images (784 wheat; 476 grass) was collected in the village of Berli Khurd in Rewari, Haryana, India, under different lighting conditions and supplemented to 6634 images to resolve the class imbalance and improve the overall coverage. Four widely accepted CNN architectures - ResNet-50, ResNet-152, VGG-16 and VGG-19 - and their variants enhanced by CBAM have been systematically assessed for the classification of wheat and weed. The proposed parallel CBAM configuration process will simultaneously focus both the channel and the spatial attention on the same input feature map, allowing independent and complementary refinement of the features. Models were trained for 30 epochs with AdamW optimization (learning rate = 0.0001) and a batch size of 16 at Google TPU (V2-8) runtime.ResultsCBAM integration significantly improved classification performance across all architectures. CBAM-ResNet-50 and CBAM-ResNet-152 both achieved near-perfect validation accuracy of 99.5%, compared to 89.2% and 98.0% for their baseline counterparts representing improvements of 10.3% and 1.5%, respectively. CBAM-ResNet-50 attained precision of 99.1%, recall of 98.5%, and an F1-score of 99.2%; CBAM-ResNet-152 achieved precision of 99.4%, recall of 98.6%, and an F1-score of 99.3%. VGG-16 and VGG-19 also improved substantially, from 87.0% to 97.3% and from 88.2% to 98.4%, respectively.ConclusionThe parallel configuration of the CBAM consistently improved the robustness of the extraction of features, reduced misclassification and improved coverage across all four CNN architectures. Attention-based gains were largest in the residual networks, indicating that skipping the link increases the benefits of parallel hybrid attention. These findings demonstrate the practical value of targeted residual networks for reliable and field-based weed identification in precision agriculture.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1831688</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1831688</link>
        <title><![CDATA[Bioherbicides and agroecology: challenges and opportunities for agroecological weed management]]></title>
        <pubdate>2026-05-04T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Milos Zaric</author><author>Vesna Dragičević</author><author>Milena Simić</author><author>Natalija Pavlović</author><author>Milan Brankov</author>
        <description><![CDATA[The limited availability of herbicides for weed management, coupled with the rapid expansion of herbicide-resistant weed populations, has intensified the need to explore alternative weed management strategies, particularly for producers transitioning to and/or operating in organic farming systems. The expansion of bioherbicides in the US market has opened new opportunities in weed control and new research avenues for weed management. Bioherbicides are natural substances with herbicidal activity, and are mostly non-selective and do not translocate within plants. They are directly connected with agroecological principles by serving as sustainable, nature-derived complementarily to synthetic herbicides aiming to control weeds while preserving biodiversity, soil health, and ecological balance. Their non-selective activity requires special attention because they may also affect crops, while targeted application may be needed for safe use. Because some bioherbicides are new to the market, data on their effectiveness against troublesome weeds is limited. Therefore, bioherbicides, when integrated with precision application technologies and non-chemical tactics, may serve as a bridging strategy for systems facing herbicide resistance. This perspective discusses the challenges and opportunities of bioherbicides as a new tool for weed control, with particular attention to application technology, regulatory pathways, and ecosystem services.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1817915</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1817915</link>
        <title><![CDATA[Can high resolution UAV-derived weed maps replace camera-based targeted spray application?]]></title>
        <pubdate>2026-04-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Madhusudhan Adhikari</author><author>Sudhir Payare</author><author>Ricardo Pinto</author>
        <description><![CDATA[Efficient weed mapping is critical for enabling site-specific weed management (SSWM) and ensuring effective targeted herbicide application in no-till dryland cropping systems. Producers are increasingly interested in using UAV (Unmanned Aerial Vehicle) based weed mapping to generate prescription maps as a lower-cost alternative to camera-based systems, yet the accuracy and operational feasibility of these UAV-derived methods remain uncertain. This study compared three UAV-based weed detection approaches, RGB Excess Green (ExG) index, NIR band thresholding, and a YOLOv11 deep learning model against a ground-based camera reference system across three mapping dates in a summer fallow field. UAV imagery was collected using RGB and multispectral sensors, and YOLO was trained on annotated RGB image tiles. Key performance metrics evaluated were prediction accuracy (MAE, RMSE, and R2), omission rates (%) and Bland-Altman analysis (bias and Limits of Agreement-LoA). Results showed that all UAV methods systematically underpredicted weeds compared to camera-based, with bias and variability increasing with weed density and from early season (April 24) to late season (June 24). RGB consistently provided the lowest errors and most stable agreement, YOLO tracked spatial patterns but had the largest underestimation, and NIR performance varied according to soil and residue conditions. Weed omission rates ranged from 41–65% for RGB, 48–73.5% for NIR, and 78–85% for YOLO. These findings demonstrate that the effectiveness of UAV-based maps is constrained by image spatial resolution, which can limit the detection of small weeds that are more vulnerable to management practices. In contrast, real-time camera-based systems improve the detection of small weeds at application, increasing herbicide application efficiency in large-scale operations. Future research should focus on refining UAV image acquisition protocols and integrating advanced sensing technologies to improve weed detection reliability across the growing season and support more effective site-specific weed management.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1795286</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1795286</link>
        <title><![CDATA[Sowing methods and early-season weed interference duration as key drivers of yield loss reduction in canola]]></title>
        <pubdate>2026-04-29T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Muhammad Awais Arshad</author><author>Rana Nadeem Abbas</author><author>Usman Zulfiqar</author><author>Ali Ahmad</author><author>Go’zal Burxonova</author><author>Mayank Anand Gururani</author>
        <description><![CDATA[Canola is a major oilseed crop of semiarid regions throughout the world. The productive performance of canola is influenced by different sowing methods and durations of weed–crop interference. Appropriate sowing methods combined with timely weed management during the early growth stages can significantly improve canola productivity. A field experiment was conducted to evaluate the effect of different sowing methods and durations of early-season weed interference on growth and yield components of canola crop at the Agronomy Research Area, Department of Agronomy, University of Agriculture, Faisalabad, during 2021–2022. The experiment consisted of three different sowing methods (flat, bed, and ridge) with five different weed–crop competition periods [weed-free control, weedy up to 30, 40, and 50 days after sowing (DAS), and full-season weed competition]. The design of the experiment was a randomized complete block design (RCBD) with a split-plot arrangement. Each treatment was replicated three times. The results showed that the lowest weed density and fresh and dry weights of weeds were observed in ridge sowing, followed by bed sowing, while the highest were recorded under the flat sowing method. Results for leaf area index, grain yield, biological yield, number of pods, number of grains/pod, harvest index, number of branches, plant height, 1,000-grain weight, and oil content showed the highest values in ridge sowing followed by bed sowing, while the lowest values were recorded under the flat sowing method. Among weed–crop competition periods, the weed-free control (season-long weed removal) produced the highest yield and quality parameters, whereas full-season weed competition resulted in the lowest crop performance. Yield and related traits progressively declined as the duration of weed competition increased from 30 days after sowing. In conclusion, the results showed that sowing method significantly influences canola yield and quality, and prolonged early-season weed interference substantially reduces crop productivity. Based on the results of this study, the ridge sowing method combined with weed-crop competition up to 30 DAS is recommended for canola cultivation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1749362</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1749362</link>
        <title><![CDATA[Deep learning-based quantification of tall fescue abundance in pastures]]></title>
        <pubdate>2026-04-23T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Ross E. Binkley</author><author>Samuel R. Revolinski</author><author>Echo E. Gotsick</author><author>Ray S. Smith</author><author>Zeya Wang</author><author>Katsutoshi Mizuta</author>
        <description><![CDATA[Accurate and rapid measurement of tall fescue abundance is essential for efficient forage management and mitigating livestock exposure to potential endophyte-related toxicity. Traditional visual estimation methods are labor-intensive and are subject to change depending on the observer doing the calculations, which limits their scalability and consistency. This study explores the application of deep learning techniques to automate and improve the classification of tall fescue abundance across pasture systems in Kentucky. Ground-truth abundance classes were evaluated using one of the traditional methods with occupancy grid and compared against estimates derived from red-green-blue images. Two convolutional neural network architectures, YouOnlyLookOnce (YOLO) and ResNet were employed for image-based classification. Among the models tested, YOLOv8x achieved a classification accuracy of 96% across three abundance classes, effectively distinguishing tall fescue from other vegetation and bare soil. Results demonstrated the potential of artificial intelligence in detecting spatial distribution of tall fescue, thereby supporting risk assessment of toxicity. Compared to the traditional methods, the deep learning approach improves efficiency and reduces manual labor efforts while maintaining highly accurate prediction performance for continuous monitoring applications.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1777087</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1777087</link>
        <title><![CDATA[Evaluation of YOLO-based weed detection models on commercial horseradish fields in Southern Illinois]]></title>
        <pubdate>2026-04-14T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Abhinav Pagadala</author><author>Sandesh Poudel</author><author>Janmejay Umakanth Rathi</author><author>S. Sunoj</author><author>John F. Reid</author>
        <description><![CDATA[Horseradish (Armoracia rusticana) is a high-value specialty crop whose production in Southern Illinois is constrained by limited herbicide options and labor-intensive weed management, particularly in commercial fields. This study developed a multisource image dataset and evaluated lightweight deep learning models to enable real-time, vision-based weed detection for future robotic weeding systems in commercial horseradish fields of Southern Illinois. Image data collection was conducted during the 2024 growing season at two commercial fields and one research site using a handheld smartphone and an unmanned ground vehicle (Farm-ng Amiga robotic platform) equipped with two stereo cameras (Luxonis OAK-D cameras). The data was first annotated, assigning appropriate labels to horseradish and weed instances, then augmented to improve data diversity. We trained and compared nine YOLO models (v8, v11, v12; nano, small, medium) using standard object detection metrics (precision, recall, F1-score, mAP@50) and computational indicators (inference time, GFLOPs, model size, training time), and selected the best configuration for hyperparameter tuning with an automated search over learning rate, regularization, and optimizer. The tuned YOLOv8-nano model achieved the best balance of detection performance and computational efficiency, and was subsequently benchmarked on multiple desktop and edge-computing platforms to assess real-time feasibility. The results demonstrated that lightweight YOLO architectures can provide accurate, fast horseradish-weed detection suitable for deployment on embedded hardware, offering a key sensing component for future autonomous mechanical weeding in commercial horseradish production. This study makes three key contributions: (i) a multisource image dataset of horseradish and weeds collected from both commercial and research fields using manual imaging and a robotic platform; (ii) an evaluation protocol that combines accuracy metrics with computational indicators to guide model selection for embedded deployment; and (iii) a cross-platform benchmarking workflow that assesses the real-time feasibility of lightweight YOLO models on desktop and edge-computing hardware for robotic weeding applications.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1789426</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1789426</link>
        <title><![CDATA[Can ligneous residues be recycled for weed control?]]></title>
        <pubdate>2026-03-27T00:00:00Z</pubdate>
        <category>Brief Research Report</category>
        <author>Mario Fontana</author><author>Luca Bragazza</author><author>Saïd Elfouki</author><author>Sandie Masson</author><author>Aurélie Gfeller</author><author>Pascal Boivin</author><author>Ophélie Sauzet</author>
        <description><![CDATA[The use of pesticides in agriculture causes problems for human health and the environment, so that alternative solutions for weed control are urgently requested. In this study we test the possibility to recycle composted wood and white fir bark as biopesticide at three different experimentation scales: (i) in Petri dish, hot water extracts of the ligneous residues were used for a germination test with rapeseed and winter wheat seeds; (ii) in greenhouse pots, two successive cycles of rapeseed sowings were carried out with an equivalent of 300 m³ ha-¹ and 600 m³ ha-¹ of ligneous residues so to assess the effect on crop seedling biomass; (iii) in a field experiment, 300 m3 ha-1 of ligneous residues were spread as mulch or incorporated into the soil just before the sowing of rapeseed in 2022 without any herbicide application. We observed that fresh bark extract prevented winter wheat and rapeseed germination, while extracts of decomposed bark and composted wood did not affect crop seed germination. In the greenhouse experiment, the biomass of rapeseed seedlings was lower with ligneous residues compared to the control, particularly with bark. In the field, only the bark had a negative effect on the number of emerging weeds during the autumn 2022, while no difference in weed biomass was observed between treatments in the following spring 2023. Overall, the 3-cm thick mulch alone was not sufficient to control the weed biomass in the field but seems promising as part of an integrated weed management strategy.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1690014</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1690014</link>
        <title><![CDATA[Can modulations of nitrogen fertilisation and crop traits promote biological weed regulation through competition? A simulation study]]></title>
        <pubdate>2026-03-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Laurène Perthame</author><author>Delphine Moreau</author><author>Thibault Maillot</author><author>Nathalie Colbach</author>
        <description><![CDATA[With the reduction of both herbicide and mineral fertiliser use for environmental reasons, crop–weed competition for nitrogen might increase in arable fields. Adapting nitrogen fertilisation and selecting crop species/varieties according to their nitrogen-nutrition traits could provide options to influence competitive relationships among plants. A simulation study was conducted to identify which nitrogen-fertilisation options and crop traits related to nitrogen nutrition have the greatest influence on weed impacts in the agroecosystem. We examined indicators of both weed harmfulness (i.e., crop grain yield loss due to weeds, field infestation by weed biomass, and weed seed production) and weed benefits (i.e., weed species richness and weed-based food offer for bees). Sensitivity analyses were performed using a process-based model (FlorSys) simulating crop and weed growth and dynamics over the years based on information on the cropping system, pedoclimate, and species traits. A maize monoculture from southwestern France was used as a case study. Different maize varieties (differing in their trait values related to nitrogen nutrition) were simulated under different scenarios of nitrogen fertilisation (application date and rate, crop residue management, and initial soil organic nitrogen) and weather. The analyses showed that nitrogen application rate and maize variety were the factors most influencing weed impacts on the agroecosystem. Decreasing nitrogen rates increased weed harmfulness and decreased maize yield potential (i.e., yield in the absence of weeds). The maize traits that both reduced weed harmfulness the most and increased maize productivity the most were low plant nitrogen demand, high root nitrogen uptake efficiency, and a specific leaf area (leaf area per unit leaf biomass) insensitive to plant nitrogen stress. These results are useful for better understanding the role of nitrogen in crop–weed competition and for identifying management strategies that promote biological weed regulation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1717415</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1717415</link>
        <title><![CDATA[Biosolarization as an alternative method to inhibit parasitic Phelipanche ramosa germination]]></title>
        <pubdate>2026-03-10T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Carolina R. Conte</author><author>Shayne Morrissey</author><author>Bradley D. Hanson</author><author>Christopher W. Simmons</author>
        <description><![CDATA[Phelipanche ramosa, or branched broomrape, is a parasitic weed that attaches to the roots of host plants and can cause great agricultural losses, from reduced yield to crop termination without harvest. Conventional approaches to manage broomrape infestations include fumigation with toxic compounds, such as methyl bromide. Solarization has been used as well, but can leave a field out of service for entire seasons. Biosolarization is an alternative pest management strategy with a shorter timeframe that can reduce the need for fumigants and preplant herbicides by amending soil with organic matter, covering with a clear tarp, and irrigating. Weed seeds subjected to biosolarization experience a variety of stresses –including biocidal organic acids, high temperatures, and low oxygen– that can prevent future germination. This study evaluated the application of biosolarization with two different amendments, three amendment rates, and three temperatures for reduction of P. ramosa germinability. Simulated biosolarization was carried out in anaerobic bioreactors of wetted and amended soil with seeds incorporated. Tomato pomace and spent mushroom substrate were used as the organic matter amendments. Soil pH, electrical conductivity, and production of biocidal organic acids were evaluated before and after biosolarization, alongside germination capacity of P. ramosa seeds. Soil metrics of biosolarization treatments were compared to unamended, solarized soil and seed germination capacity was compared to that of untreated, control seeds. Broomrape germination is triggered by strigolactone, a plant hormone released into the rhizosphere. Therefore, a strigolactone analog was used to test the germinability of the treated seeds in absence of a host. To isolate the effects of biocidal organic acid exposure on broomrape germinability, seeds were also exposed to the acids produced during biosolarization, but without the added thermal and low oxygen stresses. The results suggest that biosolarization is an effective method to reduce P. ramosa germinability by >99% with amendment rates as low as 1.0% by dry weight and temperatures of 35 °C, which can inform future validation in field studies. Use of biosolarization may help protect the production of host plants on an infested field, while reducing the need for toxic compounds or lengthy treatments.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1759319</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1759319</link>
        <title><![CDATA[Soil management in organic rainfed vineyards in the Penedès region (Catalonia, NE Spain) with cover crops and mulches. Effects on weed flora and vine vigor]]></title>
        <pubdate>2026-03-02T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Carlos Cabrera-Pérez</author><author>Jordi Llorens-Calveras</author><author>Àlex Escolà</author><author>Bàrbara Baraibar</author><author>Montse Torres-Viñals</author><author>Mireia Torres-Maczassek</author><author>Jordi Recasens</author>
        <description><![CDATA[In Mediterranean organic vineyards, repeated mechanical tillage is the standard strategy for weed control, but it contributes to soil degradation, fuel consumption, and carbon emissions. This study evaluated alternative soil management practices—cover crops in the alleyways and organic mulches under the vine row—to reduce tillage while maintaining weed suppression and vine vigor. Two field trials were conducted over two growing seasons (2021–2022), characterized by exceptionally dry conditions, in a rainfed Vitis vinifera L. cv. Chardonnay organic vineyard in the Penedès region, NE Spain. In the alleyways, two winter grasses (Hordeum vulgare and Lolium multiflorum) were sown and compared to traditional tillage management. Under the vine row, an organic pine wood chip mulch was compared to a tilled control Weed cover, vine vigor (i.e. yield, pruning weight, exposed leaf area), and canopy geometry and structure (using the principle of light detection and ranging, LiDAR) were recorded and analyzed. Cover crops effectively suppressed weeds (<10% cover), but also reduced vine vigor in both years, particularly under these extreme drought conditions. LiDAR-derived data confirmed significantly smaller canopy dimensions in vine rows bordered by cover crops compared to those between tilled alleyways. The pine mulch maintained low weed pressure and supported vine growth, showing persistence over two seasons. These results highlight the potential of organic mulching as a sustainable alternative to mechanical under-vine in-row tillage in dryland vineyards. However, the competitive impact of alleyway cover crops on vine performance must be carefully considered in water-limited environments.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1741164</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1741164</link>
        <title><![CDATA[Weed management scenario and prospects of herbicide tolerant crop technology in India]]></title>
        <pubdate>2026-02-20T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Aniruddha Maity</author><author>Debashis Paul</author><author>Prabhu Govindasamy</author><author>Rashmi Jha</author><author>Suman Dutta</author><author>Sk Asraful Ali</author>
        <description><![CDATA[Indian agriculture is the second largest contributor to the Indian economy. Globally, India ranks as the largest producer of pulses, cotton, cattle, milk, and jute and holds the second position in the production of rice, wheat, sugarcane, cotton, groundnuts, fruits, and vegetables. It is estimated that India, a country with one-fifth of the world population, needs a net quantity of 529 MT of food grains by 2050 for its food security. Although India’s 2022 foodgrain production is estimated at record 316 MT, with limited or no scope of horizontal expansion in crop area and rapid urbanization in existing crop lands, producing more food per unit area is becoming a challenge. One of the consistent and major obstacles in improving production efficiency is weed infestation in crop fields. Weeds exhibit rapid growth and extensive foliage development to suppress crop growth, and this intensive competition often deprives the main crop of the inputs required for optimal development, ultimately leading to significant yield losses or even crop failure. Although, the western countries, especially North and South American and Australia, have adopted herbicide tolerant (HT) crops, which ensures minimum or no damage to the main crops while killing the weeds by selective herbicide application, India is yet to embrace this technology. Regardless, Indian agriculture consumes a significant volume of herbicide across the crops even in the absence of HT crops. The distinctive socio-political context in India, combined with resistance from certain sections of society toward genetic engineering, has been a major factor underlying the rejection of genetically modified HT cultivars. However, with rapid transition of labor force to non-agricultural professions leading to increasing cost of manual weed control and the lack of adequate advancement in cultural and mechanical weed control tools, the pressing demand of producing significantly more food is currently a challenge for Indian agriculture. We summarize in this article the situation that indicates whether Indian agriculture, given the greater responsibility of safeguarding its demanding food requirement while maintaining the export volume, should welcome HT crop cultivars, especially in the situation of rapidly increasing labor cost.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1783794</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1783794</link>
        <title><![CDATA[Editorial: Innovative technology and techniques for effective weed control]]></title>
        <pubdate>2026-01-23T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Thomas R. Butts</author><author>Simerjeet Virk</author><author>Tom Wolf</author><author>Bruno Canella Vieira</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2026.1772118</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2026.1772118</link>
        <title><![CDATA[Correction: The usage of imidazolinone-tolerant maize in maize-soybean strip intercropping greatly facilitates weed control]]></title>
        <pubdate>2026-01-15T00:00:00Z</pubdate>
        <category>Correction</category>
        <author>Yue Zhao</author><author>Atta Mohi Ud Din</author><author>Muhammad Ali Raza</author><author>Wenyu Yang</author><author>Jialin Yu</author><author>Xing Wang Deng</author><author>Lingyang Feng</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2025.1694918</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2025.1694918</link>
        <title><![CDATA[Competitiveness of hybrid and inbred rice with junglerice (Echinochloa colona) resistant to auxinic herbicides]]></title>
        <pubdate>2026-01-12T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Juan C. Velasquez</author><author>Diego Rodriguez</author><author>Maria Fernanda Alvarez</author><author>Eduardo Graterol</author><author>Yamid Sanabria</author><author>Guido Plaza</author><author>Nilda Roma-Burgos</author>
        <description><![CDATA[Rice (Oryza sativa L.) is a crucial staple food crop, with significant production in Latin America, the Caribbean, and Asia. Weed infestations, such as with auxinic herbicide-resistant junglerice (Echinochloa colona), pose major challenges to rice production, underscoring the need for additional weed management tools, such as planting weed-competitive rice. This study evaluated the competitive ability of auxinic herbicide-resistant junglerice, with hybrid and inbred rice. Various junglerice accessions were collected and evaluated for their response to quinclorac at rates of 560 and 1,120 g a.i. ha−1. Subsequently, cross-resistance to florpyrauxifen-benzyl (FPB) was assessed using one accession with high resistance to quinclorac in dose–response assays. The intraspecific competitiveness of susceptible and resistant junglerice was evaluated in a replacement series experiment. Likewise, interspecific competitiveness of susceptible and resistant junglerice against inbred and hybrid rice was evaluated using the same approach. Large-scale testing with quinclorac indicated poor control of all junglerice accessions, achieving less than 70% control at the high rate. The one resistant accession (AR) tested showed 30-fold resistance to quinclorac and 2-fold resistance to FPB compared to the susceptible accession (UM). Under intraspecific competition, the resistant and susceptible junglerice were equally competitive, with a potential fitness penalty in the resistant population. The interspecific study suggested that, regardless of the resistance trait, junglerice was more competitive than the rice cultivars evaluated. AR biomass and leaf area exceeded those of inbred rice by ~115% and ~82% but exceeded hybrid rice by only ~70% and ~35%, respectively. This showed 21% and 26% lower relative advantage of inbred compared to hybrid rice. Breeding and planting competitive rice varieties is an ecologically viable strategy to combat weed resistance, especially in disadvantaged regions where other weed control options are limited.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2025.1704268</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2025.1704268</link>
        <title><![CDATA[Group 15 pre-emergent herbicides differentially affect plant growth, cuticular wax composition, and fatty acid metabolism in blackgrass]]></title>
        <pubdate>2025-12-11T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Hannah R. Blyth</author><author>Laurent Cornette</author><author>Barrie Hunt</author><author>Richard P. Haslam</author><author>Frédéric Beaudoin</author><author>Dana R. MacGregor</author>
        <description><![CDATA[Pre-emergent herbicides are essential tools in weed management, yet for some, we lack a molecular-level understanding of how they work. Here, we investigated how three Group 15 pre-emergent herbicides - flufenacet, S-ethyl dipropylthiocarbamate (EPTC), and tri-allate - affected growth and biochemical responses of two blackgrass (Alopecurus myosuroides) biotypes. Using a sterile, agar-based system, we quantified early seedling growth across a range of herbicide concentrations. ED40 doses defined from these (60 nM for flufenacet on shoots, 90 mM for flufenacet on roots, 600 nM for EPTC, and 6 μM for tri-allate) were used to assess the herbicides’ effects on cuticular wax composition and fatty acid metabolism using two biotypes: herbicide-sensitive “Rothamsted”, and “Peldon” which has well-characterized metabolic herbicide resistance. Flufenacet and tri-allate were both less effective on Peldon. At the ED40 dose, EPTC was less effective on Rothamsted. Flufenacet inhibited both shoot and root growth. Tri-allate and EPTC inhibited shoot growth but had no significant effect on root growth. As expected for Group 15 herbicides, total shoot wax content was affected by EPTC (Peldon -32% and Rothamsted -20%), flufenacet (Peldon -13% and Rothamsted -48%) and tri-allate (Peldon -10% and Rothamsted -32%) as were many of the compounds with chain lengths ≥C26. Unexpectedly, many of the C14-C26 species measured were altered in tri-allate, e.g. shoot α-linolenic acid was reduced by 80% and 93% in Peldon and Rothamsted, respectively. Together, these results reveal Group 15 pre-emergent herbicides cause distinct, biotype- and organ-specific actions and suggest they have different target(s) in planta.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2025.1688961</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2025.1688961</link>
        <title><![CDATA[Electrical weed control in organic highbush blueberry: influence of operational speed and number of applications on weed control]]></title>
        <pubdate>2025-10-27T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Luisa C. Baccin</author><author>Marcelo L. Moretti</author>
        <description><![CDATA[Weed control remains a critical challenge for organic blueberry producers in the Pacific Northwest, where most U.S. organic blueberry hectarage is concentrated. Electrical weed control (EWC) offers a nonchemical alternative by applying high-voltage currents to plant foliage, disrupting vascular function through heat-induced tissue damage. This study evaluated how operational speed and the number of EWC applications influence weed control efficacy across five field studies in certified organic blueberry fields in Oregon, using two types of commercial EWC equipment. Slower speeds (0.5–1 km h-1; 69–35 kJ m-2) achieved the highest efficacy, providing >80% weed control at 28 days after initial treatment (DAIT) and reducing biomass by up to 73% compared to nontreated. Sequential applications were critical for sustained control: two applications at 2 or 4 km h-1 (17–9 kJ m-2 per application) provided 77–83% weed control at 42 DAIT. Species-specific responses were observed, with northern willowherb (Epilobium ciliatum) and Pennsylvania smartweed (Persicaria pensylvanica) being more sensitive to EWC with 85–100% control at 42 DAIT, while tall fescue (Festuca arundinacea) and sharppoint fluvellin (Kickxia elatine) required multiple treatments and higher energy doses (≥24 kJ m-2) to reach 67–73% control at the same period. In a combined methods study long-term efficacy declined with single-application treatments, with control dropping below 20% by 56 DAIT, whereas sequential applications sustained >40% control. These results demonstrate that EWC provides effective nonchemical weed management in organic blueberry production, with operational speed and sequential applications key to maintain high levels of weed control.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2025.1574497</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2025.1574497</link>
        <title><![CDATA[Impact of simulated rainfall on atrazine wash off from roller crimped and standing cereal rye (Secale cereale L.) residue onto the soil]]></title>
        <pubdate>2025-10-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Lucas O. R. Maia</author><author>Shalamar D. Armstrong</author><author>Eileen J. Kladivko</author><author>Bryan G. Young</author><author>William G. Johnson</author>
        <description><![CDATA[The combination of soil residual herbicides and cover crops is an integral part of best management practices for herbicide-resistant weeds. However, the interception of soil residual herbicides by cover crop biomass interferes with herbicides reaching the soil, which can lead to lower weed control efficacy and increased selection pressure for herbicide resistance. Once intercepted, these herbicides can only move to the soil with water from rainfall or irrigation. Field trials were conducted in 2022 and 2023 to investigate the effect of cover crop termination strategies (fallow, standing, and roller crimped) and simulated rainfall volumes (0, 4.2, and 8.3 mm simulated over 20 min; equivalent to 0, 12.5, and 25 mm h-1) on atrazine wash off from cereal rye (Secale cereale L.) biomass onto the soil. The use of roller crimper resulted in an average of 10% greater ground cover relative to the standing cereal rye. Atrazine interception that was bound to rye biomass reached 29 and 94% in 2022 and 2023, respectively. In 2022, the concentration of atrazine in the soil under roller crimped cereal rye was 9% greater than that understanding cereal rye, after 4.2 mm of rainfall. In 2023, when cereal rye biomass more than doubled, only 6% of the applied atrazine was found under roller crimped cereal rye, after 8.3 mm of rainfall. Cereal rye biomass accumulation negatively impacted the amount of atrazine reaching the soil at the time of application. Although the roller crimped cereal rye reduced the amount of herbicide reaching the soil relative to the standing cereal rye, it also reduced atrazine leaching below the 0–5 cm of soil. In cover cropping systems with high levels of cereal rye biomass (e.g., > 7,000 kg ha-1), more than 8.3 mm of rain are required to wash most of the atrazine off of the biomass.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2025.1699702</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2025.1699702</link>
        <title><![CDATA[Preference and performance of Polymorphomyia basilica on different phenotypes of Chromolaena odorata and other Asteraceae in the laboratory]]></title>
        <pubdate>2025-10-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Thandeka Mahlobo</author><author>Nontembeko Dube</author><author>Costas Zachariades</author><author>Thinandavha Caswell Munyai</author>
        <description><![CDATA[Chromolaena odorata, a weed of neotropical origin, remains insufficiently controlled by biological means in South Africa. The stem-galling fly Polymorphomyia basilica was introduced as a potential agent and previously shown to be largely host-specific under no-choice conditions. This study conducted multichoice and no-choice trials to test five nontarget plant species previously selected by P. basilica in no-choice trials, and to assess the fly’s preference and performance on various C. odorata phenotypes, including the southern African biotype (SAB) and the Asian/West African biotype (AWAB). Survival and development rates of P. basilica were highest on C. odorata (SAB) and Ageratum conyzoides. Only a few galls produced adult flies on Stomatanthes africanus and Campuloclinium macrocephalum, and these adults showed low longevity. P. basilica displayed a strong preference for and high performance on C. odorata (SAB) in both trial types, with over 90% of progeny surviving to adulthood. Many larvae also developed successfully on the Taiwan 129/130 (AWAB) and Jamaican 117 phenotypes, whereas development was poorer on other phenotypes. Although the cause of variation among phenotypes remains unclear, the results indicate that P. basilica is a suitable biocontrol agent for C. odorata in South Africa and can sustain populations on the AWAB biotype where it is invasive.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2025.1627437</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2025.1627437</link>
        <title><![CDATA[Effect of pesticide and other crop protection product mixtures on dicamba volatilization]]></title>
        <pubdate>2025-09-04T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Renato Nunes Costa</author><author>Giovanna Gimenes Cotrick Gomes</author><author>Matheus Palhano</author><author>Henrique Barbosa</author><author>Dyrson Abbade Neto</author><author>Ramiro Fernando López Ovejero</author><author>Edivaldo Domingues Velini</author><author>Caio Antonio Carbonari</author>
        <description><![CDATA[Dicamba is an important tool for managing hard-to-control weeds in Brazil. Its use has increased, especially with the adoption of dicamba-tolerant crops, making the implementation of best management practices essential to ensure safe herbicide application, whether alone or in combination with other products. This study evaluated the volatilization of dicamba (diglycolamine salt – DGA) applied alone or in tank mixtures with glyphosate potassium salt (GK), a volatility reducer (VR), and various commercial crop protection products, over corn straw under controlled conditions. Volatilized dicamba was collected for 24 h at 40 °C and quantified by LC–MS/MS (LOD = 0.09 ng mL-¹, LOQ = 0.39 ng mL-¹). The VR consistently reduced dicamba vapor losses by up to 90%, regardless of the mixture. Most tank mixes did not increase volatility relative to DGA + GK + VR, except for combinations with glufosinate ammonium and mesotrione + atrazine, which increased volatilization by 49% and 43%, respectively, compared to DGA + GK + VR, though still ~70% lower than dicamba applied alone. These increases were likely related to ammonia release and interactions with amine groups, rather than pH differences. Findings demonstrate that VRs are effective for mitigating dicamba volatilization even in complex mixtures, but certain combinations require caution. Results provide practical guidance for tank-mix decisions and support the adoption of best practices to reduce volatility-related drift in dicamba-based weed control.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fagro.2025.1633565</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fagro.2025.1633565</link>
        <title><![CDATA[Physiological action of bioherbicides in weed control: a systematic review]]></title>
        <pubdate>2025-08-08T00:00:00Z</pubdate>
        <category>Systematic Review</category>
        <author>Zhenglin Zhang</author><author>Aaron Becerra-Alvarez</author><author>Kassim Al-Khatib</author>
        <description><![CDATA[IntroductionBioherbicides are naturally derived substances that can be used to control weeds. Bioherbicide compounds can be alternatives to synthetic herbicides and are key resources for the discovery of novel molecules and modes of action (MOA) for weed control. To better understand the physiological action of bioherbicides, a systematic review was conducted with an emphasis on understanding the MOA of bioherbicides.MethodsA systematic review screened 287 studies of published literature. The review retained seventeen studies that demonstrated evidence of bioherbicide mode of action.ResultsFrom our review, we found that bioherbicides are often a mixture of various substances and potentially have multiple MOAs. Compound mixtures present in bioherbicides intrinsically increase the difficulty level in elucidating the mechanistic causation for plant injury. The majority of empirical studies reported injury to weeds at the plant, tissue, or cell level - but were unable to define specific biological pathways affected by bioherbicide application. In total, seventeen studies had strong evidence for specific MOAs, including photosystem II inhibition, microtubule synthesis inhibition, carotenoid synthesis inhibition, cellular metabolism inhibition, and auxin mimics.DiscussionHypothesis driven research, chemical characterization, gene expression, and molecular in-silico modeling were important steps in identifying the MOA and should be considered in future studies. It was not uncommon to observe bioherbicide compounds with evidence for more than one MOA. With a better understanding of bioherbicides and their herbicidal action, increased efficacy can be achieved and catalyze novel product development.]]></description>
      </item>
      </channel>
    </rss>