Herbicide Application Research Articles

Synergistic impact of tank mixing pendimethalin and pyroxasulfone on soil enzymatic and microbial dynamics.

A field experiment was carried out during the Rabi 2022-23 at Punjab Agricultural University, Ludhiana to evaluate the effect of pyroxasulfone and pendimethalin on soil enzymatic and microbial activities when applied individually or as a tank mix combination. The experiment employed a factorial randomized complete block design in triplicate encompassing 16 treatments. Control soils exhibited a continuous increase in enzymatic and microbial activities over time. In herbicide-treated plots, a highly dose-dependent lag phase was observed in all enzymatic and microbial activities which gets shorter or disappear at higher application rates. Following the initial lag phase, inhibition in enzymatic and microbial activities was observed with higher inhibition in tank mix combination (90.7 to 99.1% up to 90days after herbicide application (DAA) followed by pendimethalin (77.3 to 92.9% up to 90 DAA) and pyroxasulfone (30.3 to 76.2% up to 45 DAA). After initial inhibition, enzymatic and microbial activities increased at harvest. Principal component analysis (PCA) revealed that dehydrogenase activity among soil enzymes and bacteria among microbial populations were more sensitive to studied herbicides. Based on the values of the Integrated Biomarker Response (IBRv2), pendimethalin had a greater impact on soil activities than pyroxasulfone, and their combined application exhibited a synergistic effect.

A comparative study of drone and manual herbicide application for weed management in wet direct-seeded rice (Oryza sativa L.)

A field experiment was conducted at Tamil Nadu Agricultural University, Coimbatore, during the Navarai season (January-April) of 2024 to assess the efficiency of drone-based herbicide application in terms of weed control, energy use, and cost effectiveness in wet direct-seeded rice (Oryza sativa L.). The study compared the effectiveness of weed control using herbicide combinations applied as pre-emergence followed by early post-emergence, with both drone and knapsack sprayer. The treatments included the application of pretilachlor followed by early post-emergence bispyribac sodium, and pyrazosulfuron followed by penoxsulam + cyhalofop butyl, using both drone and knapsack sprayer. Additionally, weed-free and unweeded control plots were included. Results indicated that the application of pretilachlor followed by bispyribac sodium using a drone sprayer significantly reduced weed density and weed dry weight compared to the unweeded plot. This treatment also resulted in a higher grain yield (5286 kg ha-1). Moreover, drone application of pretilachlor followed by bispyribac sodium provided a higher net return (? 51631/ha), benefit-cost ratio (2.17), energy-use efficiency (9.53), and energy productivity (0.30 kg/MJ). The experiment concluded that drone-based spraying of pretilachlor followed by bispyribac sodium is an effective weed management strategy for wet direct-seeded rice, offering superior yield attributes, energy use efficiency, and profitability.

Sustainable integrated weed control strategies to reduce herbicide use in sunflower production

This research aims to develop integrated weed control strategies that can effectively reduce the quantity of herbicides used in cultivation of sunflower. To address the challenge of weed management in mechanized crop fields and mitigate the adverse effects on the ecosystem, an experiment with 10 treatments was arranged in randomized block designs and replicated 3 times. The treatments included combinations of herbicide application, band application of herbicide and power weeder weeding. The higher weed control efficiency (WCE) was achieved in a weed-free environment. Additionally, higher WCE was observed in the treatment where weeds were managed through band application of pendimethalin (38.7 capsule suspension (CS)) in the seed row as a pre-emergence method and weeding was done with a power weeder twice. These 2 treatments registered more than 90 % WCE due to lesser weed occurrence. The present investigation also registered higher grain yield under weed-free control (2212 kg/ha). It was tailed by Pre-emergence (PE) herbicide (1 kg/ha of Pendimethalin (38.7 CS)) in seed row after irrigation followed by (fb) power weeder twice (on 15-20 and 30-35 DAS), PE herbicide (1 kg/ha of Pendimethalin (38.7 CS)) in seed row before irrigation fb power weeder twice (on 15-20 and 30-35 DAS) and PE herbicide (1 kg/ha of Pendimethalin (30 EC)) in seed row after irrigation fb power weeder twice (on 15-20 and 30-35 days after sowing (DAS)). Based on the results, pendimethalin (38.7 CS) can also be applied either before or after irrigation, as it will not significantly lose its efficacy in controlling weeds. These findings have practical implications for sunflower cultivation, offering effective strategies for integrated weed control.

Targeted weed management of Palmer amaranth using robotics and deep learning (YOLOv7).

Effective weed management is a significant challenge in agronomic crops which necessitates innovative solutions to reduce negative environmental impacts and minimize crop damage. Traditional methods often rely on indiscriminate herbicide application, which lacks precision and sustainability. To address this critical need, this study demonstrated an AI-enabled robotic system, Weeding robot, designed for targeted weed management. Palmer amaranth (Amaranthus palmeri S. Watson) was selected as it is the most troublesome weed in Nebraska. We developed the full stack (vision, hardware, software, robotic platform, and AI model) for precision spraying using YOLOv7, a state-of-the-art object detection deep learning technique. The Weeding robot achieved an average of 60.4% precision and 62% recall in real-time weed identification and spot spraying with the developed gantry-based sprayer system. The Weeding robot successfully identified Palmer amaranth across diverse growth stages in controlled outdoor conditions. This study demonstrates the potential of AI-enabled robotic systems for targeted weed management, offering a more precise and sustainable alternative to traditional herbicide application methods.

Effects of Various Herbicide Types and Doses, Tillage Systems, and Nitrogen Rates on CO2 Emissions from Agricultural Land: A Literature Review

Although herbicides are essential for global agriculture and controlling weeds, they impact soil microbial communities and CO2 emissions. However, the effects of herbicides, tillage systems, and nitrogen fertilisation on CO2 emissions under different environmental conditions are poorly understood. This review explores how various agricultural practices and inputs affect CO2 emissions and addresses the impact of pest-management strategies, tillage systems, and nitrogen fertiliser usage on CO2 emissions using multiple databases. Key findings indicate that both increased and decreased tendencies in greenhouse gas (GHG) emissions were observed, depending on the herbicide type, dose, soil properties, and application methods. Several studies reported a positive correlation between CO2 emissions and increased agricultural production. Combining herbicides with other methods effectively controls emissions with minimal chemical inputs. Conservation practices like no-tillage were more effective than conventional tillage in mitigating carbon emissions. Integrated pest management, conservation tillage, and nitrogen fertiliser rate optimisation were shown to reduce herbicide use and soil greenhouse gas emissions. Fertilisers are similarly important; depending on the dosage, they may support yield or harm the soil. Fertiliser benefits are contingent on appropriate management practices for specific soil and field conditions. This review highlights the significance of adaptable management strategies that consider local environmental conditions and can guide future studies and inform policies to promote sustainable agriculture practices worldwide.

Beyond yield: Unveiling farmer perceptions and needs regarding weed management in Bangladesh.

More than 3.5 billion people depend on rice for more than 20% of their daily calories. Globally, Bangladesh is the third largest rice producer. With 171 million people, Bangladesh is also among the top consumers. Local rice production not only affects the country's food security but also influences the global rice trade. A large yield gap has been reported due to weeds. Traditional hand weeding is very costly because of labor shortages resulting from industrialization. Limited data showed a higher yield and profits when using herbicides. However, quantitative data on various aspects of weed management and associated issues representing the country's variable rice ecosystem, which is characterized by 30 agroecological zones, are lacking. We collected data on weed management practices from 865 farmers and 69 agrochemical shops covering all 30 agro-ecological zones (AEZs) through a structured survey. We observed a significant regional variation among various parameters. Approximately 82% of farmers use herbicides, and few rely solely on either manual weeding or herbicides. Pre-emergence herbicides are the predominant. Application procedures are almost the same across the country. Although 40% of farmers had secondary and higher-level education, most depend upon local sellers' suggestions rather than reading the product label regarding the dose. Few farmers consider herbicides hazardous, and respondents rarely perceive any environmental impact. Pyrazosulfuron ethyl (35%) and acetochlor-containing bensulfuron methyl (27%) are the most-used chemical species. Approximately 45% of farmers observed that herbicides suppress early seedling growth. Additional fertilizer is required to compensate for this. Multiple weed species that are difficult to control through presently used herbicides were noted in all AEZs. Around 64% of farmers observed that herbicide application contributes to higher yields as a function of timely weeding. Cost comparisons showed that high labor prices will make rice cropping unprofitable in most parts of the country if herbicides are eliminated. Clear adverse effects of pre-emergence herbicides on early crop growth implied the potential benefits of broad-spectrum herbicide-tolerant genetically engineered (GE) rice to sustain the country's food security. Additionally, such GE rice could incentivize the adoption of alternate wet and dry irrigation methods, leading to water and cost savings.

Anthoxanthum odoratum (Poaceae) as a bioindicator of arbuscular mycorrhizal fungi abundance prior to native revegetation on agricultural soils

ABSTRACT Mycorrhizal fungi, which form symbiotic associations with plant roots, can be critical to the successful establishment of plants. Up to 90% of land plant species form associations with arbuscular mycorrhizal fungi (AMF), which develop fungal structures inside host roots. Common site preparation practices prior to ecological restoration, such as soil disturbance and herbicide application, may lessen the availability of AMF, potentially jeopardising plant establishment. However, the state of the soil microbiome can be difficult to assess directly. This study examines the potential of the widespread pasture grass Anthoxanthum odoratum (Sweet Vernal, Poaceae) as a bioassay of AMF abundance in soils. We present a rapid clearing and staining protocol for visualising AMF structures in the roots of A. odoratum. We then compare % colonisation on roots of naturally established A. odoratum plants collected from undisturbed pastures vs. sprayed and tilled pastures. Roots of A. odoratum collected from sprayed and tilled pastures showed a significantly lower average AMF colonisation at 43.8% compared with 57.6% on roots from undisturbed pastures. However, all plants sourced from the sprayed and tilled pastures still showed some AMF structures. Our results strongly suggest that A. odoratum can be a useful bioindicator of AMF presence and abundance in soils, offering a promising tool for seed-based restoration on retired agricultural land.

Impact of reduced rates of tiafenacil at vegetative growth stages on soybean growth and yield

Abstract Tiafenacil is a new non-selective protoporphyrinogen IX oxidase (PPO)-inhibiting herbicide with both grass and broadleaf activity labeled for preplant application to corn (Zea mays L.), cotton (Gossypium hirsutum L.), soybean [Glycine max (L.) Merr.], and wheat (Triticum aestivum L.). Early-season soybean emergence and growth often coincide in the U.S. Midsouth with preplant herbicide application in later-planted cotton and soybean, thereby increasing opportunity for off-target herbicide movement from adjacent fields. Field studies were conducted in 2022 to identify any deleterious impacts of reduced rates of tiafenacil (12.5% to 0.4% of the lowest labeled application rate of 24.64 g ai ha−1) applied to 1- to 2-leaf soybean. Visual injury at 1 wk after treatment (WAT) with 1/8×, 1/16×, 1/32×, and 1/64× rate of tiafenacil was 80%, 61%, 39%, and 21%, while at 4 WAT, these respective rates resulted in visual injury of 67%, 33%, 14%, and 4%. Tiafenacil at these respective rates reduced soybean height 55% to 2% and 53% to 5% at 1 and 4 WAT and soybean yield 53%, 24%, 5%, and 1%. Application of tiafenacil directly adjacent to soybean in early vegetative growth should be avoided, as severe visual injury will occur. In cases where off-target movement does occur, impacted soybean should not be expected to fully recover, and negative impact on growth and yield will be observed.

The Relationship between the Density of Winter Canola Stand and Weed Vegetation

Canola (Brassica napus L.) is an important oilseed crop that provides essential vegetable oil but faces significant competition from weeds that are influenced by various agronomic practices and environmental conditions. This study examines the complex interactions between canola stand density and weed intensity over three growing seasons, identifying a total of 27 weed species. It is important to establish a connection between the density of winter canola stands, the intensity of weeding and the response of individual weed species in real conditions. The case study was executed on plots located in the Přerov district (Olomouc region, Czech Republic). The assessment was carried out during two periods—autumn in October and spring in April. Canola plants (plant density) were counted in each evaluated area, weed species were identified, and the number of plants for each weed species was determined. Half of the plots were covered with foil before herbicide application to prevent these areas from being treated with herbicides. We used redundancy analysis (RDA) to evaluate the relationships between canola density and weed dynamics, both with and without herbicide treatment. The results show the ability of canola to compete with weeds; however, that is factored by the density of the canola stand. In dense stands (over 60 plants/m²), canola is able to suppress Galium aparine L., Geranium pusillum L., Lamium purpureum L., Papaver rhoeas L. and Chamomilla suaveolens (Pursh) Rydb. Nevertheless, there are weed species that grow well even in dense canola stands (Echinochloa crus-galli (L.) P. Beauv., Phragmites australis (Cav.) Steud., Tripleurospermum inodorum (L.) Sch. Bip. and Triticum aestivum L.). These findings highlight the potential for using canola stand density as a strategic component of integrated weed management to reduce herbicide reliance and address the growing challenge of herbicide-resistant weed populations. This research contributes significantly to our understanding of the dynamics of weed competition in canola systems and informs sustainable agricultural practices for improved crop yield and environmental stewardship.

Development of ExG, ExR, ExGR, HSV, CIELAB Images from RGB Images Using Image Segmentation Algorithm in Computer Vision Based Herbicide Spraying Applications

Weed management in agriculture is critical for preventing crop yield losses, with traditional methods often leading to environmental harm and increased production costs. This study explores the development of color indices and models for weed detection in computer vision-based herbicide spraying applications. Among the all sensors, RGB colour cameras offer several advantages, including low cost and wide availability of image processing libraries tailored for RGB image analysis. In present study a Logitech C270 webcam was used for acquiring the RGB images and a specially python algorithm was developed for image segmentation based on color. Excess Green (ExG), Excess Red (ExR), Excess Green minus Red (ExGR), HSV, and CIELAB color model images are developed by using algorithm. The research demonstrates that while ExG and ExGR indices are effective under specific conditions, the CIELAB model offers superior segmentation results across varying lighting environments. Among all these color indices and models, particularly CIELAB, can enhance the precision of weed detection in automated herbicide applications, thereby reducing environmental impact and improving agricultural efficiency.

Selectivity of pre-emergent herbicides in cassava (Manihot esculenta Crantz) and its relationship with the stem cutting planting system

Cassava (Manihot esculenta Crantz, Euphorbiaceae), an important source of food for millions of people in the world, is distributed mainly in Asia, Africa, Latin America, and the Caribbean. Weeds are important biotic constraints on cassava production, and herbicide application can provide effective weed control in this crop. However, the different possibilities of herbicide selectivity (factors associated and not associated with the plants) must be studied before implementation. The aim of this study was to evaluate the effects of the combination of different pre-emergence herbicides and two stem cutting planting systems (vertical and horizontal) on phytotoxicity and several agronomic traits of the cassava crop. The experiment was conducted through a factorial arrangement in a completely random design in Corrientes, Argentina. The factors studied were planting systems (horizontal and vertical position), weed control methods (hoeing or application of diuron, S-metolachlor, pendimethalin or clomazone, 625; 1920; 900 and 1000 g a.i. ha−1, respectively), and cropping seasons (2018–2019 and 2019–2020). The following variables were measured: phytotoxicity, plant height, relative plant stand, total weight of tuberous roots per plant, starch concentration of tuberous roots, and starch production per ha. The highest precipitations occurred in the 2018–2019 cropping season. The vertical planting system in combination with herbicides showed lower phytotoxicity values and higher values of plant height, starch concentration, and starch production per ha than the horizontal planting system. The highest phytotoxicity values were recorded with the application of diuron combined with the horizontal planting system and in the 2018–2019 season, with a 33.33% decrease in relative plant stand compared to the use of hoeing. Starch concentration remained unchanged with the use of clomazone and pendimethalin, whereas the effect of these herbicides on starch production varied with the cropping season, decreasing only in 2019–2020. Starch production was significantly lower with the use of S-metolachlor (up to 55.29% in 2018–2019) and of diuron (up to 60.57% in 2019–2020) than with the use of hoeing. In conclusion, phytotoxicity values were higher for the horizontal planting system than for the vertical system. The herbicide with the highest phytotoxic effect on the cassava crop was diuron; the effect increased when combined with the horizontal planting system in the cropping season with higher rainfall. This work provides the basis for integrated weed management concerning the use of herbicides and their selectivity according to planting systems for cassava crops.

Enzymatic Degradation toward Herbicides: The Case of the Sulfonylureas.

Commercial herbicides, particularly sulfonylureas, are used worldwide and pose a significant challenge to environmental sustainability. The efficient degradation of sulfonylurea herbicides is critical. SulE, an esterase isolated from the bacterial strain Hansschlegelia zhihuaiae S113, shows degradation activity toward sulfonylurea herbicides. However, the detailed catalytic mechanism remains vague to a large extent. Herein, we decipher the SulEP44R-catalyzed degradation mechanism of sulfonylurea herbicides using hybrid quantum mechanics and molecular mechanics approaches. Our results show that the degradation of sulfonylureas catalyzed by SulEP44R involves four concerted elementary steps. The rate-determining step has an energy barrier range of 19.7-21.4 kcal·mol-1, consistent with the experimentally determined range of 16.0-18.0 kcal·mol-1. Distortion/interaction analysis demonstrates that active-site amino acids play a vital role in the enzymatic catalytic efficacy. The unique architecture of SulEP44R's active site can serve as an excellent template for designing artificial catalysts. Key structural and charge parameters affecting catalytic activity were systematically screened and identified. Based on the elucidated degradation mechanism, several new herbicides with both high herbicidal activity and biodegradability were developed with the aid of a high-throughput strategy. Our findings may advance the application of sulfonylurea herbicides within the framework of environmental sustainability.

Synergistic adsorption and degradation of sulfonylurea herbicides by biochar-supported nano zero-valent iron composites in in-situ soil remediation

The extensive and continuous application of sulfonylurea herbicide is crucial for weed management but has resulted in widespread non-point source pollution. In this study, nano zero-valent iron/biochar (nZVI/BC) was synthesized by using FeCl3-impregnated corn stalks under anoxic pyrolysis conditions, which was applied in the in-situ remediation of bensulfuron methyl (BSFM) and sulfometuron methyl (SMTM) polluted soil. The results show that nZVI/BC with a 2.7 ratio of Fe/C had the highest efficiency in removing sulfonylurea herbicides. The removal efficiencies of BSFM and SMTM by nZVI/BC were negatively correlated to initial concentrations of sulfonylurea herbicides and positively correlated to nZVI/BC addition amount in the soil. Moreover, nZVI/BC could remove 53 % of BSFM and 72 % of SMTM at the concentration of 5 mg/kg after 21 d, which was much higher than that of BC. Notably, the removal efficiency of BSFM by nZVI/BC reached 36 % within 7 d, while the removal efficiency of SMTM by nZVI/BC was up to 68 % even within 3 d. The adsorption of herbicides by nZVI/BC was mainly driven by chemical processes involving multilayer adsorption. Furthermore, the removal mechanisms of BMTM and SMTM by nZVI/BC also involved C = O and C–O groups and oxidation of nZVI to FeO and Fe3O4 along with the cleavage of the sulfonylurea bridge. This study provides a promising application of nZVI/BC in in-situ remediating sulfonylurea herbicide- polluted soil.

Identification of weeds in cotton fields at various growth stages using color feature techniques

Weeds affect the growth and yield of cotton (Gossypium hirsutum), which is the most prevalent commercially viable non-food crop. Accurate differentiation between weeds and cotton plants is crucial for implementing precise weed-control strategies, optimizing crop yields, and minimizing herbicide usage. In this study, we aimed to investigate the effectiveness of using color feature techniques combined with Otsu's method (OTSU) to distinguish weeds from cotton plants at various growth stages. The results revealed that the image segmentation approach achieved a recognition rate of 74.17% during the second growth stage. In the third growth stage, the weed identification process primarily targeted lambsquarters (Chenopodium album). The standard deviation (SD) difference between the red (R), green (G), and blue (B) components of the plant images revealed that the difference between the SD values of R and B was <5, which could serve as an effective threshold for identifying lambsquarters. Additionally, the recognition rates for cotton and lambsquarters were 71.40% and 92.90%, respectively, and the overall recognition rate reached 82.10% during the identification process. The results of this study have practical implications for weed management practices, such as targeted herbicide application, mitigation of environmental impacts, and contribution to higher crop yields. Future research will focus on refining these methods by exploring advanced image processing techniques that integrate deep learning for automatic feature extraction, which will be evaluated for handling complex agronomic scenarios, such as leaf occlusion, varying growth stages, and image noise.

Weed management options in drum seeded wetland rice

High labour requirement and cost for raising nursery and transplanting of the seedlings has necessitated the shift from transplanted rice to direct-seeded rice. To reduce the requirement of large quantity of seeds, incidence of pests and diseases in broadcasting and to ensure uniform seed distribution for consistent crop growth and easier maintenance, mechanization is needed in direct-seeded rice. The major constraint experienced in wet DSR is the occurrence of high weed infestation as emerging seedlings in direct-sown fields are less competitive with concurrently emerging weeds. An experiment was conducted at M. S. Swaminathan Rice Research Station, Moncompu, Kerala Agricultural University during kharif and rabi 2021-22, with eight treatments and three replications in randomised complete block design to identify suitable cost-effective agronomic management practices to enhance the productivity of drum seeded rice and to maximise its resource-use-efficiency. The results revealed wet DSR using drumseeder as a viable crop establishment method for reducing the seed requirement, cultivation time, energy, cost of cultivation, pest and disease infestation, minimise plant stress due to transplanting and sustaining yield. There was significant variation in the yield and yield attributes in drum seeding depending on the weed management strategies adopted viz., two conoweedings, post emergent herbicide application, pre followed by post emergent herbicide application, post emergent herbicide application followed by conoweeding. Post-emergence application of Chlorimuron ethyl + Metsulfuron methyl @ 0.004 kg/ha and Penoxsulam + Cyhalofop butyl @ 0.135 kg/ha as tank mix at 18 DAS followed by conoweeding at 30 DAS was found economical in drum seeding which was on par yield with broadcasted crop yield under post emergent herbicide application.

Herbicide paraquat dichloride augments the expression of the c-abl-noxa-apoptotic pathway, instigating ovarian atresia in edible fish, Channa punctatus.

Ovarian cells of animals undergo atresia to regulate egg numbers and their release. However, unrestrained atretic activity decreases the chances of oocyte maturity and further process, ultimately resulting in a reduced population. Edible fishes are a critical source of nutrition and it is required to regulate their population. The application of herbicides at fish production sites is a threat to their population by altering female reproductive activity. In concern to this, here, this 60-day study investigates herbicide paraquat dichloride (PD)-induced atresia in ovarian cells of Channa punctatus (C. punctatus). Further, 96-h LC50 of PD for C. punctatus was calculated as 58.40mg/L. At the end of each exposure period, an increase in intracellular ROS in blood cells and activities of SOD and CAT in ovary tissue were observed in PD-treated fish with increasing concentration. The frequency of micronuclei in blood cells subsequently increased with the highest PD concentration. A significant (p < 0.05) increase in the relative expression of target genes was observed at the 30th and 60th day of the sampling periods in the fish treated with the highest concentration of PD. The histological study confirmed the occurrence of atretic ovary cells in PD-exposed fish. From the results it can be concluded that PD enhances the uncontrolled death of ovarian cells and has consequences of impairing the ovary health and reproductive potential of fish, hence reducing the fish population.

Weed management strategies for grain legumes in different regions of Morocco

This study examines weed management in legume crops in Morocco. Faced with the challenges of climate change, financial profitability, and herbicide resistance, farmers are adopting a range of strategies, from plowing to herbicide use to agroecological practices. A survey of 244 farmers was conducted in different regions of Morocco. The results show that crop rotation is the most common weed management practice (81.15%), followed by herbicide use (59.43%) and manual weeding (35.25%). Major challenges include weed diversity (81.16%) and weed control budget constraints (84.84%). Farmers’ observations suggest that larger plots are associated with higher weed frequency, underlining the importance of adjusting herbicide application according to field size. In summary, Moroccan farmers are adopting an integrated approach, combining plowing, crop rotations, and herbicides for effective weed management, while facing complex challenges. It is essential to promote innovative and sustainable farming practices, guided by the results of this study, with an emphasis on developing weed-resistant legume varieties. In addition, raising farmers’ awareness of best practices, including the judicious use of herbicides, is crucial for sustainable agriculture in Morocco.

Toxicity mechanism of organosilicon adjuvant in combination with S-metolachlor on Vigna angularis

The widespread use of S-metolachlor (ME) in agriculture to suppress weeds and boost crop yields, particularly in cultivating Vigna angularis, is well established. However, the application of organosilicon adjuvants with herbicides has potential threats to non-target crops. This study investigates the toxicity symptoms and mechanisms when V. angularis is exposed to ME in conjunction with a common organosilicon adjuvant. Results indicate that ME inhibits the growth of V. angularis seedlings, and adding adjuvants could aggravate the negative effects of ME. According to the growth index of seedlings, the adjuvant increased the toxicity of ME by 84–96 %. Additionally, the chlorophyll content, root permeability, and antioxidant indicators in the seedlings were also adversely affected. Integrated metabolomics and transcriptomics analyses reveal that differentially abundant metabolites (DAMs) and differentially expressed genes (DEGs) are mainly enriched in four ways: "lysine degradation," "ABC transporters," "phenylalanine metabolism," and "monoterpenoid biosynthesis." The metabolic pathways and gene regulatory network involving 11 DAMs and 22 DEGs are associated with the physiological processes affected by ME and the adjuvant. This study provides guidance for the application of herbicides and their adjuvants in agricultural production to minimize adverse effects on non-target crops.

Noxious Weed Species Monochoria vaginalis Resistant to Synthetic Auxin and Acetolactate Synthase Inhibitor Herbicides

&lt;em&gt;Monochoria vaginalis&lt;/em&gt; (Burm. f.) C. Presl is a dominant weed in paddy rice cultivation, significantly threatening productivity and farming sustainability. In Subang, Indonesia, synthetic auxin and acetolactate synthase (ALS) inhibitors are commonly used to control &lt;em&gt;M. vaginalis&lt;/em&gt;. However, farmers have currently reported declining efficacy of these herbicides. Therefore, this study aimed to confirm the resistance of &lt;em&gt;M. vaginalis&lt;/em&gt; to the early post-emergence application of synthetic auxin and ALS inhibitors. Plant bioassays were conducted using the pot test method to determine resistance level. Herbicides were applied 2 weeks after planting &lt;em&gt;M. vaginalis&lt;/em&gt; at 0.25, 0.5, 1.0, 2.0, 4.0, and 8.0 times the recommended dose, and untreated plants as control. Herbicides tested were 2,4-D, bensulfuron-methyl, bispyribac sodium, penoxulam, and sulfentrazone. The results obtained based on resistance index values (RI) showed that &lt;em&gt;M. vaginalis&lt;/em&gt; populations from Kediri and Gandasari, Subang, had moderately to high resistance to 2,4-D (RI: 8.15 and 13.0) and bensulfuron-methyl&lt;em&gt; &lt;/em&gt;(RI: 205.61 and 21.80). Weed was moderately resistant to bispyribac sodium&lt;em&gt; &lt;/em&gt;(RI of Kediri biotype: 8.79) and had low to moderate resistance to penoxulam herbicides (RI: 8.94 and 3.56). In contrast, &lt;em&gt;M. vaginalis-&lt;/em&gt;resistant biotypes remained susceptible to sulfentrazone (protoporphyrinogen oxidase/PPO inhibitors) herbicide. A significant increase in GR50 was observed between 28 and 56 days after herbicide application, signifying enhanced regrowth. The resistance of &lt;em&gt;M. vaginalis&lt;/em&gt; to synthetic auxin and ALS inhibitors presents the need for farmers to consider alternative herbicides, such as PPO inhibitors, to prevent the development of resistant weeds.

The Impact of Integrated Weed Management Practices on Nutrient Uptake in Rice (Oryza sativa L.)

The study investigated the impact of integrated weed management practices on nutrient uptake in rice (Oryza sativa L.) and weeds at 90 days after transplanting (DAT) over the 2022 and 2023 growing seasons at the Crop Research Centre (CRC) farm of Sardar Vallabhbhai Patel University of Agriculture and Technology, Meerut. Various weed control strategies, including the application of pre-emergence and post-emergence herbicides combined with manual weeding, were evaluated for their effectiveness in enhancing the uptake of essential nutrients such as nitrogen (N), phosphorus (P), and potassium (K) by rice, while also reducing nutrient loss to weeds. Among the strategies tested, the combination of Pyrazosulfuron at 150 g active ingredient per hectare (a.i. ha⁻¹) as a pre-emergence herbicide and Penoxsulam at 22 g a.i. ha⁻¹ as a post-emergence herbicide, supplemented with one manual weeding at 40 DAT, proved to be the most effective. This approach resulted in the highest nutrient uptake by rice and the lowest nutrient uptake by weeds. In this treatment, nitrogen uptake in the rice grains reached 62.7 kg per hectare in 2022 and 67.4 kg per hectare in 2023, significantly outperforming other treatments. The weed-free treatment, which involved complete weed eradication, also demonstrated high nutrient absorption, highlighting the importance of thorough weed control for optimal rice growth. Conversely, the untreated weedy check, where no weed control was implemented, led to the highest nutrient uptake by weeds, severely limiting the availability of nutrients for the rice crop. Manual weeding alone, without the use of herbicides, showed moderate effectiveness but was less efficient compared to the integrated approach combining herbicides and hand weeding.