Weed Management Approaches Research Articles

Influence of Different Nitrogen Levels and Weed Management Practices on Leaf Area Index of Dry Direct Seeded Rice (Oryza sativa L.) Under Temperate Conditions

Dry direct-seeded rice (DDSR) is an increasingly important cultivation method in regions facing water scarcity and labour constraints. Optimizing nitrogen application is instrumental in determining the environmental sustainability and economic feasibility of a farming system, making its management a top priority. In addition, the weed problems in dry direct-seeded rice account for the yield reduction and diminish the market value by reducing the product quality and raising the postharvest cost. Considering this, the present investigation was accomplished at MRCFC, SKUAST-K, Khudwani during Kharif 2022 and 2023. The experiment encircled the employment of four nitrogen levels: 0 kg N ha-1(N0), 60 kg N ha-1 (N1), 120 kg N ha-1 (N2), and 150 kg N ha-1 (N3). Additionally, seven weed management practices were employed encircling Pendimethalin at 1 kg ha-1 (3-4 DAS) + 2,4-D at 0.75 kg ha-1 (20 DAS), penoxsulam at 22.5 g ha-1 (12-15 DAS), Pyrazosulfuron combined with Pretilachlor at 30 g + 0.75 g ha-1 (3-4 DAS), Bensulfuron Methyl combined with Pretilachlor at 30 g + 0.75 g ha-1 (3-4 DAS), and Triafamone combined with Ethoxysulfuron at 40 g + 20 g ha-1 (12-15 DAS). The treatments also included a weedy check and a weed-free control. The experiment was designed in line with the factorial randomized complete block design (RCBD) possessing three replications. The acquired results elucidated a considerable increase in growth attributes such as leaf area index in response to various nitrogen levels as well as weed management approaches. Employment of nitrogen @ 150 kg ha-1 and Triafamone + Ethoxysulfuron (40+20 g ha-1) application, in addition to weed-free treatment, recorded the highest values for Leaf area index during 2022 and 2023.

Sustainable weed management approaches for cultivation of upland rice under Tripura condition

Sustainable weed management approaches for cultivation of upland rice under Tripura condition

Assessing the combined effects of mechanical and chemical weeding on weed dynamics in winter wheat

AbstractMechanical weeding, such as harrowing, offers a promising approach for reaching the European Union's goal of a 50% reduction in pesticide use. To assess its potential, used alone or with foliar‐applied herbicides without residual activity, a 6‐year study was conducted on winter wheat cultivated in loamy soil under temperate conditions (Belgium). Weed density dynamics and percentage weed control (WC) were measured and compared between wheat tillering (BBCH 27‐29) and wheat canopy closure (BBCH 39‐75). Weeds were categorised as weeds maturing generally synchronously with wheat (OW), newly emergent (NE) weeds, or new weed species (NS) appearing in spring. The presence of OW was negatively correlated with yields (up to −0.44), while spring weeds had low or no impact on yield. Overall, one harrow pass reduced OW pressure significantly, with no statistical differences between one versus two passes (the second pass was performed several days after the first). The percentage of WC reached 92%–94% when herbicide was used in combination with harrowing (respectively for one and two harrow passes), and proved to be more effective than harrowing alone whose efficacy reached 64%–70% (respectively for two and one harrow passes). This study also found evidence effects of natural competition from wheat on weeds. Specifically, 54% WC was observed just after harrowing, and 70% was observed when the wheat canopy was closed. These findings suggest that an integrated weed management approach may involve an initial harrowing pass with subsequent evaluation of its effectiveness prior to commencing another intervention. In the event of poor efficacy, a full dose application of herbicide may be warranted.

The Unsung Champions of Evolution: Weeds and Their Management in Agricultural Systems

The history of weeds is closely intertwined with the development of agriculture. As early farmers began to select crops, weeds emerged as formidable competitors, evolving alongside them in a continuous struggle for survival. Over the past 23,000 years, while crops have been bred for human purposes, weeds have continuously adapted, thriving despite rigorous weed management practices. This coevolution highlights the remarkable ability of weeds to evolve rapidly, establishing them as true champions of adaptation. Herbicide resistance, in particular, exemplifies this phenomenon, with weeds developing both target-site resistance (TSR) through genetic mutations and non-target-site resistance (NTSR) through metabolic changes. Often, these mechanisms combine, resulting in heightened levels of resistance, especially within herbicide-resistant crop systems. The evolutionary success of weeds not only underscores their adaptability but also emphasizes their critical role in supporting biodiversity and ecosystem resilience, particularly in simplified agricultural landscapes. This chapter focuses on the evolution of weed management strategies and emphasizes the urgent need to transition to ecologically based weed management (E-bWM) approaches that balance productivity with sustainability, recognizing the ecological value of weeds in fostering resilient agricultural systems.

Pulse crops as effective living mulches: An eco-conscious weed management approach

The evolution of weed management strategies from basic cultural techniques to novel, integrated approaches reflects technological advancements that promise further improvements in weed management strategies, fostering more efficient and eco-friendly farming practices. Using legume crops as living mulches for weed suppression has gained considerable attention in agricultural systems. This method involves strategically planting leguminous cover crops as intercrops to inhibit weed growth and improve soil health, potentially boosting crop yields through reduced weed pressure and enhanced nutrient availability. The successful implementation of living mulches requires careful selection of crop species, optimal planting density, and appropriate management practices. Choosing compatible legumes, optimizing planting geometry and employing suitable termination methods are essential for maximizing the weed-suppressing and soil-enhancing benefits of living mulches. The efficacy of intercropping systems in controlling weeds largely depends on intercrop components' growth rate and duration. Weed management strategies rely on understanding plant interactions, including the competitive ability of main crops at various growth stages to inhibit weed expansion. While intercropping shows promise for enhancing crop dominance over weeds, weed control efficiency varies among different intercrops due to factors affecting the intercrop-weed relationship. Smallholder farmers find this practice appealing for improving labour productivity and land use through intensification and resource utilization for maximum yield. Research on developing genotypes suitable for weed suppression and studies on combined herbicide applications and optimal dosage determination for effective control of mixed weed flora is necessary. The shift towards integrating pulse crops as a cornerstone in weed management strategies presents a promising avenue for research and application. The comparative analysis underscored in this review showcases the capacity of legumes to offer a viable alternative to synthetic herbicides and mechanical controls, paving the way for their increased adoption in diverse farming systems.

Evaluating farmer-driven weed management approaches and their impact on paddy yields in Mahaweli system B

Mahaweli System B in Polonnaruwa, Sri Lanka, lies in the dry zone’s DL1b agro-ecological region and receives an average annual rainfall of 900 mm. Paddy cultivation is the primary livelihood, supported for over 30 years by supplemental irrigation from the Maduru Oya reservoir. Roughly 35,000 farmers grow paddy across 25,000 hectares during both Yala and Maha seasons, contributing 4.2% of the national paddy production each season, with an average yield of 5.1 tons per hectare, surpassing the national average of 3.7 tons per hectare. To improve yields, Mahaweli System B leverages irrigation infrastructure, skilled extension services, collaboration with agricultural organizations, and strong farmer networks. Awareness programs emphasize high-quality seed selection, optimized land preparation, nutrient-specific fertilization, and safe agrochemical use. Despite comprehensive weed control practices, weeds remain a major challenge, reducing yields by 28-89% and impacting harvest quality. This study aims to identify weed management practices adopted by farmers in Mahaweli System B and to evaluate their effectiveness in enhancing paddy yield, providing insights to strengthen regional production outcomes.

Efficient weed segmentation in maize fields: A semi-supervised approach for precision weed management with reduced annotation overhead

The rampant growth of weeds poses a significant threat to agricultural productivity, causing substantial damage to crops and hindering overall yield. With the continuous increase in global food demand, effectively addressing the challenges posed by weeds has become an urgent priority. Currently, the application of deep learning methods has proven effective in handling complex classification problems. Nevertheless, their widespread integration into agriculture is impeded by the labor-intensive and time-consuming nature of data annotation. In contrast, the abundance of readily available unannotated data offers an opportunity to develop potent and precise models without incurring the substantial costs associated with data labeling. This study focuses on the development of a semi-supervised deep learning model capable of acquiring semantic segmentation knowledge from both annotated and unannotated images. The research findings indicate that, even with limited data, the performance of the proposed model approaches or exceeds supervised learning approaches that use a larger dataset. The model exhibits resilience in accurately segmenting weeds in high spatial resolution remote sensing images, achieving a performance of 85.5% mIoU on test data, even in scenarios with intensive weed infestation. By significantly reducing annotation costs, our approach contributes to providing a more efficient and cost-effective solution for weed management in agricultural fields.

Energy efficient weed control in high density planting rainfed cotton

An experiment utilizing a split-plot design was done to ascertain the optimal plant population and weed management strategies for enhancing yield, net income, and energy efficiency in high-density rainfed cotton cultivation. The primary plot treatments comprised three spacing configurations: 100x10 cm, 150x50x10 cm, and 175x50x10 cm. Six weed management approaches were evaluated as subplot treatments, with each treatment replicated three times throughout the 2023-24 rabi season. These practices included power weeding on 20 and 45 days after sowing (DAS), intercropping with black gram, hand weeding on 20 and 45 DAS, herbicide application of Metolachlor (pre-emergence) on 5 DAS, and a combination of Pyrithiobac sodium plus Quizalofop ethyl (post-emergence) on 20 DAS, along with weedy check and weed-free check. The 100 x 10 cm spacing combined with power weeding proved superior, achieving higher yield parameters, greater yield, increased income (Rs. 67238/ha), a benefit-cost ratio of 2.27, energy productivity of 0.38 Kg/MJ, net energy productivity of 30334 MJ/ha, and an energy use efficiency of 4.0 in high-density planting. The narrow-row spacing (100x10 cm) with power weeding also optimized plant population and enhanced per-plant productivity. This configuration also supported proper soil tilling and aeration, enabling a higher uptake of inputs with minimum energy expenditure for weeding, leading to improved overall performance.

Development of Software Interface for AI-Driven Weed Control in Robotic Vehicles, with Time-Based Evaluation in Indoor and Field Settings

Herbicide blanket application is widely practiced by farmers to chemically control weeds in the field, thereby enhancing productivity and improving crop quality. However, their repetitive use also has caused several negative issues on the environment and human health. To overcome these negative issues precision site-specific weed control can be used to reduce the herbicide application by targeted application on only weed areas. Hence, a robotic platform utilizing NVIDIA Jetson embedded device as control and processing unit was developed and tested on lab and field conditions for weed control. The average time taken for data acquisition and artificial intelligence-based computer vision tasks was tested under both lab and field conditions. Moreover, a grid map creation algorithm using YOLOv4 deep learning algorithm was evaluated to control the nozzles of the robotic platform. Integrating all these components together enabled real-time weed management approaches, enhancing the precision and efficiency of herbicide application Independent paired t-tests reveal that there is no significant difference in computational time between lab and field testing. Conversely, independent paired t-test revels that there is significant difference in image size between lab and field testing. The reduction of herbicide application based on grid map was obtained 79 to 80 %, which does not include YOLOv4 algorithm failure and system synchronization failure. The study suggests the importance of field testing for real-time applications of the robotic platform by using deep learning computer vision methods for weed control.

Allelopathy prospective of oil seed crops for sustainable weed management- A review

Weeds are a severe menace to crop cultivation as they interfere with crop growth and development and result in considerable loss in yield of oil seed crops. As a result, farmers have widely used synthetic herbicides for weed management. Using herbicides guides various environmental and health issues, and researchers have been exploring alternative environmentally friendly ways of controlling weeds. Among these, incorporating allelopathy as a tool in an integrated weed management approach could significantly bring down herbicide usage. Allelopathy refers to the influence of one plant on another in its surroundings or on associated microflora/microfauna through the release of allelochemicals that intervene with the growth of plants. In field crops, allelopathy can be applied through intercropping, crop rotation, cover crops, mulching and allelopathic water extracts to manage weeds. Research evidence indicates that oil seed crops possess potent allelo chemicals that have great potential to be utilized as natural herbicides. This review aims to outline oil seed crops allelopathy that releases effective allelo chemicals with the possibility of being used in oil seed crop cultivation. By applying the allelopathy principles, farmers can pursue environmentally friendly and sustainable weed control techniques and improve crop yield and quality.

Evaluation of ALS-Resistant Yellow Nutsedge (Cyperus esculentus) in Georgia Peanut

Abstract Accounting for 53% of United States peanuts (Arachis hypogaea L.), Georgia is the top peanut-producing state with approximately 1.42 billion kg produced in 2023. Peanut producers often use the ALS imidazolinone herbicide imazapic but reduced yellow nutsedge (Cyperus esculentus L.) control was reported in Georgia peanuts after four-years of continuous imazapic use. This study aimed to determine the level of resistance (LD50, I50, and GR50), potential cross-resistance for the suspected resistant population, and identify the associated genetic mutations conferring resistance. A susceptible biotype was treated with 0, 0.0088, 0.0175, 0.035, 0.07, 0.14, 0.28, and 0.56 kg ai ha-1, and a resistant biotype was sprayed with 0, 0.07, 0.14, 0.28, 0.56, 1.13, 2.26, and 4.5 kg ai ha-1 of imazapic. To determine if the suspected resistant biotype was cross-resistant to halosulfuron-methyl, an ALS herbicide used to control nutsedge spp., both biotypes were treated with 0, 0.0117, 0.0233, 0.0466, 0.0933, 0.187, 0.373, and 0.746 g ai ha-1 of halosulfuron-methyl. Plants were rated for injury 7, 14, and 28 days after treatment (DAT), and above-ground biomass harvested at 28 DAT. For imazapic, LD50 was 0.041 and 1.503 kg ai ha-1 and the GR50 was estimated to be 0.0128 and 1.853 kg ai ha-1 for Sus and Res biotypes, respectively, indicating 36 and 145-fold increase in resistance of the Res biotype for I50 and GR50, respectively. Both biotypes responded similarly to applications of halosulfuron-methyl, with biomass reductionat rates greater than 0.023 kg ai ha-1. Transcriptome profiles revealed a mutation in the target-site gene of the resistant biotype, causing an amino acid substitution from Alanine to Valine at position 205 (Ala205Val). Growers should continue to rotate chemistries and implement integrated weed management approaches for control of C. esculentus as the use of imazapic over consecutive years has led to resistance in C. esculentus.

Selection and adaptation to weed management methods: implications for non-chemical and integrated weed management approaches.

Herbicide-resistant weeds are a growing global concern, threatening food security. Non-chemical weed management approaches are becoming increasingly important. Furthermore, the adoption of non-conventional agricultural practices is on the rise, with regenerative farming practices aimed at rebuilding soil organic matter, restoring biodiversity, and reducing chemical use gaining traction. Consequently, non-chemical weed management methods are seen as essential solutions. However, excessive reliance on these methods may inadvertently lead to weed selection and adaptation, reducing their effectiveness. Here, we explore the mechanisms driving changes in efficacy due to selectivity and adaptation to non-chemical weed management practices. Additionally, we discuss potential integrated weed management (IWM) strategies that combine chemical and non-chemical methods to mitigate the risks of weed adaptation. This study highlights the role of evolutionary processes in shaping weed adaptation to non-chemical weed management methods and underscores the need to understand these processes to develop IWM approaches that remain effective over time. Monitoring phenological shifts and adaptations in the field should be a key component of decision support systems, tailored to the unique conditions of each site. Furthermore, a deeper understanding of weed adaptation mechanisms can enhance the efficacy of IWM strategies and help delay the inevitable adaptation to these control methods. © 2024 Society of Chemical Industry.

Influence of cultural and weed management approaches on economics and soil microbial load in brinjal (Solanum melongena L.)

Influence of cultural and weed management approaches on economics and soil microbial load in brinjal (Solanum melongena L.)

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.

Study of Amino Acid-Derived 3-Acyltetramic Acids as Herbicidal Agents.

The growing problem of herbicide resistance necessitates the development of novel herbicidal active ingredients, together with other integrated weed management approaches. Natural products are a major source of inspiration for novel actives. In previous research, we identified a 3-acyltetramic acid of microbial origin that inhibited algal growth in marine biofilms, at least in part through inhibition of photosystem II. In this work, we demonstrate the herbicidal effect of this lead compound and construct multiple libraries to test the impact of the different substituents of the central scaffold in order to study the structure-activity relationships. Among these analogues, the highest activities were found for medium- to long-chain acyl groups and apolar secondary amino acid residues. Finally, we provide first insights into the herbicidal mechanisms and present preliminary field-trial and ecotoxicological results for TA12-Pro, the most active analogue in our library. Together, this research shows the potential of 3-acyltetramic acids for herbicide development.

Exploiting Soybean and Flaxseed Meal Byproducts as Safe Weed Management Approaches in Onion Field

The intensive and repeated use of chemical herbicides has led to the emergence of herbicide-resistant weeds, which, in addition to their environmental impacts, also pose significant threats to human and animal health. This study aimed to explore the potential of oilseed industrial wastes, specifically soybean and flaxseed meals, as safe and environmentally friendly bioherbicides for controlling weeds associated with onion crops. Two field experiments were conducted along two successive winter of 2020/21 and 2021/22. Treatments involved foliar spray of soybean and flaxseed meals in three different concentrations (15, 30 and 45%), mulching of seed meals, oxyfluorfen herbicide, two hand hoeing and untreated weedy check. The findings demonstrated that all weed control treatments significantly reduced weed density, biomass and nutrient uptake. Two hand hoeing, oxyfluorfen herbicide and the mulching of soybean and flaxseed meals alternated in the top rank for weed control, showing minimal significant differences among them. Following these effective treatments, soybean meal extracts at 45 and 30% exhibited notable weed control compared to the weedy check. The greatest enhancement in onion growth, yield characteristics and bulb quality was observed with the application of hand hoeing, soybean and flaxseed meal mulching treatments, with no significant differences between them. High-Performance Liquid Chromatography (HPLC) fractionation of both meals identified various phenolic acids at different concentrations. Practically, these safe efficient treatments proved progress on chemical herbicide. Hence, onion farmers are advised to apply soybean and flaxseed meals mulching safe treatments as alternative to harmful chemical herbicides under all experimental conditions.

New segmentation approach for effective weed management in agriculture

Accurate weed detection in agricultural images is a crucial challenge for improving crop management practices and reducing chemical usage. In this study, we propose an innovative segmentation model called DWUNet, inspired by popular architectures and incorporating the latest advances in the state of the art. Our model delivers remarkable accuracy, with a Jaccard index reaching 0.825, while ensuring fast inference speed of only 8 ms per image, thus providing an optimal solution for real-time applications. By comparing DWUNet to several state-of-the-art models, we demonstrate its superiority in terms of accuracy and efficiency. Furthermore, a qualitative analysis of the visual results confirms DWUNet's ability to accurately detect weeds and generalize results beyond the training data. This study represents a significant advancement in the field of precision agriculture, providing a powerful tool for sustainable crop management and reducing environmental impact.

Early detection and management of herbicide-resistant weeds

Small weed patches may be noticed in fields after herbicide application, but they typically do not have a significant impact on the season’s crop yield. As a result, they are usually not treated as a threat to future yields. However, if these patches harbour weed biotypes resistant to one or multiple herbicides, resistance alleles can spread both spatially (via various dispersal pathways, including seed transport by machinery and commodity contamination) and temporally (through seed persistence). This poses a significant threat to herbicide-based weed management. Once these populations spread and cover a large enough area, eradication becomes improbable despite all the resistance management efforts. Therefore, a proactive and collaborative endeavour is needed to detect and manage small and patchy resistant weed populations. In this paper, we review the current potential of weed resistance detection using imagery and molecular markers as well as possible weed management approaches. Finally, we advocate for the use of a combination of these techniques to manage herbicide-resistant weeds when populations are small. This multifaceted approach is presently not applicable to all resistance mechanisms, and all weed species located in any crop, but could initially focus on biotypes and species that are easy to detect and represent the greatest threat.

Weed Ecology: Insights for Successful Management Strategies: A Review

In crop ecosystems, the primary challenge in establishing a long-term weed management strategy arise from a lack of understanding regarding the nature of weediness and the factors that contribute to species dominance. To address this, farmers and researchers often rely on quick and efficient, yet temporary weed control methods, which can lead to long-term issues. To develop a more effective and sustainable weed management approach, it is crucial to gain a comprehensive understanding of both the biological characteristics and ecological behaviours of weeds. This can be achieved by incorporating preventive techniques, scientific knowledge and management skills, with the goal of enhancing crop production and benefiting farmers. While further information is needed in all aspects of weed management, the primary objective of weed science is to increase our knowledge of weed biology and ecology, thus fostering a better understanding of weediness. This understanding will facilitate the adoption of appropriate management strategies instead of relying solely on short-term solutions that may create or exacerbate long-term problems. The successful growth and reproduction of any species depend on a variety of conditions. In a given ecosystem, the species that can thrive more efficiently under the specific set of environmental conditions will produce the most viable offspring and become the most abundant organisms. Weed ecology, which examines the adaptive mechanisms that enable weeds to thrive in highly disturbed soil conditions, provides essential insights into the distribution and abundance of weeds in both natural and managed systems. The occurrence of a weed in a particular area is influenced by multiple factors, with climatic, soil-related (edaphic) and biotic factors being the most significant among them.

Performance of Various Weed Management Approaches on Weed Dynamics, Yield Attributes and Yield of Puddled Rice under Different Planting Techniques

Background: Rice is a major food source worldwide and direct seeding can shorten crop duration and reduce labour. The system of rice intensification (SRI) can boost yields with fewer inputs. Weed management is crucial for high yields, but chemical herbicides may not be necessary with SRI. A study evaluated herbicide performance based on rice establishment methods. Methods: An field experiment was conducted in January to May, 2021 (Navarai) to find out the efficient weed control techniques in puddled rice. The experiment has been carried out in split-plot design, which included two planting techniques viz., drum seeded rice and system of rice intensification (SRI) in main plot, as well as eight weed control techniques viz., hand weeding, cono weeding, pretilachlor, bispyribac sodium and fenoxaprop - p - ethyl as pre and post emergence application in sub plot. Result: The results of the experiment demonstrated that among the planting techniques and weed management practices tested, the system of rice intensification and sequential application of pretilachlor @ 0.5 kg a.i ha-1 fb bispyribac sodium @ 20 g a.i ha-1 has revealed lowest weed density and highest weed control efficiency, yield attributes and yield and energetics.