Mechanical Weed Research Articles

A novel mechanical-laser collaborative intra-row weeding prototype: structural design and optimization, weeding knife simulation and laser weeding experiment

IntroductionThe competition between intra-row weeds and cultivated vegetables for nutrients is a major contributor for crop yield reduction. Compared with manual weeding, intelligent robots can improve the efficiency of weeding operations.MethodsThis study proposed a novel mechanical-laser collaborative intra-row weeding device structure. A slider-crank mechanism size optimization algorithm was proposed, and the correctness of the algorithm was verified by ADMAS software. Finally, the crank and link lengths were determined to be 87 mm and 135 mm, respectively. The resistance of triangular weeding knives with different penetration angles and edge angles in the soil was simulated and analyzed using EDEM software. The simulation results show that the triangular weeding knife with a soil penetration angle of 0 ° and an edge angle of 30 ° encountered the least resistance. In addition, weed control experiments with different powers and lasers were conducted using 200 W NIR and 200 W blue lasers. The experimental results show that the time it took for a 50 W blue laser and a 100 W NIR laser to remove small weeds was approximately between 0.3 and 0.4 s, and the time it took for a 50 W blue laser to remove larger weeds was approximately between 0.5 and 0.6 s. The time it took for 75 W and 50 W NIR lasers to remove weeds was more than 1 s.ResultsBased on the above research results, a prototype of a mechanical-laser collaborative intra-row weeding device was successfully built.DiscussionThis study provides a new idea for the field of intelligent weeding. The simulation and experimental results can provide a reference for the research and development of mechanical weeding and laser weeding equipment.

Effects of weed management on soil metagenomic composition in cultivated chickpea fields

Abstract Non-chemical methods, including mechanical and manual weed management are important for improving crop yields and preserving soil microbial diversity. In Tunisia, chickpea cultivation uses a combination of these methods to suppress weeds. This study aimed to evaluate the impact of weeding practices on chickpea (Cicer arietinum L. cultivar REBHA) yield and soil microbial diversity. Field experiments were conducted at the Technical Center for Biological Agriculture in Essaida, Tunisia, using six plots with manual and no weeding treatments. Chickpea yield was measured, and soil samples were collected for metagenomic analysis. Floristic surveys identified 13 weed species, with Chenopodium album L., Rumex acetosa L., and Urtica dioica L. being the most dominant. Seed yield ranged from 23.2 to 26.2 qls/ha in non-weeded plots and from 25.1 to 30.1 qls/ha in weeded plots, showing an increase in yield (11.75%) with manual weeding.
Soil metagenomics revealed changes in bacterial community composition between the two treatments. The dominant phylum was Pseudomonadota, whose relative abundance increased from 24.88% in non-weeded plots to 34.76% in weeded plots. Alpha diversity indices showed lower species richness and diversity in weeded soils, with 62000 OTUs in weeded plots compared to 43202 OTUs in non-weeded plots. Betaproteobacteria and Alphaproteobacteria exhibited higher OTU counts in weeded soils. The Simpson diversity index was lower in non-weeded soils (0.025) than in weeded soils (0.075), indicating a more irregular microbial distribution in non-weeded plots. Thus, manual weeding improved chickpea yield and altered the soil bacterial community, increasing diversity in key microbial taxa. This study highlights the complex interaction between weed management practices and soil microbial ecosystems, which may influence crop productivity.

Evaluation of mechanical and combined chemical with mechanical weeding in maize (Zea mays L.), soybean (Glycine max (L.) Merr. and winter wheat (Triticum aestivum L.)

Evaluation of mechanical and combined chemical with mechanical weeding in maize (Zea mays L.), soybean (Glycine max (L.) Merr. and winter wheat (Triticum aestivum L.)

Mechanization in Cotton Farming: Addressing Labor Shortages and Enhancing Productivity in India

Cotton is a globally significant crop, playing a vital role in both the agricultural and industrial economy. Cotton is a crucial raw material for the textile and apparel industries, driving international trade and commerce. Its global demand influences market dynamics, trade policies, and economies worldwide. The cotton industry provides livelihoods for millions of people, particularly in developing countries, from farming to manufacturing, making it a key source of employment globally. In India, approximately 59% of the raw material for India's textile industry comes from cotton. However, cotton cultivation is challenged by lower yields and high costs associated with various operations such as sowing, weed management, pest control, and harvesting. Mechanization significantly improves cotton yield and profitability by enhancing efficiency, reducing labor, and enabling the cultivation of larger areas with better resource utilization. Precision tools like seed-cum-fertilizer drills and mechanized planters ensure optimal seed placement and spacing, boosting plant health and yield potential. Additionally, mechanized harvesting reduces labor costs, minimizes harvest losses, and ensures better-quality cotton, leading to higher market returns and overall profitability. The innovative concept of High Density Planting Systems (HDPS) shows great potential for improving yields, particularly in rainfed cotton. This system involves planting five to ten plants per square meter, which enhances yield and is compatible with mechanized operations for seeding, weeding, pest management, and harvesting. The key objective of using improved sowing equipment is to achieve precise seed distribution within the row, facilitating operations like weeding and fertilizing at predetermined distances and depths. Proper seed placement by planters is critical to achieving optimal germination. Implementing efficient mechanical weeders could motivate small-scale farmers, boosting production and reducing poverty. A power weeder, a mechanized tool commonly used for preparing soil beds, offers significant savings in time, labor, and fuel. Furthermore, the adoption of mechanical cotton pickers would help ensure timely harvesting operations, increasing yields and contributing to higher cotton production. India’s low cotton productivity can be attributed to the limited adoption of modern agronomic practices and the low level of mechanization. Embracing these innovations could lead to significant improvements in the cotton sector Cotton pickers and strippers play a vital role in modern, large-scale cotton cultivation by significantly reducing harvesting time and labor costs, making them indispensable for efficient operations. These machines increase productivity by enabling faster harvesting across larger areas, minimizing the reliance on manual labor, which can be costly and scarce. Additionally, they reduce harvest losses and enhance yield by ensuring more cotton is collected with minimal waste. Cotton pickers, being gentler, help preserve fiber quality, while strippers are ideal for bulk harvesting in regions growing lower-grade cotton. Overall, mechanized harvesting ensures timely and efficient cotton collection, improving both yield and quality.

Herbicide‐resistant weed management with robots: A weed ecological–economic model

AbstractThe heavy reliance on herbicides for weed control has led to an increase in resistant weeds in the United States. Robotic weed control is emerging as an alternative technology for removing weeds mechanically using artificial intelligence. We develop an integrated weed ecological and economic dynamic (I‐WEED) model to examine the biophysical and economic drivers of adopting robotic weed management and simulate the optimal timing and intensity of robotic adoption within and across growing seasons. We specify a cohort‐based weed growth model that relates yield damages to effective weed density and treats the susceptibility of weeds to herbicides as a renewable resource that can be regenerated by using mechanical weeding robots, due to a fitness cost that makes resistant weeds less prolific. Compared to myopic weed management which ignores resistance development, forward‐looking management leads to earlier adoption of robots and treating robots as complements instead of substitutes to herbicides. This weed management results in adopting fewer robots, deploying robots on a smaller portion of the land, higher profitability, and lower yield loss in the long run, relative to myopic management. Counterintuitively, myopic management leads to a lower resistance level through its higher robot adoption intensity. We also find that a lower level of initial weed seed resistance and/or a higher fitness cost result in a higher level of resistance because they create incentives for farmers to delay the adoption of robotic weed control. Our analysis shows the importance of jointly considering the interactions between weed ecology and economics in analyzing the incentives and effects of robotic weed management on weed resistance.

The reduction of chemical inputs by ultra-precise smart spot sprayer technology maximizes crop potential by lowering phytotoxicity

Weeding is at the heart of agriculture. Today, using herbicides is unavoidable in conventional agriculture. However, increasing ecological awareness, the need to reduce carbon dioxide emissions, and the pursuit of sustainable food have driven industries and academics to explore new approaches for growing and protecting crops. In this context, smart spot sprayers emerge as a highly innovative alternative to broadcast treatments, which overuse pesticides, and mechanical weeding, which is limited by restrictive application conditions. Using artificial intelligence (AI) for plant recognition and ultra-precise spraying technology, herbicides are applied directly to weeds with minimal overspray, reducing their use by 90% compared to conventional methods. Spot sprayers' narrowly targeted spray limits chemicals' contact with the crop, resulting in low phytotoxicity, preserving natural crop development while maximizing yield potential. In addition, site-specific application increases the selectivity of chemical products artificially, enabling more concentrated mixtures to be used. Also, AI enables the selective application of non-selective molecules, supporting their use in established cultures. These characteristics open new opportunities for effective weed control where the traditional solutions fall short. This publication demonstrates the potential of the ultra-precise smart spot sprayer ARA in weed management in onion and sugar beet crops. Although comparing the overall performance of ARA with other smart spot sprayers on the market cannot be done in this article, this technology's potential in rendering weed management on farms more effective, sustainable, and saving labor without compromising yield is nevertheless indicated.

Design and Experiment of an Inter-Row Weeding Machine Applied in Soybean and Corn Strip Compound Planting (SCSCP)

To address the lack of specialized machinery for the mechanical weeding of SCSCP in the Huang Huai Hai region, this study designs a mechanized inter-row weeding machine for SCSCP. The machine features a reciprocating weeding shovel and an adaptive contouring mechanism for cultivation and soil loosening. This paper details the machine’s principles by analyzing the geometric relationship and mechanical model between the corresponding profiling quantities, which determine the relevant parameters for adaptive contouring to ensure stable operation on undulating ground. Furthermore, by optimizing the design of the weeding shovel’s reciprocating motion mechanism, combining EDEM simulation with the weeding shovel–soil interaction, it has been determined that, at various PTO shaft speeds, the optimal weeding efficacy is achieved with a blade-type weeding shovel structure when operating at a forward speed of 3.5 km/h. Field experiments were conducted with different PTO shaft speeds and weeding depths, using weeding and seedling injury rates as performance indicators. The results showed that, based on the optimal speed, the PTO shaft speed is 760 r/min, the operating depth is 3–5 cm, and the average row weeding rate is 90.4%. The average soybean and corn seedling injury rate is 3.4% and 4.2%, meeting the technical requirements for mechanical weeding.

Driveway Detection for Weed Management in Cassava Plantation Fields in Thailand Using Ground Imagery Datasets and Deep Learning Models

Weeds reduce cassava root yields and infest furrow areas quickly. The use of mechanical weeders has been introduced in Thailand; however, manually aligning the weeders with each planting row and at headland turns is still challenging. It is critical to clear weeds on furrow slopes and driveways via mechanical weeders. Automation can support this difficult work for weed management via driveway detection. In this context, deep learning algorithms have the potential to train models to detect driveways through furrow image segmentation. Therefore, the purpose of this research was to develop an image segmentation model for automated weed control operations in cassava plantation fields. To achieve this, image datasets were obtained from various fields to aid weed detection models in automated weed management. Three models—Mask R-CNN, YOLACT, and YOLOv8n-seg—were used to construct the image segmentation model, and they were evaluated according to their precision, recall, and FPS. The results show that YOLOv8n-seg achieved the highest accuracy and FPS (114.94 FPS); however, it experienced issues with frame segmentation during video testing. In contrast, YOLACT had no segmentation issues in the video tests (23.45 FPS), indicating its potential for driveway segmentation in cassava plantations. In summary, image segmentation for detecting driveways can improve weed management in cassava fields, and the further automation of low-cost mechanical weeders in tropical climates can be performed based on the YOLACT algorithm.

Effectiveness of Weed Control on Two Varieties of Corn (Zea Mays L.) in West Aceh Regency

This research aims to find out which weed control techniques are most effective in suppressing weed growth on corn plants, to find out the interaction of manual, mechanical, and chemical weed control on corn plants, to find out the influence of weed control techniques on the production and growth of corn plants. This research be carried out in West Aceh Regency on corn farming land in the Pante Ceureumen District. The time allocation is from April to June 2014. The research was conducted using a randomized block design with a factorial pattern with two factors being studied. The first factor is the weed control technique (T): no control, manual control, using husk charcoal, chemical, atrazine + mesotrion 1.35 ml each 9 m² and the second factor is the variety (V): Bisi-2 and Bisi-18. Based on the treatment of 12 plots with 3 repetitions times until there are 36 experimental units. Each treatment plot measures 300 cm x 300 cm with a planting distance of 75 cm x 25 cm so that the number of sample plants in each plot is 48 plants and the number of sample plants in each plot is 8 plants. The distance between plots is 50 cm and the distance between replications is 100 cm. The results obtained from observations are analyzed using the F test. If the results obtained from the variance are significantly different at the 5% level. The result of the research that has been carried out is that the most effective control technique in suppressing weed growth in corn plants is found at T5 (chemistry, topramezone + atrazine 1.35 ml each 9 m², at 21, 40, and 56 HST), followed by T2 (culture technique using rice husk charcoal), T4 (Chemical, nicosulfuron + atrazine 1.35 ml each 9 m², at 21, 40, and 56 HST) and T1 (manual, at 21, 40, and 56 HST) have the same position, then T3 (chemistry, atrazine + mesotrione 1.35ml each 9 m², at 21, 40 and 56 HST), and the last position in weed control techniques is WC (without control).

Weed Management with New Generation Herbicides in Rabi Lentil in Sub-mountainous Area of Reasi District

In rabi, 2017–18, a field study was carried out at KVK, Reasi, SKUA&T, Jammu & Kashmir to assess the effectiveness of five herbicides applied alone, in combination with mechanical weeding (MW), or in sequence to study the effects of the herbicides on weed control and production economics of lentil variety L4147 (Pusa Ageti). Three replications of the experiment were conducted using completely randomized block design having six treatments with three replications. The treatments included T1:Weedy check (control), T2: Weed free, T3: Hand Weeding at 30 DAS and 45 DAS (Khurpi), T4: Quizalofop-p-ethyl 5% EC @ 50 g ai /ha at 40 DAS, T:5 Imazethapyr 10% SL at 40 DAS @ 37.5 g ai /ha, T6: Chlorimuron ethyl 25% WP (PPI) @ 4 g ai/ha and T7: Pendimethalin 30% EC (PE) @ 1 kg ai/ha. The most successful approach for controlling weeds, after weed free, was two hand weeding (HAND WEEDING), according to the results. However, at 60 DAS, two hand weedings at 30 DAS and 45 DAS produced the dry matter accumulation and lowest density of all weed species, followed by pendimethalin and Imazethapyr (post-emergence/POE). Under two hand weeding, the highest weed control efficiency of 83% was attained, and this was followed by Imazethapyr at 40 DAS. But under weed-free conditions, the maximum yield (1365 kg /ha) as well as the highest pods per plant (66.07), seeds per pod (1.94) and nodules per plant (8.20) were observed. Two hand weeding was then applied at 25 and 40 DAS. Pendimethalin greatly lowered broad leaved weeds but only moderately controlled grasses and sedges, while it was still better than control when applied alone. In contrast, Imazethapyr significantly suppressed both broad and grasses. When it came to the economic component, two-hand weeding outperformed all other treatments, including control, with the highest net returns, benefit cost ratio (~42294.49 /ha and 2.8), and lowest weed index (2.8). It was discovered that this combined treatment was the most profitable and long-lasting weed control method for lentils.

Impact of mechanical weed control on soil N dynamics, soil moisture, and crop yield in an organic cropping sequence

Mechanical weed control is a major element of weed suppression in organic farming systems. In addition to the direct effect on weed growth, mechanical weeding, such as harrowing or hoeing, is known to induce side effects on several soil- and crop-related properties. In this study, we investigated the impact of mechanical weeding on soil mineral nitrogen (SMN), soil moisture, and crop yield in an organic crop rotation of grass-clover (Lolium multiflorumLam., Trifolium pratense L.), silage maize (Zea mays L.) and winter barley (Hordeum vulgare L.). The experiment was conducted in two consecutive years (2021, 2022), where each crop was grown in each year on a Plaggic Anthrosol with sandy loam in North-West Germany. Two weed control treatments (mechanical: harrowing, hoeing; chemical: herbicide application) were implemented in a randomized block design with four replications. Greater net nitrogen (N) mineralization in maize compared to winter barley were attributed to the incorporation of grass-clover residues before sowing of maize and greater mineralization potential during the maize growing season. Higher weed growth in maize after mechanical weeding resulted in a reduction of up to 47% in SMN content in the topsoil. In barley, no differences in weed suppression were observed between the treatments and only small effects on SMN were determined after mechanical weeding. The soil water content in the mechanically weeded plots was significantly higher at several events in both years and for both crops, which was attributed to increased water infiltration by disrupting the soil crust. Neither crop yield nor N uptake in harvest products was affected by the different treatments.

Screening the Potential f Fungal Derived Bioherbicide in Weed Management

Synthetic herbicides have long been a cornerstone of modern agriculture, providing effective weed control but often at significant environmental and health costs. These chemicals can persist in the environment, leach into groundwater, and harm non-target organisms, including humans. Additionally, the overuse of synthetic herbicides has led to the development of herbicide-resistant weeds, further complicating weed management strategies. In response to these challenges, researchers and farmers alike are increasingly turning to bioherbicides derived from fungi as a sustainable alternative. Fungal bioherbicides harness the natural antagonistic properties of fungi to target weeds. Unlike synthetic herbicides, which are chemically synthesized and often broad-spectrum in action, fungal bioherbicides utilize either the fungi themselves as pathogens or their metabolites to disrupt weed growth. This approach offers several distinct advantages:Target Specificity: Fungal bioherbicides can be highly specific to certain weed species or even to specific stages of weed growth. This specificity reduces collateral damage to non-target plants and organisms, making them particularly suitable for environmentally sensitive areas such as organic farms, riparian zones, and protected ecosystems. Environmental Friendliness: Unlike synthetic herbicides that can persist in the environment and accumulate in soil and water bodies, fungal bioherbicides generally have lower persistence. They degrade more rapidly and often have minimal impact on non-target organisms, thereby preserving biodiversity and ecosystem health. Reduced Risk of Resistance: Synthetic herbicides often face the challenge of herbicide-resistant weeds, which evolve due to continuous and widespread use. Fungal bioherbicides, by contrast, pose a lower risk of resistance development. This is because they typically act through multiple modes of action or biochemical pathways within the weed, making it harder for weeds to develop resistance mechanisms. Research into fungal-derived bioherbicides is actively exploring and harnessing these advantages. Scientists are screening diverse fungal species to identify potent pathogens or metabolites that effectively inhibit weed growth. Moreover, advances in biotechnology and genetic engineering allow for the enhancement of fungal strains to optimize their bioherbicidal properties while ensuring safety and efficacy. One promising example is the use of fungal pathogens like Phomamacrostoma and Colletotrichum truncatum, which have demonstrated efficacy against various weed species including common agricultural weeds like velvetleaf and pigweed. These fungi infect weeds through mechanisms such as spore attachment, penetration of plant tissues, and secretion of phytotoxic metabolites that inhibit weed growth. In addition to their direct impact on weed management, fungal bioherbicides contribute to sustainable agricultural practices by reducing reliance on synthetic chemicals. They align with principles of integrated pest management (IPM) by offering a biological control method that complements cultural and mechanical weed control strategies. Moving forward, continued research and development efforts are essential to refine fungal bioherbicides, optimize application techniques, and expand their practical use in diverse agricultural settings. Challenges such as formulation stability, cost-effectiveness, and regulatory approvals also need to be addressed to facilitate widespread adoption by farmers.

Field observation and verbal exchange as different peer effects in farmers’ technology adoption decisions

AbstractFarmers’ adoption of novel technologies is influenced by other farmers’ behavior, a phenomenon known as peer effects. Although such effects have been studied intensively, the literature does not clearly distinguish between those that result (1) from verbal exchanges with other farmers and (2) from field observations, including the application of technology, its outcomes, and field conditions. We extend existing theoretical concepts and hypothesize that verbal information exchanges and field observations are two types of peer effects. Using data from an online survey of German sugar beet farmers’ application of mechanical weeding from early 2022, we find that the likelihood of adopting mechanical weeding increases across all model specifications by around 26%–28% if at least one adopter is known and by approximately 30%–32% if at least one field is observed. The two types of peer effects complement and reinforce each other in explaining adoption decisions. The effects increase with the number of adopters known and fields observed but decrease with larger distances to the observed fields. The findings can support designing extension services and future peer effects research that should consider the distinction between peer effects arising from verbal exchanges and field observations.

Analysis of the Productivity of Garden Maintenance Work and Efforts to Improve Effective and Efficient Work Procedures

Weeds growing wild among the staple crops cultivated by farmers have become a serious problem and must be immediately controlled, especially in forestry, agricultural and plantation areas. Therefore, practical knowledge is needed about how to manage the problem of weeds that grow undesirable and how to overcome them. Non-chemical weed control is carried out with physical activity. Physical activity carried out by workers while working is a physical workload that will affect their work productivity. The weight or lightness of work done by workers can be measured through direct measurements of human limbs or physique, among others, heart rate, blood pressure, body temperature, sweat rate, consumption of inhaled oxygen and chemical content in the blood. This study aims to identify the use of semi mechanical weed tools and brush cutter as well as analyze the physical workload experienced by workers. The stages and methods of research are carried out by measuring and testing tools in the field based on technical aspects including theoretical work capacity, effective work, field efficiency, fuel consumption, while ergonomic work aspects by measuring workload and fatigue levels directly on the operator's heart rate. From the measurement and calculation of the Increase Ratio of Heart Rate (IRHR), the lowest workload level was obtained with an index of 1.15 and the highest workload level of 1.51.

Theoretical and practical propositions for more sustainable livestock production

A brief review is made of theoretical and practical propositions for more sustainable livestock production (meat and milk). An Organic Livestock Conversion Index (OLCI) was developed to evaluate the level of approximation of Livestock Production Units (LPU) to the organic model. Organic practices such as crop rotation, use of cover crops, mechanical and manual weed control, and recycling of manure reduce soil erosion and pest problems and generally allow for avoiding the use of chemical fertilizers and pesticides, which - along with the substitution of nitrogen fertilizer with legumes and/or manure – reduces energy use in organic systems. Furthermore, practices by LPU contribute to sustainable livestock production by means of minimal use of chemical fertilizers in pastures; adding nutrients to the soil solely by cattle depositing manure during grazing, manual weed control, use of silvopastoral systems, and energy efficiency by the farmers. The approximation of the LPU to organic production, the use of organic practices, Silvopastoral Systems and more energy efficiency demonstrate the potential of organic livestock farms for contributing to more sustainable production as compared to conventional livestock production.

The finger weeder cultivator for intra‐row mechanical weed control: Effects of uprooting force on selected weed species

AbstractMechanical weed control tools are commonly used in the production of many vegetable and field crops. This study aimed to determine the impact of weed species and growth stage on the finger weeder performances and to reveal the relation between root morphology, uprooting force and control efficacy. A one‐month field experiment with two model species, Triticum aestivum L. (grass) and Sinapis alba L. (broadleaf), showed that finger weeder control efficacy was affected by species and growth stage: Finger‐weeder application during the first two growth stages (cotyledon and second leaf) was more effective for S. alba than for T. aestivum (p < 0.0001), but at fourth‐leaf stage values for control efficacy were not significantly different (p = 0.134). In an experiment conducted in pots it was found that, at all three growth stages, the uprooting force required for S. alba was significantly lower than that for T. aestivum (p < 0.0001), indicating a lower anchoring force of the former. Determination of root‐morphology parameters revealed significantly higher root parameters, like length, in T. aestivum than in S. alba at the early developmental stages. Correlation of the control efficacy and uprooting force revealed a 2.5‐N threshold value for effective weed control. Additionally, net‐house and field experiments showed significant differences in the uprooting forces required for 10 different Mediterranean grasses versus broadleaves weed species at all developmental stages. To translate these findings into applicative recommendations, future research should characterize the relationship between the operational factors of this tool and the required uprooting force.

Research on a visual positioning method of paddy field weeding wheels based on laser rangefinder-camera calibration

The positioning of paddy field weeding wheels is of great significance for compensating the operation deviation between the weeding wheel and the seedling row in paddy field mechanical weeding. In this paper, a visual positioning method for determining the three-dimensional coordinates of weeding wheels in the camera coordinate system is proposed. By fixing the laser rangefinder with the weeding wheel, the proposed method converts the positioning of weeding wheels into solving the relative pose relationship between the laser rangefinder and the camera. Then, based on the constraints of the laser spots on the AprilTag calibration plane, a nonlinear optimization model is established to obtain the relative pose parameters. In the experiment, two evaluation indicators were proposed to evaluate the calibration accuracy. The experimental results showed that the proposed visual positioning method of the weeding wheel can reach a mean positioning error of 2.766 mm and a mean pixel error of 7.161 pixels.

Non-chemical weed management: Harnessing flame weeding for effective weed control

The goal of the current study was to create and assess the effectiveness of a hand-pulled ergonomically designed flame weeder. The developed weeder was tested in the field at three operating pressures (20, 30 and 40 Psi) and forward speeds (1.00, 1.25 and 1.50 km/h) to study their effects on plant damage, survival rates, weight preservation rates, weed management effectiveness, soil temperatures, and gas and energy consumption. Thereafter, at optimized values of forward speed and operating pressure, a comparative assessment of flame weeding with traditional methods (mechanical and manual weeding) was done in terms of weed control effectiveness, operational time, energy consumption, and cost of operation. Results showed that the optimal performance of the designed flame weeder was achieved when operated at a speed of 1 km/h and an operating pressure of 40 psi. The survival rate, weight preservation rate, weed control efficiency, change in soil temperature, recovery rate, plant damage, gas consumption, and energy consumption were observed to be 27.3 %, 32.5 %, 91.1 %, 40.74 °C, 8.5 %, 2.2 %, 4.05 kg/h, and 2500.24 MJ/ha, respectively, at optimized values of forward speed (1.00 km/h) and operating pressure (40 Psi). The actual field capacity, field efficiency and operating cost of the flame weeder were 0.0755 ha/h, 94.94 %, and 3620.81 ₹/ha, respectively. Hand weeding had the best level of weed control effectiveness, but it was a laborious, time-consuming process. When compared to manual weeding, flame weeding was 50.42 % cheaper and 94.82 % faster.

Laser weeding: opportunities and challenges for couch grass (Elymus repens (L.) Gould) control

Laser weeding may contribute to less dependency on herbicides and soil tillage. Several research and commercial projects are underway to develop robots equipped with lasers to control weeds. Artificial intelligence can be used to locate and identify weed plants, and mirrors can be used to direct a laser beam towards the target to kill it with heat. Unlike chemical and mechanical weed control, laser weeding only exposes a tiny part of the field for treatment. Laser weeding leaves behind only ashes from the burned plants and does not disturb the soil. Therefore, it is an eco-friendly method to control weed seedlings. However, perennial weeds regrow from the belowground parts after the laser destroys the aerial shoots. Depletion of the belowground parts for resources might be possible if the laser continuously kills new shoots, but it may require many laser treatments. We studied how laser could be used to destroy the widespread and aggressive perennial weed Elymus repens after the rhizomes were cut into fragments. Plants were killed with even small dosages of laser energy and stopped regrowing. Generally, the highest efficacy was achieved when the plants from small rhizomes were treated at the 3-leaf stage.

Impact of Establishment Techniques and Weed Management Strategies on Chemical Properties of Soil in Wet Direct-seeded Winter Rice

Aim: The aim of the experiment was to check the effect of establishment techniques and weed management strategies on chemical properties of soil. Study Design: The design of the experiment was split plot design. Place and Duration of Study: Assam Agricultural University-Assam Rice Research Institute, Titabar, Assam, India, during the sali season of 2022-2023. Methodology: A total of three establishment techniques viz., broadcasting , drum seeding and line sowing in main plot and six different weed management practices namely hand weeding at 20, 40 and 60 DAS , pyrazosulfuron-ethyl @ 30 g/ha at 2 DAS fb bispyribac-Na @ 25 g/ha at 25 DAS, pyrazosulfuron-ethyl @ 30 g/ha at 2 DAS fb mechanical weeding at 40 and 60 DAS, pyrazosulfuron-ethyl @ 30 g/ha at 2 DAS fb bispyribac-Na @ 25 g/ha at 25 and 45 DAS , weed free check and weedy check in sub plot , respectively. Where DAS=Days after sowing and fb=followed by. Results: Results revealed that among various establishment techniques, drum seeding technique resulted in the lowest available nitrogen (237.87 kg/ha), phosphorus (21.67 kg/ha) and potassium (150.15 kg/ha) in the soil, respectively after harvest. Moreover, under various weed management practices, pyrazosulfuron-ethyl @ 30g/ha at 2 DAS fb bispyribac-Na @ 25 g/ha at 25 and 45 DAS showed lowest nitrogen (236.87 kg/ha), phosphorus (21.37 kg/ha) and potassium (149.23 kg/ha) in the soil, respectively after harvest which was next to weed free check. Conclusion: Combined application of drum seeding along with pyrazosulfuron-ethyl @ 30g/ha at 2 DAS fb bispyribac-Na @ 25 g/ha at 25 and 45 DAS can facilitate optimum plant population of crop with dense canopy cover, resulting in higher uptake of essential minerals and nutrients by the crop, enhancing the overall yield of rice while minimizing weed population throughout the growing period.