Weed Species Research Articles

Cover cropping attenuates population growth of Macrophomina phaseolina by limiting weed biomass, despite asymptomatic colonization of cover crops.

Macrophomina phaseolina is a fungus that causes charcoal rot in strawberry and a wide variety of crop species. Little is known about its potential to asymptomatically colonize crop plants or grow saprophytically on their tissues, both of which would create a potential for alternate, asymptomatic hosts to lead to increases in inoculum. To test the impact of cover cropping on M. phaseolina abundance, we conducted randomized-block field experiments in soils infested by M. phaseolina. None of the fifteen cover crop varieties showed symptoms of charcoal rot. All Fabaceae and Brassicaceae varieties were asymptomatically colonized at varying rates, but among Poaceae, M. phaseolina was recovered from only one individual oat plant. Soil samples collected at the time of planting, tillage, and 8 weeks post-tillage showed that cover cropping attenuated the growth of M. phaseolina relative to fallow plots harboring the weedy legume Medicago polymorpha. This weed species was abundantly colonized by this pathogen in both living root samples and plant residue collected 8 weeks after tillage. Cover cropping also influenced the diversity and composition of bulk soil bacterial and fungal communities, but these effects were not associated with M. phaseolina population density. Although M. phaseolina was not detected in living wheat tissues, it was recovered from wheat residue, suggesting that it may be facultatively saprophytic. These results suggest that cover cropping does not pose a risk for increasing disease caused by M. phaseolina and could be beneficial as conducive weed species, such as M. polymorpha, are suppressed.

Combined hot water extract of lentil and grass pea increase weed control efficiency and yield of boro rice

The agriculture sector is continuously adopting environmentally friendly and sustainable methods to reduce the harmful effects of herbicides on crop production. In this context, an experiment was conducted at the Agronomy Field Laboratory (AFL), Bangladesh Agricultural University (BAU), Mymensingh, from December 2021 to May 2022, to investigate the effect of combined hot water extracts of lentil and grass peas (ELG) on weed control efficiency and yield performance of boro rice. The experiment involved four varieties of boro rice (BAU dhan3, BRRI dhan28, BRRI dhan81, and BRRI dhan96) and four treatments of crop residues. For most weed species, varieties and crop residue extracts significantly impacted weed population (WP) and weed dry weight (DW). The highest numbers of effective tillers (NET) hill-1, numbers of spikelets panicle-1 (NSP), 1000-grain weight (TGW), grain yield (GY), and straw yield (SY) were observed in the three-times hand weeding treatment. This was followed by the combination of hot water ELG applied as a pre-emergence treatment three days after transplanting and post-emergence ten days after transplanting, with the lowest values found in the no-extract treatment. Considering interaction effects, the highest GY (7.07 t ha-1) and SY (8.23 t ha-1) were observed with hand weeding combined with the variety BAU dhan3. The results of this study indicated that hand weeding, followed by the combined application ELG crop residue, showed potential activity to suppress WP and significantly affected the yield of boro rice.

Common cocklebur (Xanthium strumarium L.) interference in grain sorghum [Sorghum bicolor (L.) Moench]: the influence of weed and crop density.

The common cocklebur (Xanthium strumarium L.) is an invasive weed species in the Asteraceae family that probably originated in Central or South America but has now spread worldwide, where it infests numerous crop fields, including sorghum. It is also a significant invasive weed in various parts of Ethiopia, including the eastern region. In this study field experiments were conducted to investigate the effect of various densities of sorghum and X. strumarium on their growth and reproductive output at Haramaya and Babile Research Stations of Haramaya University in Eastern Ethiopia during the 2022/2023 growing seasons. Sorghum yield loss was greatly affected by X. strumarium density, reaching maximum yield losses of 79.2% and 93.1% at the maximum weed density at Haramaya and Babile, respectively. The presence of X. strumarium in sorghum resulted in reduced aboveground dry matter and leaf area index (LAI). The extent of this reduction depended on the density of X. strumarium. As crop density increased, X. strumarium dry matter, LAI, and bur production m-2 decreased. The highest bur production per unit area for X. strumarium was observed at its highest density (16 plants m-2) with 1097 and 869 burs per unit area at Haramaya and Babile, respectively. These results indicated that higher densities of sorghum were effective in suppressing the bur production of this weed, leading to reduced yield loss. Therefore, sorghum competitiveness against X. strumarium can be improved using higher crop densities. This could play a key role in weed management by reducing the use of herbicides and mechanical controls, thereby forming an important part of integrated weed management. © 2024 Society of Chemical Industry.

In Vitro COX Inhibitory Activity, LC-MS Analysis and Molecular Docking Study of Silene vulgaris and Stellaria media.

Silene vulgaris (Moench) Garcke and Stellaria media (L.) Vill is a perennial wild weed species belonging to the Caryophyllaceae family and is widely available and abundant in the environment. The present study has aimed to evaluate the anti-inflammatory potential of two underutilized wild edible plants, Silene vulgaris (Moench) Garcke and Stellaria media (L.) Vill. fractions employing in-vitro COX inhibitory assay. Invitro COX-2 inhibitory potential of MESV and MESM fractions was carried out using BioVisionR "COX Activity Assay Kit (Fluorometric)". LC-MS analysis of selected fractions was conducted to identify bioactive compounds that were further validated for their affinity determination toward target enzymes employing molecular docking studies using the LibDock program. In-vitro COX inhibitory assay revealed that hexane fraction of S. vulgaris (HFSV) and hexane fraction of S. media (HFSM) caused impressive inhibition of COX-2 enzyme with IC50 values 1.38 µg/mL and 1.51 µg/mL respectively. Further, LC-MS analysis revealed the presence of 46 compounds in HFSV and 44 compounds in HFSM respectively. Amongst identified bioactive compounds in HFSV and HFSM, sinapinic acid and syringic acid showed good docking scores with COX-2 i.e., 89.256, and 82.168 respectively. Also, the availability of chrysin in HFSM and rhamnetin in HFSV exhibited good docking scores i.e., 115.092, and 112.341 with a selective affinity towards COX-2. The findings of in-vitro COX Inhibitory Activity and molecular docking studies highlighted the impressive anti-inflammatory properties of S. vulgaris and S. media, and require further investigations to establish them as therapeutic candidates in the management of inflammation and related issues.

Composition and Potential Values of Species in the Agricultural Area of Kupang Indonesia

This research was conducted to investigate the composition and potential value of weeds species in an agricultural area of Kupang, Indonesia. Two sites (dry and wet site) were selected subjectively. In each site, three stands (100 m x 100 m) were placed subjectively and in each stand 25 plots (1 m x 1 m) were placed randomly (∑150 plots). In each plot, all weed present were recorded and their density and percentage cover calculated. Each species was grouped into broad-leaves, sedges, and grasses. To determine the potential value of the weeds, all weeds were grouped into whether they medicinal plants, animal feed or food ingredients. For each species, the number of individuals, dominance, frequency, and Importance Value Index (IVI) were calculated. Species diversity was also calculated using the Shannon-Wienner Diversity Index (H'). Overall, 46 weed species were found. The weeds with the highest IVI (>5.00%) were Panicum repens L (IVI 14.80%), Bolboschoenus maritimus L. Palla (IVI 10.32%), Alternanthera sessilis L (IVI 7.47%), Cyperus rotundus L, (IVI 6.97%), Digitaria ciliaris (IVI 6.69%), Cyperus elatus L (IVI 6.63%), and Ischaemum timorense Kunth (IVI 5.02%). In general, the composition of weeds between the dry and the wet sites were relatively different. Based on the number of species and diversity index, the weed community in the wet site was relatively higher than that in the dry site. Based on the IVI, the dry site tended to be dominated by grasses and broad leaves while the wet site tended to be dominated by sedges. Based on IVI, 42.80% of all the weed species present had the potential to be used as medicinal plants, 39.81% as animal feed, and 17.39% as human food. Overall, most weed species studied had the potential to be used as medicinal plants, animal feed, and food ingredients. The potential of this weed needs to be studied more deeply in the future, including their use as an alternative source of medicine and food, especially as demand increases in the future.

Weed Control and Physiological Responses in Poplar Plantations: Assessing Glyphosate’s Impact

The presence of weeds and changes in temperature and precipitation due to global climate change can negatively affect the growth, development, and adaptation of poplars to new places. Experiments were conducted at the Experimental Estate of the Institute of Lowland Forestry and Environment to test glyphosate’s efficacy and phytotoxicity and to assess the impact of glyphosate on physiological parameters in different stages of poplar plantations. A test with glyphosate was set up by a random block system with four replications at three localities, each characterized by different physical soil properties. Glyphosate efficacy was evaluated after 15 and 30 days, while phytotoxicity was evaluated according to the EWRC scale. Net photosynthesis (A), stomatal conductance (gs), transpiration rate (E), and intercellular CO2 concentration (Ci) were measured, and water use efficiency (WUE) was computed. Annual and perennial broadleaf weeds, grasses, and woody shrubs and bushes were identified. The dominant weed species across all poplar plantations were Solidago gigantea L., Solidago speciosa L., and Poa pratensis L. Glyphosate was highly effective against the major weed species, with the total efficacy ranging from 94.29 to 97.67%. The results showed significant differences in all observed gas exchange parameters, except for transpiration rate (E), between the different-aged poplar plantations. The younger poplars showed lower gas exchange rates in the treatment under the environmental conditions of the studied sites. Weed suppression resulted in altered microhabitats for poplar development at various ages, causing variation in the physiological parameters compared to the control.

Phytosociological Study of Weed Communities in Zea Mays Cultivation: Contributions to Sustainable Development Goals (SDG'S) in the Ecuadorian Tropics

Objective: This study investigates the phytosociological characteristics of weed communities associated with Zea mays cultivation in different zones of the Ecuadorian tropics, aiming to identify and classify weeds to develop effective management strategies that enhance productivity while minimizing environmental impacts Theoretical Framework: The research is based on the concept that weeds, or 'noxious weeds,' significantly challenge maize cultivation by competing for essential resources. Theories related to plant competition and agroecosystem sustainability underpin the study Method: The methodology involves a phytosociological survey across five farms in Mocache, Ventanas, and Balzar. Using 45 quadrats of 50 x 50 cm in a zigzag pattern across one-hectare plots, weed species were identified and quantified. Data were analyzed to calculate biodiversity and importance value indices. Results and Discussion: Mocache had the highest weed population, while Balzar exhibited greater species diversity. Similarity indices, including Jaccard and Bray-Curtis, revealed distinct patterns in species distribution and dominance. These findings are discussed in the context of sustainable agriculture, highlighting the implications for weed management and acknowledging potential limitations due to environmental variability. Research Implications: The study provides insights into sustainable weed management in maize agroecosystems, contributing to strategies aligned with SDG 2 (Zero Hunger) and SDG 15 (Life on Land), promoting practices that enhance food security and biodiversity conservation. Originality/Value: This research offers a novel phytosociological analysis of weed communities in tropical maize cultivation, contributing to sustainable agriculture and aligning with global sustainability goals.

Colchicine, Caffeine, Gramine, and Their Derivatives as Potential Herbicides, Fungicides, and Insecticides.

A preliminary in silico screening of 94 compounds, including colchicine, caffeine, gramine, and their derivatives, was conducted to identify potential herbicides, insecticides, and fungicides. Among the compounds tested, only gramine and its 13 derivatives exhibited potential activity. These compounds were further tested against eight species of insects, three species of weeds, and four species of fungi. All of the tested alkaloids were found to be ineffective as herbicides and insecticides, but they did exhibit some fungicidal activity. Four gramine derivatives showed some activity against Phytophthora infestans, Botrytis cinerea, Zymoseptoria tritici, and Fusarium culmorum.

Allelopathic Activity of Leaf Wastes of Liriodendron tulipifera for Sustainable Management

Logging operations of Liriodendron tulipifera L., as timber trees, and fallen leaves in autumn from ornamental trees produce a large amount of leaf waste. In this study, the allelopathy of L. tulipifera fresh and fallen leaves was investigated for the development of potential applications of leaf waste. The extracts of fresh and fallen leaves of L. tulipifera showed growth inhibitory activity against weed species, Vulpia myuros (L.) C.C.Gmel., Echinochloa crus-galli (L.) P.Beauv., and Lolium multiflorum Lam., under laboratory conditions. The powder of L. tulipifera fresh and fallen leaves also inhibited the germination of E. crus-galli under greenhouse conditions. A potent allelochemical was isolated from fresh and fallen leaf extracts through a bioassay-guided separation process, and was identified as lipiferolide. Lipiferolide inhibited the growth of L. multiflorum and Lepidum sativum in a concentration-dependent manner. This investigation suggests that the leaf waste of L. tulipifera from logging operations and fallen leaves is potentially useful for the purpose of weed control, such as through the use of soil additive materials from leaves or the creation of foliar spray from leaf extracts. The development of weed control materials using L. tulipifera leaf waste may be a means with which to minimize waste, reducing environmental impacts and economic concerns.

Algorithm for Locating Apical Meristematic Tissue of Weeds Based on YOLO Instance Segmentation

Laser technology can be used to control weeds by irradiating the apical meristematic tissue (AMT) of weeds when they are still seedlings. Two factors are necessary for the successful large-scale implementation of this technique: the ability to accurately identify the apical meristematic tissue and the effectiveness of the localization algorithm used in the process. Based on this, this study proposes a lightweight weed AMT localization algorithm based on YOLO (look only once) instance segmentation. The YOLOv8n-seg network undergoes a lightweight design enhancement by integrating the FasterNet lightweight network as its backbone, resulting in the F-YOLOv8n-seg model. This modification effectively reduces the number of parameters and computational demands during the convolution process, thereby achieving a more efficient model. Subsequently, F-YOLOv8n-seg is combined with the connected domain analysis algorithm (CDA), yielding the F-YOLOv8n-seg-CDA model. This integration enables the precise localization of the AMT of weeds by calculating the center-of-mass coordinates of the connected domains. The experimental results indicate that the optimized model significantly outperforms the original model; the optimized model reduces floating-point computations by 26.7% and the model size by 38.2%. In particular, the floating-point calculation is decreased to 8.9 GFLOPs, and the model size is lowered to 4.2 MB. Comparing this improved model against YOLOv5s-seg and YOLOv10n-seg, it is lighter. Furthermore, it exhibits exceptional segmentation accuracy, with a 97.2% accuracy rate. Experimental tests conducted on five different weed species demonstrated that F-YOLOv8n-seg-CDA exhibits strong generalization capabilities. The combined accuracy of the algorithm for detecting these weeds was 81%. Notably, dicotyledonous weeds were detected with up to 94%. Additionally, the algorithm achieved an average inference speed of 82.9 frames per second. These results indicate that the algorithm is suitable for the real-time detection of apical meristematic tissues across multiple weed species. Furthermore, the experimental results demonstrated the impact of distinctive variations in weed morphology on identifying the location of the AMT of weeds. It was discovered that dicotyledonous and monocotyledonous weeds differed significantly in terms of the detection effect, with dicotyledonous weeds having significantly higher detection accuracy than monocotyledonous weeds. This discovery can offer novel insights and avenues for future investigation into the identification and location of the AMT of weeds.

Efficacy of Saflufenacil for Dry Bean and Annual Weed Desiccation

The efficacy of saflufenacil for desiccating dry bean and annual weeds may be influenced by application rate, single or sequential applications, adjuvant selection and rate, and water carrier volume. Five field experiments were conducted from 2021 to 2023 near Exeter and Ridgetown, Ontario, Canada to evaluate the efficacy of saflufenacil applied at two rates, applied once or sequentially, with four adjuvants at various rates, and three water carrier volumes for desiccating dry bean and common weed escapes in Ontario dry bean production. Saflufenacil (25 g ai ha-1) + Merge (1.0 L ha-1) applied with a 200 L ha-1 water carrier volume desiccated dry bean 96, 100, and 100% at 5, 8, and 14 days after application (DAA), respectively; there was no improvement in dry bean desiccation by increasing the rate of Merge to 2.0 L ha-1 or with a sequential application. With saflufenacil (50 g ai ha-1) + Merge (1.0 L ha-1), there was no impact on dry bean desiccation with water carrier volumes of 100, 200, or 300 L ha-1. Dry bean desiccation with saflufenacil (50 g ai ha-1) plus the adjuvants Merge, MSO, AMS, or Merge + AMS was similar. Sequential applications of saflufenacil (25 g ai ha-1) applied twice at a 1-week interval did not improve dry bean desiccation. For weed species desiccation, saflufenacil + Merge desiccated green pigweed (38-100%) and common ragweed (65-96%) most effectively. However, it was less effective on common lambsquarters (0-48%), barnyardgrass (9-24%), and green foxtail (6-14%), with no significant effect of saflufenacil rate, adjuvant selection, adjuvant rate, single vs sequential application, or water carrier volume. This study highlights the potential and limitations of saflufenacil for desiccating dry bean and common weed escapes in Ontario dry bean production.

Deep learning for image-based detection of weeds from emergence to maturity in wheat fields

Effective weed control in wheat (Triticum aestivum L.) fields is crucial for optimizing production and ensuring food security in semi-arid regions. The implementation of deep learning for weed detection could enable precise weed management, leading to enhanced wheat yield, increased income for growers through targeted herbicide use, and a reduced environmental footprint associated with herbicide application. Charlock mustard (Sinapis arvensis L.) [CM], creeping thistle (Cirsium arvense (L.) Scop) [CT], and forking larkspur (Consolida regalis Gray) [FL]) are among the most invasive weed species in wheat fields. Effective management of these weeds is essential to ensure optimal wheat productivity in the semi-arid regions. To detect weeds, an unmanned arial vehicle was used to collect images and videos from 185 wheat fields in Tokat, Turkey. The images were collected from five phenological periods of each species including seedling, rosette, vegetative, flowering, and fruiting (in total 15 classification process). These stages are either important for timely weed control or essential for understanding weed pressure threshold, the potential for increasing weed seedbank increase, and identifying herbicide resistant weeds. A total of 145,792 objects were labeled in the images to create the dataset, divided into 80 % for training + validation and 20 % for testing. The dataset was used with the YOLOv5 (You Only Look Once) deep learning architecture. The YOLOv5 was the newest YOLO model during this study carried out. All neural networks provided by YOLOv5 (nano, small, medium, large, and xlarge) were trained and the Precision, Recall, F-1 Score, and AUC (Area under the Curve) performances of the neural networks were evaluated. The YOLOv5s (small) was the most precise neural network in detecting weeds regardless of the species. In contrast, nano was the least precise neural network in detecting each weed species. For CT, when small neural network was used, precision of detection ranged from 0.87 (fruit stage) to 0.96 (rosette and vegetative stages). For, forking larkspur, the best neural network was achieved with YOLOv5 small and the precision ranged from 0.45 (fruit stage) to 0.93 (vegetative stage). Using YOLOv5 small in Charlock mustard, the most precise detection occurred at seedling, rosette, and vegetative stages (with precision of 0.96) and the least precise detection was recorded at the fruit stage (0.81). Other performance evaluations (Recall, F-1 Score, and AUC) were in agreement with those of Precision. Our results indicated that by using YOLOv5 small neural network, all three weed species could be detected at all growth stages with the precision of 0.86 with the exception of fruit stage. Future research should (1) focus on assessing YOLOv5 small neural network with the newest versions of YOLO and also (2) evaluate this neural network for detecting weed species in wheat fields to allow for improved weed control and future recommendations.

Ecological Impact and Invasiveness of Alien Weed Species in Moradabad District

Ecological Impact and Invasiveness of Alien Weed Species in Moradabad District

Fertility and tillage intensity affect weed community diversity and functional structure in long-term organic systems.

Knowledge of how agricultural management interacts with weed seed banks and emergent weed communities is crucial for proactive weed management. Though studies have detailed how differences in disturbance and nutrient applications between organic and conventional herbicide-based systems affect weed communities, few have focused on these same factors in contrasting organic systems. This study assessed the seed banks and emergent weed communities from the most recent crop rotation cycle (2017-2022) of a long-term experiment, which compared four organic grain and forage cropping systems differing in nutrient inputs and soil disturbance. The high fertility (HF) system received high-rate nutrient applications, low fertility (LF) received low-rate applications, enhanced weed management (EWM) focused on weed control through frequent soil disturbance, and reduced tillage (RT) prioritized soil health with less intense or frequent soil disturbance. Soil samples for greenhouse germination assays were collected at the beginning (2017) and end (2022) of the rotation to explore how these four systems influenced seed bank dynamics over time. Weed community biomass was also sampled in each crop during this time. Treatment effects on weed abundance, taxonomic diversity, and community-weighted means and functional dispersion of weed traits were analyzed with generalized mixed-effect models. The RT system had the highest weed seed bank taxonomic diversity, and EWM had the lowest. RT and LF had higher functional dispersion of traits than HF in the seed bank. Weed seed bank communities in HF and RT were characterized by short, small-seeded, and early germinating weed species. However, seed banks were also labile: Differences between systems in seed density and all other mean trait values were dependent on the crop, which preceded seed bank sampling. Likewise, differences among emergent weed communities in the four systems depended on an interaction between crop species and their planting year. Results suggest that resource availability and intensity of disturbance act as weed community assembly filters in organic cropping systems. Organic growers seeking to design systems that balance weed management and production goals can use relatively low soil disturbance and nutrient application to increase weed community taxonomic or functional diversity without necessarily increasing weed biomass or seed bank density.

Evaluation of phytotoxic potential in Asteraceae plant extracts for biological control of Echinochloa crus-galli and Echinochloa colona.

This study evaluates the phytotoxic potential of methanolic extracts from six Asteraceae species: Wedelia chinensis, Helianthus annuus, Cosmos bipinnatus, Tagetes erecta, Tithonia diversifolia, and Zinnia elegans. The extracts were tested at concentrations of 0.03, 0.1, 0.3, and 1.0 g/mL to assess their inhibitory effects on the radicle and hypocotyl lengths of Echinochloa crus-galli and Echinochloa colona. The two most potent species, C. bipinnatus and T. diversifolia, were further evaluated using extracts from their roots, stems, and leaves. Among these, C. bipinnatus leaf extracts showed the most significant phytotoxicity and were tested at 20, 40, and 60 days of plant age. At 0.03 g/mL, C. bipinnatus extract inhibited the hypocotyl and radicle lengths of E. colona by 23.01% and 56.45%, and E. crus-galli by 8.5% and 36.35%, respectively. At 1.0 g/mL, the extract inhibited the hypocotyl lengths of E. colona and E. crus-galli by 97.54% and 88.15%, and the radicle lengths by 93.52% and 99.99%, respectively. The 60-day-old C. bipinnatus leaf extract exhibited the highest inhibitory effect, correlating with the identification of key allelochemicals such as cinnamic acid, caffeic acid, coumaric acid, ferulic acid, 2-4 dimethohydroxy benzoic acid, and salicylic acid. These findings suggest that the 60-day-old C. bipinnatus leaf extracts have strong potential for use in the biological control of these weed species, offering a promising avenue for the development of natural herbicides.

Diversity and Life History Traits of Native Weed Communities in Agricultural Areas: A Case Study in Eastern China.

Native weeds have a long history of adaptation to local environments. Understanding the relationship between the occurrence of native weeds and their life history traits is crucial for effective weed management and risk assessment of plant invasions. In this study, we surveyed native weed species and their dominance across 666 field sites in agricultural areas of Yangzhou City, China, and each site was 13.3 hectares in area. A total of 287 native weed species were recorded, referring to 63 families, among which 45% were 50-100 cm in plant height and 47% were of an erect life type. In terms of the proportions out of the total native weed occurrence dominance, Poaceae, Compositae, and Fabaceae weeds accounted for 30%, 13%, and 11%; liana and perennials both occupied 32%; and aquatic, hygrophyte, sun plant, and shade plant all occupied < 10%. Additionally, the proportions increased with increasing seed production per plant and with increasing weediness reported worldwide. Native weed groups holding moderate vegetative reproduction abilities, moderate seed sizes, or herbicide resistance showed higher proportions. Moreover, most of the native weeds surveyed were not succulent or thorny plants and did not hold thorns, awns, obvious hairs, or mucilage on their fruits.

Real-time lettuce-weed localization and weed severity classification based on lightweight YOLO convolutional neural networks for intelligent intra-row weed control

Competition for nutrients between intra-row weeds and cultivated vegetables is a major contributor to reduced crop yields. Compared with manual weeding, intelligent robots can improve the efficiency of weeding operations. Developing real-time and reliable robotic systems for weed control in vegetable fields is a significant challenge due to the complexity of real-time identification, localization, and classification of vegetables as well as various weed species. The main purpose of this study was to propose a high-performance, lightweight deep learning model and an intra-row weed severity classification algorithm for real-time lettuce identification and weed severity classification. In this study, a scaling factor (τ = 0.5) was chosen to lightweight the YOLOv7 model. A new Multimodule-YOLOv7-L lightweight model was then developed by combining ECA and CA attention mechanisms, ELAN-B3 and DownC modules. The overall performance of the Multimodule-YOLOv7- L was better than that of other deep learning models, including YOLOv7, YOLOv7-Tiny, YOLOv8m, YOLOv5n-Cabbage, SE: YOLOv5x, YOLOv5s_Ghb, MST-YOLO_CBAM, Citrus-YOLOv7, Pineapple-YOLOv7, MS-YOLOv7 and CBAM-YOLOv7. The precision, recall, mAP@0.5, F1-score, model weight and FPS of the Multimodule-YOLOv7- L model were 97.5 %, 95.7 %, 97.1 %, 96.6 %, 18.4 MB and 37.3 FPS (Image resolution about 3000 × 3000), respectively. An intra-row weed severity classification algorithm based on the Multimodule-YOLOv7-L model was proposed for use in a new mechanical-laser collaborative intra-row weeding robot. The developed algorithm achieved a classification accuracy of 100 % in eight lettuce weed scenarios, with the processing time of a single image ranging from 4-13 ms. The results of this study provided valuable reference for the development of intelligent robots for intra-row weed control. The algorithm proposed in this article can be obtained at https://github.com/H777R/The-intra-row-weed-severity-classification-algorithm.git.

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&amp;T, Jammu &amp; 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.

Discovering Novel Bioherbicides: The Impact of Hemp-derived Phytocannabinoid Applications on Zea mays L. and Relevant Weeds

In addition to competition, phytotoxic plant metabolites contribute to the weed-suppressing properties of cover crops, which could be the basis for the development of novel bioherbicides. We investigated the impact of five Cannabis sativa L. -derived neutral phytocannabinoids and an aqueous C. sativa tissue extract (HE) at six concentrations on the germination rate (GR) and seedling root length (RL) of Zea mays L., two monocotyledonous and two dicotyledonous weed species in laboratory Petri dish bioassays. Additionally, the effect of pre-emergence applications of HE, cannabidiol (CBD), and cannabidivarin (CBDV) formulations on GR and shoot dry matter (SDM) were examined in greenhouse pot studies. The effects of phytocannabinoids and HE were analyzed in dose-response curves. For the highest rates, the effects on GR, RL and SDM were calculated by ANOVA and HSD test (p < 0.05). HE exhibited the greatest suppression on GR and RL for all plant species in the Petri dish bioassay, with RGR, RL exceeding −90%. Phytocannabinoids reduced mainly RL of all plants and decreased the GR of most weed species. Effects varied among plants and phytocannabinoids, with CBDV and CBD showing similar high inhibitory effects on RL as HE in the Petri dish bioassay. All pre-emergence applications resulted in a positive RGR across all studied plants and in a positive RSDM in Z. mays and Echinochloa crus-galli (L.) P. Beauv, whereas in the other weed species the RSDM was negative. In conclusion, phytocannabinoids play a major role in weed suppression of HEs. CBDV and CBD are the most promising candidates for bioherbicide development especially against annual dicotyledonous weed species.

Resistance to acetyl-CoA carboxylase (ACCase)-inhibiting herbicides in Lolium multiflorum Lam. populations of Argentina.

Italian ryegrass (Lolium multiflorum Lam.) is one of the most troublesome grass weeds in Argentina. The extensive and repetitive use of acetyl-CoA carboxylase (ACCase)-inhibiting herbicides has induced resistance in this weed species. The objectives of this study were to quantify the resistance levels to ACCase-inhibiting herbicides in two resistant populations and to identify the target-site mutations associated with their resistance. Two resistant Italian ryegrass populations, Roldán and H2, were studied. Roldán was a suspected haloxyfop-resistant population, located in a wheat field from Santa Fe province with a history of ACCase-inhibiting herbicide use. The H2 population was obtained from the susceptible Hernandarias population (H0) after two cycles of selection with the herbicide quizalofop-ethyl. Whole-plant dose-response assays revealed that the resistant populations exhibited a high resistance to haloxyfop, with resistance factors (RF) exceeding 97-fold. Additionally, both populations showed a moderate resistance to pinoxaden (RF > 7), while maintaining susceptibility to clethodim. Partial chloroplastic ACCase sequences revealed isoleucine-to-asparagine substitution at position 2041 (Ile-2041-Asn) in both resistant populations. This work provides a better understanding of cross-resistance to ACCase-inhibiting herbicides in L. multiflorum populations and represents the first report of the target-site mutation Ile-2041-Asn conferring resistance in populations from Argentina. © 2024 Society of Chemical Industry.