Comparative secretome analysis of Striga and Cuscuta species identifies candidate virulence factors for two evolutionarily independent parasitic plant lineages.

BACKGROUND: Many parasitic plants of the genera Striga and Cuscuta inflict huge agricultural damage worldwide. To form and maintain a connection with a host plant, parasitic plants deploy virulence factors (VFs) that interact with host biology. They possess a secretome that represents the complement of proteins secreted from cells and like other plant parasites such as fungi, bacteria or nematodes, some secreted proteins represent VFs crucial to successful host colonisation. Understanding the genome-wide complement of putative secreted proteins from parasitic plants, and their expression during host invasion, will advance understanding of virulence mechanisms used by parasitic plants to suppress/evade host immune responses and to establish and maintain a parasite-host interaction. RESULTS: We conducted a comparative analysis of the secretomes of root (Striga spp.) and shoot (Cuscuta spp.) parasitic plants, to enable prediction of candidate VFs. Using orthogroup clustering and protein domain analyses we identified gene families/functional annotations common to both Striga and Cuscuta species that were not present in their closest non-parasitic relatives (e.g. strictosidine synthase like enzymes), or specific to either the Striga or Cuscuta secretomes. For example, Striga secretomes were strongly associated with 'PAR1' protein domains. These were rare in the Cuscuta secretomes but an abundance of 'GMC oxidoreductase' domains were found, that were not present in the Striga secretomes. We then conducted transcriptional profiling of genes encoding putatively secreted proteins for the most agriculturally damaging root parasitic weed of cereals, S. hermonthica. A significant portion of the Striga-specific secretome set was differentially expressed during parasitism, which we probed further to identify genes following a 'wave-like' expression pattern peaking in the early penetration stage of infection. We identified 39 genes encoding putative VFs with functions such as cell wall modification, immune suppression, protease, kinase, or peroxidase activities, that are excellent candidates for future functional studies. CONCLUSIONS: Our study represents a comprehensive secretome analysis among parasitic plants and revealed both similarities and differences in candidate VFs between Striga and Cuscuta species. This knowledge is crucial for the development of new management strategies and delaying the evolution of virulence in parasitic weeds.

Continuous mowing differentially affects floral defenses in the noxious and invasive weed Solanum elaeagnifolium in its native range.

In weeds, disturbance has been found to affect life history traits and mediate trophic interactions. In urban landscapes, mowing is an important disturbance, and we previously showed that continuous mowing leads to enhanced fitness and defense traits in Solanum elaeagnifolium, Silverleaf Nightshade (SLN). However, most studies have been focused on foliar defenses, ignoring floral defenses. In this study we examined whether continuous mowing affected floral defenses in SLN using mowed and unmowed populations in South Texas, their native range. We found flowers of mowed SLN plants larger but lighter than unmowed plants. Additionally, flowers on plants that were mowed frequently were both heavier and larger. Mowed plants had higher spine density and consequently unmowed flowers had higher herbivore damage. Additionally, early instar Manduca sexta fed on mowed flower-based artificial diets showed no difference in mass than the control and unmowed; however, later instars caterpillars on unmowed diets gained significantly more mass than the mowed treatment and control. Mowed plants had higher spine density which may shed light on why unmowed flowers experienced higher herbivore damage. We found caterpillars fed on high mowing frequency diets were heavier than those on low mowing frequency diets. Collectively, we show that mowing compromises floral traits and enhances plant defenses against herbivores and should be accounted for in management.

Inhibition of co-occurring weeds and young sugarcane seedling growth by perennial sugarcane root extract.

Allelopathy is a process whereby a plant directly or indirectly promotes or inhibits growth of surrounding plants. Perennial sugarcane root extracts from various years significantly inhibited Bidens pilosa, Digitaria sanguinalis, sugarcane stem seedlings, and sugarcane tissue-cultured seedlings (P < 0.05), with maximum respective allelopathies of - 0.60, - 0.62, - 0.20, and - 0.29. Allelopathy increased with increasing concentrations for the same-year root extract, and inhibitory effects of the neutral, acidic, and alkaline components of perennial sugarcane root extract from different years were significantly stronger than those of the control for sugarcane stem seedlings (P < 0.05). The results suggest that allelopathic effects of perennial sugarcane root extract vary yearly, acids, esters and phenols could be a main reason for the allelopathic autotoxicity of sugarcane ratoons and depend on the type and content of allelochemicals present, and that allelopathy is influenced by other environmental factors within the rhizosphere such as the presence of old perennial sugarcane roots. This may be a crucial factor contributing to the decline of perennial sugarcane root health.

Trade-offs constrain the success of glyphosate-free farming.

Glyphosate, the most widely used herbicide, is linked with environmental harm and there is a drive to replace it in agricultural systems. We model the impacts of discontinuing glyphosate use and replacing it with cultural control methods. We simulate winter wheat arable systems reliant on glyphosate and typical in northwest Europe. Removing glyphosate was projected to increase weed abundance, herbicide risk to the environment, and arable plant diversity and decrease food production. Weed communities with evolved resistance to non-glyphosate herbicides were not projected to be disproportionately affected by removing glyphosate, despite the lack of alternative herbicidal control options. Crop rotations with more spring cereals or grass leys for weed control increased arable plant diversity. Stale seedbed techniques such as delayed drilling and choosing ploughing instead of minimum tillage had varying effects on weed abundance, food production, and profitability. Ploughing was the most effective alternative to glyphosate for long-term weed control while maintaining production and profit. Our findings emphasize the need for careful consideration of trade-offs arising in scenarios where glyphosate is removed. Integrated Weed Management (IWM) with more use of cultural control methods offers the potential to reduce chemical use but is sensitive to seasonal variability and can incur negative environmental and economic impacts.

Culture optimization of Streptomyces sp. KRA16-334 for increased yield of new herbicide 334-W4.

This study aimed to isolate actinomycetes that exhibit strong herbicidal activity, identify compounds active against weeds, and researching methods to improve the production of these compounds through culture optimization to establish a foundation for the development of environmentally friendly bioherbicides. 334-W4, one of the herbicidal active substances isolated from the culture broth of Streptomyces sp. KRA16-334, exhibited herbicidal activity against various weeds. The molecular formula of 334-W4 was determined to be C16H26N2O6, based on ESI-MS (m/z) and 1H and 13C NMR spectral data. It had molecular weight 365.1689 [M+Na] and 343.1869 [M+H], indicating the presence of the epoxy-ß-aminoketone moiety based on HMBC correlations. Additionally, selective culture was possible depending on the addition of trifluoroacetic acid (TFA) during culture with GSS medium. Experiments confirmed that exposure of the KRA16-334 strain to UV irradiation (254 nm, height 17 cm) for 45 seconds improved the yield of the active substance (334-W4) by over 200%. As a result of examining yields of active materials of four mutants selected through optimization of culture conditions such as temperature, agitation, and initial pH, the yield of one mutant 0723-8 was 264.7 ± 12.82 mg/L, which was 2.8-fold higher than that of wild-type KRA16-334 at 92.8 ± 5.48 mg/L.

Effects of soil pH on the growth, soil nutrient composition, and rhizosphere microbiome of Ageratina adenophora.

Ageratina adenophora is an invasive weed species found in many countries. Methods to control the spread of this weed have been largely unsuccessful. Soil pH is the most important soil factor affecting the availability of nutrients for plant and impacting its growth. Understanding the mechanisms of the influence of soil pH on the growth of A. adenophora may help to develop effective control measures. In this study, we artificially changed the soil pH in pot experiments for A. adenophora. We studied the effects of acidic (pH 5.5), weakly acidic (pH 6.5), neutral (pH 7.2), and alkaline (pH 9.0) soils on the growth, availability of soil nutrients, activity of antioxidant enzymes, levels of redox markers in the leaves, and the structure and diversity of the rhizosphere microbiome. Soil with a pH 7.2 had a higher (47.8%) below-ground height versus soils of pH 5.5 at day 10; plant had a higher (11.3%) above-ground height in pH 7.2 soils than pH 9.0 soils at day 90; no differences in the fresh and dry weights of its above- and belowground parts, plant heights, and root lengths were observed in plants growing in acid, alkaline, or neutral pH soil were observed at day 180. Correspondingly, the antioxidant enzymes SOD (superoxide dismutase), POD (peroxidase), CAT (catalase) and redox markers GSH (glutathione) and MDA (malondialdehyde) were measured in the leaves. Significant differences existed in the activities of CAT and the levels of GSH between those growing in acidic and alkaline soils and those in neutral pH soil at day 90; however, only lower (36.8%) CAT activities in those grown at pH 5.5 than those grown at pH 7.2 were found at day 180. Similarly, significant differences in available P (16.89 vs 3.04 mg Kg-1) and total K (3.67 vs 0.96 mg Kg-1), total P (0.37 vs 0.25 g Kg-1) and total N (0.45 vs 1.09 g Kg-1) concentrations were found between the rhizosphere soils of A. adenophora grown at pH 9.0 and 7.2 at day 90; no such differences were seen at day 180. High throughput analyses of the 16S rRNA and ITS fragments showed that the rhizosphere microbiome diversity and composition under different soil pH conditions changed over 180 days. The rhizosphere microbiomes differed in diversity, phylum, and generic composition and population interactions under acid and alkaline conditions versus those grown in neutral soils. Soil pH had a greater impact on the diversity and composition of the prokaryotic rhizosphere communities than those of the fungal communities. A. adenophora responded successfully to pH stress by changing the diversity and composition of the rhizosphere microbiome to maintain a balanced nutrient supply to support its normal growth. The unusual pH tolerance of A. adenophora may be one crucial reason for its successful invasion. Our results suggest that attempts use soil pH to control its invasion by changing the soil pH (for example, using lime) will fail.

A Critical Review of Conventional and Modern Approaches to Develop Herbicide-Resistance in Rice.

Together with rice, weeds strive for nutrients and space in farmland, resulting in reduced rice yield and quality. Planting herbicide-resistant rice varieties is one of the effective ways to control weeds. In recent years, a series of breakthroughs have been made to generate herbicide-resistant germplasm, especially the emergence of biotechnological tools such as gene editing, which provides an inherent advantage for the knock-out or knock-in of the desired genes. In order to develop herbicide-resistant rice germplasm resources, gene manipulation has been conducted to enhance the herbicide tolerance of rice varieties through the utilization of techniques such as physical and chemical mutagenesis, as well as genome editing. Based on the current research and persisting problems in rice paddy fields, research on the generation of herbicide-resistant rice still needs to explore genetic mechanisms, stacking multiple resistant genes in a single genotype, and transgene-free genome editing using the CRISPR system. Current rapidly developing gene editing technologies can be used to mutate herbicide target genes, enabling targeted genes to maintain their biological functions, and reducing the binding ability of target gene encoded proteins to corresponding herbicides, ultimately resulting in herbicide-resistant crops. In this review article, we have summarized the utilization of conventional and modern approaches to develop herbicide-resistant cultivars in rice as an effective strategy for weed control in paddy fields, and discussed the technology and research directions for creating herbicide-resistant rice in the future.

Stereo Vision for Plant Detection in Dense Scenes.

Automated precision weed control requires visual methods to discriminate between crops and weeds. State-of-the-art plant detection methods fail to reliably detect weeds, especially in dense and occluded scenes. In the past, using hand-crafted detection models, both color (RGB) and depth (D) data were used for plant detection in dense scenes. Remarkably, the combination of color and depth data is not widely used in current deep learning-based vision systems in agriculture. Therefore, we collected an RGB-D dataset using a stereo vision camera. The dataset contains sugar beet crops in multiple growth stages with a varying weed densities. This dataset was made publicly available and was used to evaluate two novel plant detection models, the D-model, using the depth data as the input, and the CD-model, using both the color and depth data as inputs. For ease of use, for existing 2D deep learning architectures, the depth data were transformed into a 2D image using color encoding. As a reference model, the C-model, which uses only color data as the input, was included. The limited availability of suitable training data for depth images demands the use of data augmentation and transfer learning. Using our three detection models, we studied the effectiveness of data augmentation and transfer learning for depth data transformed to 2D images. It was found that geometric data augmentation and transfer learning were equally effective for both the reference model and the novel models using the depth data. This demonstrates that combining color-encoded depth data with geometric data augmentation and transfer learning can improve the RGB-D detection model. However, when testing our detection models on the use case of volunteer potato detection in sugar beet farming, it was found that the addition of depth data did not improve plant detection at high vegetation densities.

Acting pre-emptively reduces the long-term costs of managing herbicide resistance.

Globally, pesticides improve crop yields but at great environmental cost, and their overuse has caused resistance. This incurs large financial and production losses but, despite this, very diversified farm management that might delay or prevent resistance is uncommon in intensive farming. We asked farmers to design more diversified cropping strategies aimed at controlling herbicide resistance, and estimated resulting weed densities, profits, and yields compared to prevailing practice. Where resistance is low, it is financially viable to diversify pre-emptively; however, once resistance is high, there are financial and production disincentives to adopting diverse rotations. It is therefore as important to manage resistance before it becomes widespread as it is to control it once present. The diverse rotations targeting high resistance used increased herbicide application frequency and volume, contributing to these rotations' lack of financial viability, and raising concerns about glyphosate resistance. Governments should encourage adoption of diverse rotations in areas without resistance. Where resistance is present, governments may wish to incentivise crop diversification despite the drop in wheat production as it is likely to bring environmental co-benefits. Our research suggests we need long-term, proactive, food security planning and more integrated policy-making across farming, environment, and health arenas.

Synthesis and Herbicidal Activity of 2-(2-Oxo-3-pyridyl-benzothiazol-6-yloxy)hexanoic Acids.

The discovery of a lead compound is fundamental to herbicide innovation, but the limited availability of valuable lead compounds has hindered their development in recent years. By utilizing the structural diversity-oriented inactive group strategy, 3-(2-pyridyl)-benzothiazol-2-one was identified as a promising lead scaffold for herbicides, starting from benzothiazole which is an inactive moiety commonly found in herbicides such as mefenacet, benazolin, benzthiazuron, and fenthiaprop-ethyl. To investigate the structure-activity relationship (SAR) of these chemicals, a series of 2-(2-oxo-3-pyridyl-benzothiazol-6-yloxy)hexanoic acid derivatives (VI01 ∼ VI28) were synthesized through classical nucleophilic SNAr reaction using halogenated pyridines and 6-methoxybenzothiazole-2-one. The chemical structures of all the title compounds were confirmed by NMR and MS analysis. Petri dish assays indicated that many compounds exhibited potent herbicidal activity against both broad-leaf weeds and grass weeds at 1.0 mg/L. The SAR analysis revealed that the presence of a trifluoromethyl group at the 5-position of pyridine is essential for herbicidal activity. Furthermore, carboxylic esters exhibit higher herbicidal activity compared to carboxylic amides and free acids, and the activity decreased with the extension of the carbon chain. The postemergence herbicidal activity of VI03 against 16 species of weeds was tested by pot experiments in a greenhouse. VI03 demonstrated comparable efficacy in controlling broadleaf weeds and superior efficacy in controlling grass weeds compared to carfentrazone ethyl. The present study has unveiled a novel molecular scaffold exhibiting remarkably potent herbicidal activity. These findings are anticipated to provide valuable insights for the advancement of new herbicides and offer an alternative approach for managing resistant weeds.

Draft genome of Brasenia schreberi, a worldwide distributed and endangered aquatic plant.

OBJECTIVES: Brasenia is a monotypic genus in the family of Cabombaceae. The only species, B. schreberi, is a macrophyte distributed worldwide. Because it requires good water quality, it is endangered in China and other countries due to the deterioration of aquatic habitats. The young leaves and stems of B. schreberi are covered by thick mucilage, which has high medical value. As an allelopathic aquatic plant, it can also be used in the management of aquatic weeds. Here, we present its assembled and annotated genome to help shed light on medial and allelopathic substrates and facilitate their conservation. DATA DESCRIPTION: Genomic DNA and RNA extracted from B. schreberi leaf tissues were used for whole genome and RNA sequencing using a Nanopore and/or MGI sequencer. The assembly was 1,055,148,839 bp in length, with 92 contigs and an N50 of 22,379,495 bp. The repetitive elements in the assembly were 555,442,205 bp. A completeness assessment of the assembly with BUSCO and compleasm indicated 88.4 and 90.9% completeness in the Eudicots database and 95.4 and 96.6% completeness in the Embryphyta database. Gene annotation revealed 67,747 genes that coded for 73,344 proteins.

A first survey for herbicide resistant weeds across major maize growing areas in the North Island of New Zealand.

Weeds are increasingly documented with evolved resistance to herbicides globally. Three species have been reported as resistant in maize crops in New Zealand: Chenopodium album to atrazine and dicamba, Persicaria maculosa to atrazine and Digitaria sanguinalis to nicosulfuron. Despite knowledge of these cases, the distribution of these resistant biotypes is unknown. This study aimed to determine the prevalence of known resistant weeds in major maize growing areas in New Zealand, and to pro-actively screen other species for resistance. Weed seeds of broadleaf and grass species were collected from 70 randomly selected maize growing farms in the North Island in 2021-2022. Seeds were grown and treated with herbicides at recommended field rates. Atrazine-resistant C. album were recorded in a third of surveyed farms and nicosulfuron-resistant D. sanguinalis in a sixth. Half of Waikato farms and a quarter of Bay of Plenty farms (no Hawkes Bay or Wellington farms) had atrazine-resistant C. album. Dicamba-resistant C. album were not detected, nor were atrazine-resistant P. maculosa. Nicosulfuron resistant D. sanguinalis was recorded in 19% of Waikato farms, 6% of Bay of Plenty farms and 9% of Hawkes Bay farms (no Wellington farms). Amaranthus spp., Fallopia convolvulus, Persicaria spp., Solanum spp., Echinochloa crus-galli, Panicum spp. and Setaria spp. were not resistant to any of the herbicides tested. Twenty-nine to 52% of maize farms in the North Island are estimated to have herbicide resistant weeds. Resistance is common in maize farms in Waikato and western Bay of Plenty. Resistance is rare in southern regions, with only one instance of nicosulfuron-resistant D. sanguinalis and no resistant C. album. Most annual weeds in maize are not resistant to herbicides; although atrazine resistant C. album is widespread, it is currently controlled with alternative herbicides. Resistant D. sanguinalis appears to be an emerging problem.

Design, Synthesis, and Biological Activity of Novel Phenyltriazolinone PPO Inhibitors Containing Five-Membered Heterocycles.

Protoporphyrinogen oxidase (PPO, EC 1.3.3.4) catalyzes the oxidation of protoporphyrinogen IX to protoporphyrin IX, which is a key step in the synthesis of porphyrins in vivo. PPO inhibitors use protoporphyrinogen oxidase as the target and block the biosynthesis process of porphyrin by inhibiting the activity of the enzyme, eventually leading to plant death. In this paper, phenyl triazolinone was used as the parent structure, and the five-membered heterocycle with good herbicidal activity was introduced by using the principle of substructure splicing. According to the principle of bioisosterism, the sulfur atoms on the thiophene ring were replaced with oxygen atoms. Finally, 33 phenyl triazolinones and their derivatives were designed and synthesized, and their characterizations and biological activities were investigated. The in vitro PPO inhibitory activity and greenhouse herbicidal activity of 33 target compounds were determined, and compound D4 with better activity was screened out. The crop safety determination, field weeding effect determination, weeding spectrum determination, and crop metabolism study were carried out. The results showed that compound D4 showed good safety to corn, soybean, wheat, and peanut but poor selectivity to cotton. The field weeding effect of this compound is comparable to that of the commercial herbicide sulfentrazone. The herbicidal spectrum experiment showed that compound D4 had a wide herbicidal spectrum and a good growth inhibition effect on dicotyledonous weeds. Molecular docking results showed that compound D4 forms a hydrogen bond with amino acid residue Arg-98 in the tobacco mitochondria (mtPPO)-active pocket and forms two π-π stacking interactions with Phe-392. This indicates that compound D4 has stronger PPO inhibitory activity. This indicates that compound D4 has wide prospects for development.

Potential Candidate Molecule of Photosystem II Inhibitor Herbicide-Brassicanate A Sulfoxide.

Brassicanate A sulfoxide, a secondary metabolite of broccoli, exhibited the inhibition of weed growth, but its mechanism of action on weeds remains unclear. To elucidate the mechanism by which brassicanate A sulfoxide suppresses weeds, this study explores the interaction between brassicanate A sulfoxide and the photosystem II D1 protein through molecular docking and molecular dynamics simulations. This research demonstrates that brassicanate A sulfoxide interacts with the photosystem II D1 protein by forming hydrogen bonds with Phe-261 and His-214. The successful expression of the photosystem II D1 protein in an insect cell/baculovirus system validated the molecular docking and dynamics simulations. Biolayer interferometry experiments elucidated that the affinity constant of brassicanate A sulfoxide with photosystem II was 2.69 × 10-3 M, suggesting that brassicanate A sulfoxide can stably bind to the photosystem II D1 protein. The findings of this study contribute to the understanding of the mode of action of brassicanate A sulfoxide and also aid in the development of natural-product-based photosynthesis-inhibiting herbicides.

The complete plastome sequences of invasive weed Parthenium hysterophorus: genome organization, evolutionary significance, structural features, and comparative analysis.

Parthenium hysterophorus, a globally widespread weed, poses a significant threat to agricultural ecosystems due to its invasive nature. We investigated the chloroplast genome of P. hysterophorus in this study. Our analysis revealed that the chloroplast genome of P. hysterophorus spans a length of 151,881 base pairs (bp). It exhibits typical quadripartite structure commonly found in chloroplast genomes, including inverted repeat regions (IR) of 25,085 bp, a small single copy (SSC) region of 18,052 bp, and a large single copy (LSC) region of 83,588 bp. A total of 129 unique genes were identified in P. hysterophorus chloroplast genomes, including 85 protein-coding genes, 36 tRNAs, and eight rRNAs genes. Comparative analysis of the P. hysterophorus plastome with those of related species from the tribe Heliantheae revealed both conserved structures and intriguing variations. While many structural elements were shared among the species, we identified a rearrangement in the large single-copy region of P. hysterophorus. Moreover, our study highlighted notable gene divergence in several specific genes, namely matK, ndhF, clpP, rps16, ndhA, rps3, and ndhD. Phylogenetic analysis based on the 72 shared genes placed P. hysterophorus in a distinct clade alongside another species, P. argentatum. Additionally, the estimated divergence time between the Parthenium genus and Helianthus (sunflowers) was approximately 15.1 million years ago (Mya). These findings provide valuable insights into the evolutionary history and genetic relationships of P. hysterophorus, shedding light on its divergence and adaptation over time.

Synthesis and Evaluation of New Phytotoxic Fluorinated Chalcones as Photosystem II and Seedling Growth Inhibitors.

The development of novel phytotoxic compounds has been an important aim of weed control research. In this study, we synthesized fluorinated chalcone derivatives featuring both electron-donating and electron-withdrawing groups. These compounds were evaluated both as inhibitors of the photosystem II (PSII) electron chain as well as inhibitors of the germination and seedling growth of Amaranthus plants. Chlorophyll a (Chl a) fluorescence assay was employed to evaluate their effects on PSII, while germination experiments were conducted to assess their impact on germination and seedling development. The results revealed promising herbicidal activity for (E)-3-(4-bromophenyl)-1-(4-fluorophenyl)prop-2-en-1-one (7 a) and (E)-1-(4-fluorophenyl)-3-phenylprop-2-en-1-one (7 e). Compounds 7 a and 7 e exhibited a reduction in Chl a parameters associated with performance indexes and electron transport per reaction center. This reduction suggests a decrease in PSII activity, attributed to the blockage of electron flow at the quinone pool. Molecular docking analyses of chalcone derivatives with the D1 protein of PSII revealed a stable binding conformation, wherein the carbonyl and fluorine groups interacted with Phe265 and His215 residues, respectively. Additionally, at a concentration of 100 µM, compound 7 e demonstrated pre- and post-emergent herbicidal activity, resulting in a reduction of the seed germination index, radicle and hypocotyl lengths of Amaranthus weeds.

Remote Sensing Evaluation Drone Herbicide Application Effectiveness for Controlling Echinochloa spp. in Rice Crop in Valencia (Spain).

Rice (Oryza sativa L.) is a staple cereal in the diet of more than half of the world's population. Within the European Union, Spain is a leader in rice production due to its climate and tradition, accounting for 26% of total EU production in 2020. The Valencian rice area covers around 15,000 hectares and is strongly influenced by biotic and abiotic factors. An important biotic factor affecting rice production is weeds, which compete with rice for sunlight, water and nutrients. The dominant weed in Spain is Echinochloa spp., although wild rice is becoming increasingly important. Rice cultivation in Valencia takes place in the area of L'Albufera de Valencia, which is a natural park, i.e., a special protection area. In this natural area, the use of phytosanitary products is limited, so it is necessary to use the minimum amount possible. Therefore, the objective of this work is to evaluate the possibility of using remote sensing effectively to determine the effectiveness of the application of the herbicide cyhalofop-butyl by drone for the control of Echinochloa spp. in rice crops in Valencia. The results will be compared with those obtained by using sterilisation machines (electric backpack sprayers) to apply the herbicide. To evaluate the effectiveness of the application, the reflectance obtained by the satellite sensors in the red and near infrared (NIR) wavelengths, as well as the normalised difference vegetation index (NDVI), were used. The remote sensing results were analysed and complemented by the number of rice plants and weeds per area, plant dry weight, leaf area, BBCH phenological state, SPAD index values, chlorophyll content and relative growth rate. Remote sensing is validated as an effective tool for determining the efficacy of an herbicide in controlling weeds applied by both the drone and the electric backpack sprayer. The weeds slowed down their development after the treatment. Depending on the phenological state of the crop and the active ingredient of the herbicide, these results are applicable to other areas with different climatic and environmental conditions.

Intrarow Uncut Weed Detection Using You-Only-Look-Once Instance Segmentation for Orchard Plantations.

Mechanical weed management is a drudging task that requires manpower and has risks when conducted within rows of orchards. However, intrarow weeding must still be conducted by manual labor due to the restricted movements of riding mowers within the rows of orchards due to their confined structures with nets and poles. However, autonomous robotic weeders still face challenges identifying uncut weeds due to the obstruction of Global Navigation Satellite System (GNSS) signals caused by poles and tree canopies. A properly designed intelligent vision system would have the potential to achieve the desired outcome by utilizing an autonomous weeder to perform operations in uncut sections. Therefore, the objective of this study is to develop a vision module using a custom-trained dataset on YOLO instance segmentation algorithms to support autonomous robotic weeders in recognizing uncut weeds and obstacles (i.e., fruit tree trunks, fixed poles) within rows. The training dataset was acquired from a pear orchard located at the Tsukuba Plant Innovation Research Center (T-PIRC) at the University of Tsukuba, Japan. In total, 5000 images were preprocessed and labeled for training and testing using YOLO models. Four versions of edge-device-dedicated YOLO instance segmentation were utilized in this research-YOLOv5n-seg, YOLOv5s-seg, YOLOv8n-seg, and YOLOv8s-seg-for real-time application with an autonomous weeder. A comparison study was conducted to evaluate all YOLO models in terms of detection accuracy, model complexity, and inference speed. The smaller YOLOv5-based and YOLOv8-based models were found to be more efficient than the larger models, and YOLOv8n-seg was selected as the vision module for the autonomous weeder. In the evaluation process, YOLOv8n-seg had better segmentation accuracy than YOLOv5n-seg, while the latter had the fastest inference time. The performance of YOLOv8n-seg was also acceptable when it was deployed on a resource-constrained device that is appropriate for robotic weeders. The results indicated that the proposed deep learning-based detection accuracy and inference speed can be used for object recognition via edge devices for robotic operation during intrarow weeding operations in orchards.