Rice Bacterial Blight Research Articles

Pathogen-induced methylglyoxal negatively regulates rice bacterial blight resistance by inhibiting OsCDR1 protease activity

Xanthomonas oryzae pv. oryzae (Xoo) causes bacterial blight (BB), a globally devastating disease of rice (Oryza sativa) that is responsible for significant crop loss. Sugars and sugar metabolites are important for pathogen infection, providing energy and regulating events associated with defense responses; however, the mechanisms by which they regulate such events in BB are unclear. As an inevitable sugar metabolite, methylglyoxal (MG) is involved in plant growth and responses to various abiotic stresses, but the underlying mechanisms remain enigmatic. Whether and how MG functions in plant biotic stress responses is almost completely unknown. Here, we report that the Xoo strain PXO99 induces OsWRKY62.1 to repress transcription of OsGLY II genes by directly binding to their promoters, resulting in overaccumulation of MG. MG negatively regulates rice resistance against PXO99: osglyII2 mutants with higher MG levels are more susceptible to the pathogen, whereas OsGLYII2-overexpressing plants with lower MG content show greater resistance than the wild type. Overexpression of OsGLYII2 to prevent excessive MG accumulation confers broad-spectrum resistance against the biotrophic bacterial pathogens Xoo and Xanthomonas oryzae pv. oryzicola and the necrotrophic fungal pathogen Rhizoctonia solani, which causes rice sheath blight. Further evidence shows that MG reduces rice resistance against PXO99 through CONSTITUTIVE DISEASE RESISTANCE 1 (OsCDR1). MG modifies the Arg97 residue of OsCDR1 to inhibit its aspartic protease activity, which is essential for OsCDR1-enhanced immunity. Taken together, these findings illustrate how Xoo promotes infection by hijacking a sugar metabolite in the host plant.

Development of Spectral Features for Monitoring Rice Bacterial Leaf Blight Disease Using Broad-Band Remote Sensing Systems

Development of Spectral Features for Monitoring Rice Bacterial Leaf Blight Disease Using Broad-Band Remote Sensing Systems

Rice transcription factor OsNAC2 maintains the homeostasis of immune responses to bacterial blight.

Rice (Oryza sativa) bacterial blight, caused by Xanthomonas oryzae pv. Oryzae (Xoo), threatens plant growth and yield. However, the molecular mechanisms underlying rice immunity against Xoo remain elusive. Here, we identified a NAC (NAM-ATAF-CUC) transcription factor OsNAC2 as a negative regulator in the resistance to bacterial blight disease in rice. Constitutive overexpression of OsNAC2 inhibited the expression of salicylic acid (SA) biosynthesis-related genes (i.e. isochorismate synthase 1 (OsICS1), phenylalanine ammonia lyase 3 (OsPAL3), etc.) with adverse impacts on the pathogenesis-related proteins (PRs) responses and compromised blight resistance. Moreover, OsNAC2 interacted with APETALA2/ethylene-responsive element binding protein (AP2/EREBP) transcription factor OsEREBP1 and possibly threatened its protein stability, destroying the favorable interaction of OsEREBP1-Xa21-binding protein OsXb22a in the cytoplasm during Xoo-induced infection. On the contrary, downregulation of OsNAC2 resulted in enhanced resistance to bacterial blight in rice without any growth or yield penalties. Our results demonstrated that OsNAC2 inhibits SA signaling and stably interacted with OsEREBP1 to impair disease resistance. This OsNAC2-OsEREBP1-based homeostatic mechanism provided insights into the competition between rice and bacterial pathogens, and it will be useful to improve the disease resistance of important crops through breeding.

Action mechanism of the potential biocontrol agent Brevibacillus laterosporus SN19-1 against Xanthomonas oryzae pv. oryzae causing rice bacterial leaf blight.

The causal agent of rice bacterial leaf blight (BLB) is Xanthomonas oryzae pv. oryzae (Xoo), which causes serious damage to rice, leading to yield reduction or even crop failure. Brevibacillus laterosporus SN19-1 is a biocontrol strain obtained by long-term screening in our laboratory, which has a good antagonistic effect on a variety of plant pathogenic bacteria. In this study, we investigated the efficacy and bacterial inhibition of B. laterosporus SN19-1 against BLB to lay the theoretical foundation and research technology for the development of SN19-1 as a biopesticide of BLB. It was found that SN19-1 has the ability to fix nitrogen, detoxify organic phosphorus, and produce cellulase, protease, and siderophores, as well as IAA. In a greenhouse pot experiment, the control efficiency of SN19-1 against BLB was as high as 90.92%. Further investigation of the inhibitory mechanism of SN19-1 on Xoo found that the biofilm formation ability of Xoo was inhibited and the pathogenicity was weakened after the action of SN19-1 sterile supernatant on Xoo. The activities of enzymes related to respiration and the energy metabolism of Xoo were significantly inhibited, while the level of intracellular reactive oxygen species was greatly increased. Scanning electron microscopy observations showed folds on the surface of Xoo. A significant increase in cell membrane permeability and outer membrane permeability and a decrease in cell membrane fluidity resulted in the extravasation of intracellular substances and cell death. The results of this study highlight the role of B. laterosporus SN19-1 against the pathogen of BLB and help elucidate the underlying molecular mechanisms.

Evaluation of Metabarcoding Methods for Plant Disease Surveillance

Metabarcoding holds great potential for general plant pathogen surveillance by providing an untargeted profile of the host microbiome. However, the standard marker utilized for microbiome analysis of prokaryotes, the 16 rRNA gene, offers limited diagnostic utility as it provides phylogenetic resolution primarily at the genus level, and universal primers often co-amplify plant DNA. Here, we evaluated two recently published universal primer sets targeting the DNA gyrase and RNA polymerase ß subunit genes ( gyrB and rpoB, respectively), relative to a plant discriminating 16S primer set (799F/1115R), as disease surveillance tools. Comparative analysis of a mock bacterial community, as well as naturally infected citrus variegated chlorosis samples, indicated that the gyrB method displayed optimal performance in the amplification of DNA across a broad taxonomic spectrum of plant-pathogenic bacteria, providing resolution at the species and, in some cases, subspecies levels. It also generated high-quality datasets with minimal to no co-amplification of plant DNA, outperforming the rpoB and 16S assays in these regards. Further evaluation revealed that the gyrB method displayed an overall linear trend in the detection of several diverse bacterial pathogens; however, it was at least an order of magnitude less sensitive than a standard real-time PCR assay. Finally, we demonstrate the potential of this method to disentangle a mixed population of Pantoea spp. associated with a rice-bacterial blight outbreak and identify putative novel pathogens that would otherwise be overlooked with conventional PCR-based tests. This work represents steps toward establishing a robust, untargeted metabarcoding method for general plant disease surveillance. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Genome Resource for the Highly Virulent Xanthomonas oryzae pv. oryzae Strain HN2011 from China

Xanthomonas oryzae pv. oryzae ( Xoo) is the causal bacterium of rice bacterial blight (BB), which is one of the most destructive bacterial diseases of rice worldwide. Although more than 40 BB resistance genes ( Xa genes) have been identified, only a few conferring broad resistance (e.g., Xa4 and Xa21) have been widely used for rice breeding in Asia. The narrow genetic basis for the BB resistance of rice cultivars has resulted in the emergence of new pathogenic strains that can overcome the resistance of commonly grown rice cultivars derived from breeding programs. For example, Xoo strain HN2011, which was isolated in Hainan (China), can overcome the resistance mediated by multiple BB resistance genes, including Xa4 and Xa21. We herein present the complete genome sequence of HN2011 generated by Nanopore sequencing. The genomic data will be useful for elucidating the genomic variations of Xoo and will contribute to clarifying the interaction between Xoo and rice. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license .

Effects of seed soaking and foliar spraying of Kalanchoe pinnata aqueous leaf extracts against rice bacterial leaf blight

This study aims at evaluating the disease-reducing effects against rice bacterial leaf blight (Xanthomonas oryzae pv. oryzae). Under greenhouse conditions, the activities of the four enzymes [peroxidase (POX), catalase (CAT), polyphenol oxidase (PPO) and phenylalanine ammonia lyase (PAL)] after application of Kalanchoe pinnata aqueous leaf extracts using the combination of seed soaking and foliar spraying were studied. Overall, two extract concentrations [1 and 2% (w/v)] applied as seed soaking combined with the five extract concentrations [1, 2, 3, 4 and 5% (w/v)] applied as foliar spraying were tested. Three application methods were furthermore used for foliar spraying (7 days before pathogen inoculation (DBI), 14 DBI and their combination). Results showed the effects increased with the increase of extract concentrations and durations from application time points prior to pathogen inoculation. The combination of foliar spraying at 7 and 14 DBI provided stronger protection compared to single sprays. The effects involved induced resistance. Indeed, the activities of POX and CAT increased until 4 days after inoculation (DAI) and remained until 7 DAI, while those of PPO and PAL increased similarly then decreased until 7 DAI. Activities of these enzymes increased after pathogen inoculation and reached higher levels with extract applications.

Bactericidal bissulfone B7 targets bacterial pyruvate kinase to impair bacterial biology and pathogenicity in plants.

The prevention and control of rice bacterial leaf blight (BLB) disease has not yet been achieved due to the lack of effective agrochemicals and available targets. Herein, we develop a series of novel bissulfones and a novel target with a unique mechanism to address this challenge. The developed bissulfones can control Xanthomonas oryzae pv. oryzae (Xoo), and 2-(bis(methylsulfonyl)methylene)-N-(4-chlorophenyl) hydrazine-1-carboxamide (B7) is more effective than the commercial drugs thiodiazole copper (TC) and bismerthiazol (BT). Pyruvate kinase (PYK) in Xoo has been identified for the first time as the target protein of our bissulfone B7. PYK modulates bacterial virulence via a CRP-like protein (Clp)/two-component system regulatory protein (regR) axis. The elucidation of this pathway facilitates the use of B7 to reduce PYK expression at the transcriptional level, block PYK activity at the protein level, and impair the interaction within the PYK-Clp-regR complex via competitive inhibition, thereby attenuating bacterial biology and pathogenicity. This study offers insights into the molecular and mechanistic aspects underlying anti-Xoo strategies that target PYK. We believe that these valuable discoveries will be used for bacterial disease control in the future.

BsR1, a broad-spectrum antibacterial peptide with potential for plant protection.

The urgent need for new antibacterial drugs arises from the emergence of bacterial multidrug resistance due to antibiotic overuse. Antimicrobial peptides, crucial components of innate immunity in animals and plants, exhibit effectiveness against multidrug-resistant bacteria while minimizing the development of drug resistance. In this study, the antibacterial peptide BsR1, comprising 21 amino acids, was finalized by predicting the active site of an antifungal gene and sequence optimization. BsR1 displayed broad-spectrum antibacterial activities against diverse Gram-positive and Gram-negative bacteria, with a low minimum inhibitory concentration of 4.25-17 μM. Stability experiments demonstrated that BsR1 has high resistance to thermal, ultraviolet, and acid-base conditions, while revealing increased sensitivity to divalent ions Ca2+ and Mg2+. The mode of action of BsR1 involved cell membrane damage, leading to bacterial cell structure disruption and subsequent death. Secondary structure prediction indicated a linear helical conformation with a positive charge of +7.5, facilitating its interaction with the target cell membrane. BsR1 exhibited excellent biological safety, as it did not induce necrosis in tobacco leaves, and the low observed hemolytic effect on mammalian cells with a value of 3.26%. Additionally, BsR1 demonstrated the ability to enhance disease resistance in rice and effectively curbed the spread of rice bacterial blight. This research presents BsR1 as a novel approach and potential medication in the development of antibacterial drugs, offering a valuable tool in combating pathogenic microorganisms, particularly in plants.IMPORTANCEThis study addresses the critical need for new antibacterial drugs in the face of bacterial multidrug resistance resulting from antibiotic overuse. It highlights the significance of antimicrobial peptides as essential components of innate immunity in animals and plants, which have been proven effective against multidrug-resistant bacteria and are difficult to develop resistance against. This study successfully synthesizes a broad-spectrum antibacterial peptide, BsR1, with strong inhibitory activities against various Gram-positive and Gram-negative bacteria. BsR1 demonstrates favorable stability and a mode of action that damages bacterial cell membranes, leading to cell death. It also exhibits biological safety and shows potential in enhancing disease resistance in rice. This research offers a novel approach and potential medication for antibacterial drug development, presenting a valuable tool in combating pathogenic microorganisms, particularly in plants.

Repurposing Salicylamides to Combat Phytopathogenic Bacteria and Induce Plant Defense Responses.

Based on the research strategy of "drug repurposing", a series of derivatives and marketed drugs that containing salicylic acid skeleton were tested for their antibacterial activities against phytopathogens. Salicylic acid can not only regulate some important growth metabolism of plants, but also induce plant disease resistance. The bioassay results showed that the salicylamides exhibited excellent antibacterial activity. Especially, oxyclozanide showed the best antibacterial effect against Xanthomonas oryzae, Xanthomonas axonopodis pv. citri and Pectobacterium atroseptica with MICs of 0.78, 3.12 and 12.5 μg.mL-1, respectively. In vivo experiments with rice bacterial leaf blight had further demonstrated that oxyclozanide exhibited stronger antibacterial activity than the commercial bactericide, thiodiazole copper. Oxyclozanide could induce plant defense responses through the determination of salicylic acid content and the activities of defense-related enzymes including CAT, POD, and SOD in rice. The preliminarily antibacterial mechanism study indicated that oxyclozanide exhibited the antibacterial activity by disrupting cell integrity and reducing bacterial pathogenicity. Additionally, oxyclozanide could induce plant defense responses through the determination of salicylic acid content.

Design, synthesis and antibacterial activity of coumarin-3-carboxylic acid derivatives containing acylhydrazone moiety

Plant diseases caused by bacteria lead to enormous yield and economic losses in agricultural production. To develop innovative bactericides for controlling plant disease, a series of coumarin-3-carboxylic acid derivatives containing acylhydrazone thioether/sulfoxide were designed and synthesized by utilizing the principles of bioisosterism and active splicing. The bactericidal activities of these derivatives were subsequently evaluated. The result indicated that E2 exhibited the highest antibacterial activities in vitro against Xanthomonas oryzae pv. oryzae, Ralstonia solanacearum, and Acidovorax citrulli, with EC50 values of 2.97, 1.17, and 1.23 µg/mL, respectively. Moreover, in vivo experiments showed that E2 exhibited robust protective properties against Ralstonia solanacearum, and Acidovorax citrulli, with efficacies of 72.52 % and 63.90 %, respectively, at a concentration of 100 µg/mL, which was comparable to the positive control kasugamycin at the same concentration. Scanning electron microscopy analysis revealed that E2 induced changes in the cellular morphology of Acidovorax citrulli, such as shrinkage and collapse. Subsequent investigation revealed that E2 had the capacity to compromise the structural stability of the bacterial membrane of Ralstonia solanacearum. This study represents the first report on the antibacterial activities of this series of coumarin-3-carboxylic acid derivatives containing the acylhydrazone thioether/single-sulfoxide moiety, and the results suggest that coumarin-3-carboxylic acid derivatives containing the acylhydrazone single-sulfoxide may hold potential as effective antibacterial agents. And coumarin-3-carboxylic acid derivatives exhibited promise as plant bacterial agent to prevent rice bacterial leaf blight, tomato bacterial wilt, and melon bacterial fruit blotch.

Xoo-YOLO: a detection method for wild rice bacterial blight in the field from the perspective of unmanned aerial vehicles.

Wild rice, a natural gene pool for rice germplasm innovation and variety improvement, holds immense value in rice breeding due to its disease-resistance genes. Traditional disease resistance identification in wild rice heavily relies on labor-intensive and subjective manual methods, posing significant challenges for large-scale identification. The fusion of unmanned aerial vehicles (UAVs) and deep learning is emerging as a novel trend in intelligent disease resistance identification. Detecting diseases in field conditions is critical in intelligent disease resistance identification. In pursuit of detecting bacterial blight in wild rice within natural field conditions, this study presents the Xoo-YOLO model, a modification of the YOLOv8 model tailored for this purpose. The Xoo-YOLO model incorporates the Large Selective Kernel Network (LSKNet) into its backbone network, allowing for more effective disease detection from the perspective of UAVs. This is achieved by dynamically adjusting its large spatial receptive field. Concurrently, the neck network receives enhancements by integrating the GSConv hybrid convolution module. This addition serves to reduce both the amount of calculation and parameters. To tackle the issue of disease appearing elongated and rotated when viewed from a UAV perspective, we incorporated a rotational angle (theta dimension) into the head layer's output. This enhancement enables precise detection of bacterial blight in any direction in wild rice. The experimental results highlight the effectiveness of our proposed Xoo-YOLO model, boasting a remarkable mean average precision (mAP) of 94.95%. This outperforms other models, underscoring its superiority. Our model strikes a harmonious balance between accuracy and speed in disease detection. It is a technical cornerstone, facilitating the intelligent identification of disease resistance in wild rice on a large scale.

Rice bacterial leaf blight drives rhizosphere microbial assembly and function adaptation.

Our results suggest that rhizosphere bacteria are more sensitive to bacterial leaf blight (BLB) than fungi. BLB infection decreased the diversity of the rhizosphere bacterial community but increased the complexity and size of the rhizosphere microbial community co-occurrence networks. In addition, the relative abundance of the genera Streptomyces, Chitinophaga, Sphingomonas, and Bacillus increased significantly. Finally, these findings contribute to the understanding of plant-microbiome interactions by providing critical insight into the ecological mechanisms by which rhizosphere microbes respond to phyllosphere diseases. In addition, it also lays the foundation and provides data to support the use of plant microbes to promote plant health in sustainable agriculture, providing critical insight into ecological mechanisms.

Whale Optimized Deep Model for Paddy and Maize Leaf Disease Detection

Plant disease management is an essential process to minimize loss in the field of agriculture. Plant leaf disease detection(PLDD) technology helps the formers to reduce the loss of quality yield production. This study focuses on detecting paddy and maize plant leaf disease-detecting methods. It contributes to a PLDD method to improve detection accuracy and overall performance. The PLDD method introduced a whales-optimized artificial neural network (WOANN) method for classifying the four Maize and four rice leaf disease-related classes. The WOANN uses the whale optimizer's food-searching functionalities to improve the performance and detection accuracy of the dense net model. This WOANN classifies the maize leaf light, maize grey leaf spot, maize common rust, rice bacterial leaf blight, rice bacterial leaf steak, rice brown spot, and healthy leaves of both Maize and paddy. It uses the Hilbert-Schmidt independent criterion lasso correlation algorithm to support the WOANN classifier in selecting the significant features. The performance analysis shows that the WOANN-based approach achieves a maximum of 99.35% detection accuracy for maize leaf disease and 99.13% for paddy leaf disease. Its efficiency analysis shows that the WOANN-based approaches achieve a maximum accuracy rate than comparison approaches.

Sigma factor 70 RpoD contributes to virulence by regulating cell motility, oxidative stress tolerance, and manipulating the expression of hrpG and hrpX in Xanthomonas oryzae pv. oryzae

Xanthomonas oryzae pv. oryzae (Xoo) causes bacterial blight in rice, which reduces crop yield and leads to significant economic losses. Bacterial sigma (σ) factors are highly specialized proteins that allow RNA polymerase to recognize and bind to specific promoters. σ70 factors also regulate the expression of genes involved in stress response and virulence. However, the role of RpoD in Xoo is still unclear. In this study, we found that σ70 factor RpoD is quite conservative among phytopathogenic bacteria, especially in Xanthomonas sp. In Xoo, PXO_RpoD plays an important role in oxidative stress tolerance and cell motility, as well as being essential for full virulence. Cleavage under targets and tagmentation (CUT&Tag) analyses indicated that RpoD mediates the type three secretion system (T3SS) by regulating the regulation of hrpG and hrpX. By performing bacterial one-hybrid and electrophoretic mobility assay (EMSA), we observed that RpoD directly bound to the promoters of hrpG and hrpX. Collectively, these results demonstrate the transcriptional mechanism and pathogenic functions of RpoD in regulating cell motility and oxidative stress response, providing novel insights into potential targets for disease control.

Inorganic Nanoparticles–Driven Self–Assembly of natural small molecules in water for constructing multifunctional nanocapsules against plant diseases

Directly constructing nanoparticles through the self–assembly of natural small molecules in aqueous media presents many opportunities for crop protection; however, this special strategy is hindered by the lack of simple and cost–effective preparation methods to date. Herein, we report a facile strategy for constructing multifunctional natural nanocapsules for treating plant diseases based on the special coassembly of natural small organic molecules and inorganic nanoparticles. In aqueous conditions, uniform curcumin nanocapsules (ZnO@Cur) are assembled through electrostatic interactions, coordination effects and hydration effects as mediated by trace of nanoscale zinc oxide. The nanocapsules obtained can be further modified to enhance stability by introducing a polydopamine coating (ZnO@Cur@PDA). The antibacterial activity of ZnO@Cur@PDA against plant-pathogenic bacteria was better than that of curcumin, ZnO NPs, ZnO@Cur and zinc thiazole in vitro. The nanocapsules effectively kill plant–pathogenic bacteria via tight binding to the bacterial surface, inducing reactive oxygen species accumulation and disrupting bacterial cell walls. ZnO@Cur@PDA display strong activities against rice bacterial blight with protective activity of 64.0 % and curative activity of 62.2%, which is much better than commercial drugs bismerthiazol (protective activity of 33.0 % and curative activity of 38.4%) and zinc thiazole(protective activity of 38.6 % and curative activity of 31.8%). ZnO@Cur@PDA display adequate washing resistance, and low rice plant toxicity; furthermore, they are degradable. Additionally, both the inner cavities and outer surfaces of nanocapsules bear abundant sites and spaces that can be further tuned for loading other pesticide molecules or flexible construct complex multifunctional nanoparticles. Our study should encourage further development in the coassembly of organic and inorganic materials via green processes for effective and tunable nanopesticides.

Survey and Isolation of Rice Bacterial Leaf Blight Caused by Xanthomonas oryzae pv. oryzae

A survey was conducted at different rice growing regions of Tamil Nadu such as Erode, Tanjore and Coimbatore. Among the areas surveyed the maximum disease incidence was recorded at Tanjore in the rice variety ADT 54 with the percent disease incidence of 50.23%. Initially one bacterial pathogen Xanthomonas oryzae pv.oryzae was isolated in nutrient agar medium from the leaves having characteristic symptom. Totally 10 isolates of Xoo were collected from three different regions of Tamil Nadu. On isolating the pathogen the colonies are found to be well separated with slimy yellow color and mucoid growth.

The effect of tobacco leaf biopesticides on the development of bacterial leaf blight of rice

The staple food of the Indonesian population is rice, the need for rice continues to increase following the increase in population, and one of the obstacles to increasing production is crop failure caused by rice leaf blight. Leaf blight is one of the important diseases which causes almost 70% yield loss. The purpose of this study was to determine the effect of the concentration and interval of application of tobacco leaf biopesticide on the development of leaf blight in Ciherang rice variety. This study was designed using a factorial complete randomized design, the first factor was the concentration of tobacco leaf biopesticide which consisted of 4 levels, namely 0 ml/l, 1 ml/l, 2 ml/l, and 3 ml/l. the second factor is the Giving Interval which consists of 3 levels. i. e. every 5 days, 10 days, and 15 days. Parameters of the development of rice bacterial leaf blight (BLB) that were observed were the number of grains per plant, percentage of attack and intensity of attack by leaf blight. The results showed that the highest number of grains per plant, the lowest attack percentage, and the lowest attack intensity were in the B3P1.

Synthesis, antibacterial and antifungal activity of myricetin derivatives containing piperidine and amide fragments.

Continuous use of synthetic bactericides and fungicides is causing pathogens to develop resistance, resulting in increased use of pesticides and affecting food security. The green pesticides derived from natural products could reduce or avoid 'pesticide hazards' caused by synthetic pesticides as a result of their unique mechanism of action. Therefore, it is of great significance to create green pesticides with novel structures. Herein, 30 novel myricetin derivatives containing piperidine and amide fragments were designed and synthesized using active group splicing. Among them, compound Z30 had excellent inhibitory effect against Xanthomonas oryzae pv. Oryzae (Xoo) with the half effective concentration (EC50 ) of 2.7 μg mL-1 . Compound Z26 not only exhibited better antibacterial activity against Xaxonopodis pv. Citri (Xac) with EC50 of 3.9 μg mL-1 , but also displayed higher antifungal activity against Rhizoctonia solani (Rs) with EC50 of 8.3 μg mL-1 . In vivo experiments proved that Z30 against bacterial blight of rice and Z26 against rice blast exhibits significant protective and curative effect. Scanning electron microscopy (SEM) and transmission electron microscopy (TEM) showed that Z26 and Z30 could change the integrity of cell wall and membrane of pathogen Xoo, Xac and Rs, resulting in cytoplasmic leakage and eventually death. Enzymatic assay, molecular docking and molecular dynamics simulations (MDs) indicated that Z26 could be used as a potential succinate dehydrogenase inhibitor (SDHI). Z26 and Z30 significantly reduced the pathogenicity of the pathogens, which provided a new idea and direction for the development of green pesticides. © 2023 Society of Chemical Industry.

Enhancing Rice Crop Management: Disease Classification Using Convolutional Neural Networks and Mobile Application Integration

Early diagnosis of rice disease is important because it poses a considerable threat to agricultural productivity as well as the global food security of the world. It is challenging to obtain more reliable outcomes based on the percentage of RGB value using image processing outcomes for rice disease detections and classifications in the agricultural field. Machine learning, especially with a Convolutional Neural Network (CNN), is a great tool to overcome this problem. But the utilization of deep learning techniques often necessitates high-performance computing devices, costly GPUs and extensive machine infrastructure. As a result, this significantly raises the overall expenses for users. Therefore, the demand for smaller CNN models becomes particularly pronounced, especially in embedded systems, robotics and mobile applications. These domains require real-time performance and minimal computational overhead, making smaller CNN models highly desirable due to their lower computational cost. This paper introduces a novel CNN architecture which is comparatively small in size and promising in performance to predict rice leaf disease with moderate accuracy and lower time complexity. The CNN network is trained with processed images. The image processing is performed using segmentation and k-means clustering to remove background and green parts of affected images. This technique proposes to detect rice disease of rice brown spot, rice bacterial blight and leaf smut with reliable outcomes in disease classifications. The model is trained using an augmented dataset of 2700 images (60% data) and validated with 1200 images of disease-affected samples to identify rice disease in agricultural fields. The model is tested with 630 images (14% data); testing accuracy is 97.9%. The model is exported into a mobile application to introduce the real-life application of the outcome of this work. The model accuracy is compared to others work associated with this type of problem. It is found that the performance of the model and the application are satisfactory compared to other works related to this work. The over-all accuracy is notable, showing the reliability and dependability of this model to classify rice leaf diseases.