Bacterial Leaf Blight Research Articles

Efektivitas Bakteri Endofit Asal Lahan Basah untuk Menekan Penyakit Hawar Daun Bakteri (Xanthomonas oryzae) pada Padi Beras Merah (Oryza nivara L.)

Brown rice is a type of rice that has many benefits for the health of the body. The main diseases that attack many rice plants and cause a decrease in production include bacterial leaf blight (HDB) caused by the bacterium Xanthomonas oryzae. One alternative to control HDB is to use antagonistic agents, namely endophytic bacteria. This study aims to examine the ability of endophytic bacterial isolates from wetlands and the effect of application time in suppressing the intensity of bacterial leaf blight and to determine its effect on the growth of brown rice plants. There were 2 isolates of endophytic bacteria tested in this study, namely isolates of root origin (AKL) and isolates of stem origin (BLR) isolated from karamunting plants. This study used a completely randomized design (CRD) consisting of 5 treatments and 4 replications. The treatment used in this study was only the pathogen Xanthomonas Oryzae (control), soaking seeds with endophytic bacteria from roots, soaking seeds with endophytic bacteria from stems, soaking seeds + application when transplanting with endophytic bacteria from roots and seed soaking + application when transplanting Plant with stem-origin endophytic bacteria. Treatment of endophytic bacteria on brown rice seeds and application during transplanting was able to reduce the intensity of bacterial leaf blight (X. oryzae) with a disease intensity of 83% and an effectiveness of 15.6%. Treatment of endophytic bacteria on rice seeds did not inhibit seed germination and was able to increase the number of tillers, but had not been able to affect the increase in plant height.

Structural insight into subunit F of respiratory chain complex I from Xanthomonas oryzae pv. oryzae inhibition by parthenolide.

Bacterial leaf blight caused by Xanthomonas oryzae pv. oryzae (Xoo) is one of the most serious diseases of rice, and there is a lack of bactericides for controlling this disease. We previously found parthenolide (PTL) is a potential lead for developing bactericides against Xoo, and subunit F of respiratory chain complex I (NuoF) is an important target protein of PTL. However, the binding modes of PTL with NuoF need further elucidation. In this study, we obtained the crystal structure of Xoo NuoEF (complex of subunit E and F of respiratory chain complex I) with a resolution of 2.36 Å, which is the first report on the protein structure of NuoEF in plant-pathogenic bacteria. The possible binding sites of PTL with NuoF (Cys105 and Cys187) were predicted with molecular docking and mutated into alanine using a base mismatch method. The mutated proteins were expressed in Escherichia coli and purified with affinity chromatography. The binding abilities of PTL with mutated proteins were investigated via pull-down assay and BIAcore analysis, which revealed that double mutation of Cys105 and Cys187 in NuoF severely affected the binding ability of PTL with NuoF. In addition, the binding modes were further simulated with combined quantum mechanical/molecular mechanical calculations, and the results indicated that PTL may have a stronger binding with Cys105 than Cys187. NuoEF protein structure of Xoo was resolved, and Cys105 and Cys187 in NuoF are important binding sites of PTL. This study further clarified the action mechanism of PTL against Xoo, and will promote the innovation of bactericides targeting Xoo complex I. © 2024 Society of Chemical Industry.

Cost-effective multiplex PCR assay for simultaneous detection of bacterial leaf blight, blast and brown planthopper resistance genes in rice

Cost-effective multiplex PCR assay for simultaneous detection of bacterial leaf blight, blast and brown planthopper resistance genes in rice

Subtractive genomics study of Xanthomonas oryzae pv. Oryzae reveals repurposable drug candidate for the treatment of bacterial leaf blight in rice

BackgroundXanthomonas oryzae pv. oryzae is a plant pathogen responsible for causing one of the most severe bacterial diseases in rice, known as bacterial leaf blight that poses a major threat to global rice production. Even though several experimental compounds and chemical agents have been tested against X. oryzae pv. oryzae, still no approved drug is available. In this study, a subtractive genomic approach was used to identify potential therapeutic targets and repurposible drug candidates that could control of bacterial leaf blight in rice plants. ResultsThe entire proteome of the pathogen underwent an extensive filtering process which involved removal of the paralogous proteins, rice homologs, non-essential proteins. Out of the 4382 proteins present in Xoo proteome, five hub proteins such as dnaA, dnaN, recJ, ruvA, and recR were identified for the druggability analysis. This analysis led to the identification of dnaN-encoded Beta sliding clamp protein as a potential therapeutic target and one experimental drug named [(5R)-5-(2,3-dibromo-5-ethoxy-4hydroxybenzyl)-4-oxo-2-thioxo-1,3-thiazolidin-3-yl]acetic acid that can be repurposed against it. Molecular docking and 100 ns long molecular dynamics simulation suggested that the drug can form stable complexes with the target protein over time. ConclusionFindings from our study indicated that the proposed drug showed potential effectiveness against bacterial leaf blight in rice caused by X. oryzae pv. oryzae. It is essential to keep in consideration that the procedure for developing novel drugs can be challenging and complicated. Even the most promising results from in silico studies should be validated through further in vitro and in vivo investigation before approval.

In silico characterization of five novel disease-resistance proteins in Oryza sativa sp. japonica against bacterial leaf blight and rice blast diseases.

The online version contains supplementary material available at 10.1007/s13205-023-03893-5.

Inhibitory role of copper and silver nanocomposite on important bacterial and fungal pathogens in rice (Oryza sativa)

Rice (Oryza sativa) being among the most important food crops in the world is also susceptible to various bacterial and fungal diseases that are the major stumbling blocks in the way of increased production and productivity. The bacterial leaf blight caused by Xanthomonas oryzae pv. oryzae and the sheath blight disease caused by Rhizoctonia solani are among the most devastating diseases of the rice crop. In spite of the availability of array of chemical control, there are chances of development of resistance. Thus, there is a need for the nanotechnological intervention for management of disease in the form of copper and silver nano-composites. The copper (CuNPs) and silver nanoparticles (AgNPs) were synthesized using green route and characterized using different high throughput techniques, i.e., UV–Vis, FT-IR, DLS, XRD, FE-SEM, TEM. The particle size and zeta potential of synthesized CuNPs and AgNPs were found 273 nm and − 24.2 mV; 95.19 nm and − 25.5 mV respectively. The nanocomposite of CuNPs and AgNPs were prepared having particle size in the range of 375–306 nm with improved stability (zeta potential − 54.7 to − 39.4 mV). The copper and silver nanoparticle composites evaluated against Xanthomonas oryzae pv. oryzae and Rhizoctonia solani were found to have higher antibacterial (inhibition zone 13 mm) and antifungal activities (77%) compared to only the copper nanoparticle (8 mm; 62% respectively). Net house trials of nano-composite formulations against the bacterial blight of rice also corroborated the potential of nanocomposite formulation. In silico studies were carried out selecting two disease-causing proteins, peptide deformylase (Xanthomonas oryzae) and pectate lyase (Rhizoctonia solani) to perform the molecular docking. Interaction studies indicatedthat both of these proteins generated better complex with CuNPs than AgNPs. The study suggested that the copper and silver nano-composites could be used for developing formulations to control these devastating rice diseases.

Molecular and Phenotypic Investigation on Antibacterial Activities of Limonene Isomers and Its Oxidation Derivative against Xanthomonas oryzae pv. oryzae.

Xanthomonas oryzae pv. oryzae (Xoo) causes a devastating bacterial leaf blight in rice. Here, the antimicrobial effects of D-limonene, L-limonene, and its oxidative derivative carveol against Xoo were investigated. We revealed that carveol treatment at ≥ 0.1 mM in liquid culture resulted in significant decrease in Xoo growth rate (> 40%) in a concentration-dependent manner, and over 1 mM, no growth was observed. The treatment with D-limonene and L-limonene also inhibited the Xoo growth but to a lesser extent compared to carveol. These results were further elaborated with the assays of motility, biofilm formation and xanthomonadin production. The carveol treatment over 1 mM caused no motilities, basal level of biofilm formation (< 10%), and significantly reduced xanthomonadin production. The biofilm formation after the treatment with two limonene isomers was decreased in a concentration-dependent manner, but the degree of the effect was not comparable to carveol. In addition, there was negligible effect on the xanthomonadin production mediated by the treatment of two limonene isomers. Field emission-scanning electron microscope (FE-SEM) unveiled that all three compounds used in this study cause severe ultrastructural morphological changes in Xoo cells, showing shrinking, shriveling, and holes on their surface. Moreover, quantitative real-time PCR revealed that carveol and D-limonene treatment significantly down-regulated the expression levels of genes involved in virulence and biofilm formation of Xoo, but not with L-limonene. Together, we suggest that limonenes and carveol will be the candidates of interest in the development of biological pesticides.

Performance analysis of various deep learning models for detecting rice diseases

&lt;p&gt;A major portion of the world’s population relies on rice as a staple diet, hence rice is essential to maintaining food security worldwide. Unfortunately, rice crops are susceptible to a number of illnesses that, if detected and treated promptly, can result in significant output losses. Expert visual inspection is a time-consuming and arbitrary part of the conventional procedures for diagnosing diseases in rice. An effective method for automated illness diagnosis in agriculture has evolved in recent years: deep learning, a branch of artificial intelligence. The objective of this research is to compare AlexNet, DCNN, MobileNet, GoogleNet, VGG16, ResNet50 and Xception, these are various deep learning models in order to choose the one that would produce the highest levels of accuracy, precision recall, specificity, and F1-score for detecting rice diseases. In this study we train the model for nine different types of rice diseases named as Rice Blast (Pyricularia oryzae), Rice Sheath Blight (Rhizoctonia Solani), Bacterial Leaf Blight (Xanthomonas oryzae pv. oryzae), Tungro Disease, Rice Grassy Stunt Virus (RGSV), Rice Yellow Mottle Virus (RYMV), Bakanae Disease (Fusarium moniliforme), Brown Spot (Cochliobolus miyabeanus) and Rice Tungro Bacilliform Virus (RTBV) with 30,000 images. For this we used the secondary dataset for analyzing the performance of models. We trained the model for both normalized and non-normalized dataset. After comparing the various models we get the better result from ResNet50 model with accuracy of 97.50%.&lt;/p&gt;

Effect of Application of Endophytic Bacteria on the Development of Bacterial Leaf Blight Disease, Growth, and Production of Rice Plants

Bacterial leaf blight can be found in various stages of rice plant growth, so this disease can affect the growth and production of rice plants. This research aims to determine the effect of applying an endophytic bacterial formula to rice seedlings on the development of HDB disease, growth, and production of rice plants. This study used 4 isolates of endophytic bacteria (isolates BE-KH1, BE-M2, BE-M3, and BE-S5) which were formulated in coconut water waste + peptone. The results of the study showed that the application of the endophytic bacterial formula to rice seedlings was able to reduce the severity of bacterial leaf blight by 54,5 – 63,2% and had an effect on growth, full grain weight, and rice grain weight in rice plants inoculated with Xanthomonas oryzae pv. oryzae bacteria.

Investigation of the antibacterial activity of benziothiazolinone against Xanthomonas oryzae pv. oryzae

Plant pathogenic bacteria can cause numerous diseases for higher plants and result in severe reduction of crop yield. Introduction of new bactericides can always effectively control these plant diseases. Benziothiazolinone (BIT) is a novel fungicide registered in China for the control of plant fungal diseases, however, its anti-bacterial activity is not well studied. The results of activity tests showed that BIT exhibited stronger inhibitory activity against bacteria, particularly for Xanthomonas oryzae pv. oryzae (Xoo) (EC50 = 0.17 μg/mL), which was superior than that of the tested fungi in vitro. BIT also exhibited excellent protective and curative activity against rice bacterial leaf blight (BLB) caused by Xoo with the control efficacies of 71.37% and 91.64% at 600 μg/mL, respectively. After treatment with BIT, Xoo cell surface became wrinkled and the cell shape was distorted with extruding cellular content. It was also found that BIT decreased DNA synthesis and affected the biofilm formation and motility of Xoo cells. However, no significant change in the protein content was observed. Moreover, the results of quantitative real-time PCR also showed that expressions of several genes related to DNA synthesis, biofilm formation and motility of Xoo cells were down- or up-regulated, which further proved the anti-bacterial activity of BIT in influencing the biological properties of Xoo. Additionally, BIT also enhanced the activity of phenylalanine ammonia lyase (PAL), a plant defense enzyme. Taken together, benziothiazolinone might be served as an alternative candidate for the control of BLB.

Strategy For Controlling Bacterial Leaf Blight (Xanthomonas sp.) on Eucalyptus Pellita Plants by Administering P. aeruginosa RE081

The demand for Eucalyptus Pellita seeds as a high-throughput inoculum (HTI) crop commodity in the field is extremely high. However, Xanthomonas sp., a bacteria that causes bacterial leaf blight, poses a significant challenge in ensuring a steady supply of healthy seedlings in nurseries. Researchers have explored using the rhizobacteria P. aeruginosa RE081 as an environmentally friendly biocontrol agent to address this issue. This study aims to determine the optimal concentration of P. aeruginosa RE081 that can effectively reduce the incidence and severity of bacterial leaf blight caused by Xanthomonas sp. The research was conducted using a completely randomized design, with different concentrations of P. aeruginosa RE081 (105, 106, 107, 108 CFU/mL) being tested. The findings indicate that the biological agent's concentration significantly impacts plant disease occurrence and severity. In vivo testing revealed that P. aeruginosa RE081 reduced disease severity by only 2.13% at a 108 CFU/mL concentration. Interestingly, concentrations lower than 108 CFU/mL increased disease severity compared to the control group.

First report of bacterial leaf blight on tea: an emerging threat to the Indian tea industry

First report of bacterial leaf blight on tea: an emerging threat to the Indian tea industry

Characterization of rice aspartic protease genes and induced expression by phytohormones and Xanthomonas oryzae pv. oryzae

Aspartic proteases (APs) are present in both monocotyledonous and dicotyledonous plants. APs consist of nine different families of proteolytic enzymes. APs play important functions in several physiological processes including defense. However, there are limited reports on APs in disease resistance in rice (Oryza sativa). Here, we report that 104 APs were discovered in rice genome. They can be classified into three clades (I, II and III) with APs from Arabidopsis thaliana, and Nymphaea colorata according to phylogenetic relationships. Tandem and segmental duplications were observed to lead to the expansion of OsAP genes in rice. Analysis of gene structure revealed that numerous OsAPs contain multiple exons and introns, however, several OsAPs harbor a single exon and no introns. Synteny analyses demonstrated that four AP genes among O. sativa, A. thaliana, and N. colorata may evolve from a common ancestor of land plants. Ten conserved motifs of amino acids were uncovered from the OsAPs, and two of the motifs are the catalytic sequences, with the conserved Asp-Thr and Ser-Gly amino acids. Within the OsAP promoter sequences, cis-regulatory elements responsive to light, abscisic acid, auxin, gibberellins, methyl jasmonate, and salicylic acid were identified. Stress-responsive elements and tissue-specific expressed elements were also found. Majority of OsAP genes were found to be expressed in diverse tissues and organs. Some of the OsAP genes were observed to be induced by brassinosteroids, jasmonic acid, and salicylic acid. Further, some OsAP genes can be induced by Xanthomonas oryzae pv. oryzae (Xoo), the cause of rice bacterial leaf blight. Among them, OsAP21 was strongly activated by the pathogen, suggesting its potential function in response to the bacterial agent. The results shed light in the potential functions of OsAP genes in rice disease resistance to Xoo.

Introgression of bacterial leaf blight (BLB) resistant gene, Xa7 into MARDI elite variety, MR219 by marker assisted backcrossing (MABC) approach.

Bacterial leaf blight (BLB) is one of the major rice diseases in Malaysia. This disease causes substantial yield loss as high as 70%. Development of rice varieties which inherited BLB resistant traits is a crucial approach to promote and sustain rice industry in Malaysia. Hence, this study aims were to enhance BLB disease resistant characters of high yielding commercial variety MR219 through backcross breeding approach with supporting tool of marker-assisted selection (MAS). Broad spectrum BLB resistance gene, Xa7 from donor parent IRBB7 were introgressed into the susceptible MR219 (recurrent parent) using two flanking markers ID7 and ID15. At BC3F4, we managed to generate 19 introgressed lines with homozygous Xa7 gene and showed resistant characteristics as donor parent when it was challenged with Xanthomonas oryzae pv. oryzae through artificial inoculation. Recurrent parent MR219 and control variety, MR263 were found to be severely infected by the disease. The improved lines exhibited similar morphological and yield performance characters as to the elite variety, MR219. Two lines, PB-2-107 and PB-2-34 were chosen to be potential lines because of their outstanding performances compared to parent, MR219. This study demonstrates a success story of MAS application in development of improved disease resistance lines of rice against BLB disease.

Investigation of the Spread of Bacterial Wheat Leaf Blight Caused by Pathotypes of Pseudomonas syringaein Some Wheat Growing Areas in Syria

Abo Bakr, A., F. Khatib, M. Kassem, S.G. Kumari, N. Husien and N. Asaad. 2024. Investigation of the Spread of Bacterial Wheat Leaf Blight Caused by Pathotypes of Pseudomonas syringaein Some Wheat Growing Areas in Syria. Arab Journal of Plant Protection, 42(3): 291-298. https://doi.org/10.22268/AJPP-001257 Wheat is one of the most important cereal crops grown globally, which is affected by several biotic and abiotic stresses, especially in conjunction with the climatic changes that have been evident in the last decade, and among these stresses is the bacterial wheat leaf blight disease caused by the bacteria Pseudomonas syringae pv. syringae. The importance and danger of this bacterium is due to its ability to be transmitted by seed, as it negatively affects the quality of grain and the weight of one thousand grains. The study aimed to investigate the spread of bacterial wheat leaf blight caused by P. syringae and its pathotypes in the main wheat growing areas in Syria (Aleppo, Hama, Homs, Tartous and Latakia governorates) during 2022. The results obtained showed that bacterial wheat leaf blight disease was observed in 42 fields out of 59 fields surveyed (71.2%). The lowest incidence (50%) was recorded in Latakia with severity of less than 2, and highest incidence (77.8%) was recorded in Aleppo governorate with severity of 4 based on a 0-5 scale. Symptoms of bacterial wheat leaf blight was observed in all fields, which began as water-soacked leaf spots, and then turned into greenish-gray necrosis and finally a straw color. Symptoms of blackishbrown color nodes were observed only in 4 fields in Aleppo and Tartous governorates, it could be caused by the pathotype P. s. pv. japonica. In addition, the bases of wheat chaffs showed blackish-brown watery spots in 6 fields. In Aleppo and Tartous governorates these symptoms were identical to those typical of the pathotype P. s. pv. atrofaciens. Characteristics of 156 isolates, LOPAT tests and fluorescence on King B medium indicated that these isolates belong to the genus Pseudomonas, representing 87.7% of the total number of isolates, whereas 26 isolates (14.3%) were negative for Levan and fluorescence tests and their characteristics indicated that they belong to the genus Xanthomonas. Keywords: Wheat, bacterial wheat leaf blight, P. syringae, pathotypes, Syria

Marker-assisted breeding accelerates the development of multiple-stress-tolerant rice genotypes adapted to wider environments.

Rice, one of the major staple food crops is frequently affected by various biotic/abiotic stresses including drought, salinity, submergence, heat, Bacterial leaf blight, Brown plant hopper, Gall midge, Stem borer, Leaf folder etc. Sustained increase of yield growth is highly necessary to meet the projected demand in rice production during the year 2050. Hence, development of high yielding and multiple stress tolerant rice varieties adapted to wider environments will serve the need. A systematic MAB approach was followed to pyramid eight major QTLs/genes controlling tolerance to major abiotic/biotic stresses viz., drought (qDTY1.1 and qDTY2.1), salinity (Saltol), submergence (Sub1), bacterial leaf blight (xa13 and Xa21), blast (Pi9) and gall midge (Gm4) in the genetic background of an elite rice culture CBMAS 14065 possessing high yield and desirable grain quality traits. Two advanced backcross derivatives of CBMAS 14065 possessing different combinations of target QTLs namely #27-1-39 (qDTY1.1+qDTY2.1+Sub1+xa13+Xa21+Gm4+Pi9) and #29-2-2 (qDTY1.1+qDTY2.1+Saltol+Xa21+Gm4+Pi9) were inter-mated. Inter-mated F1 progenies harboring all the eight target QTLs/genes were identified through foreground selection. Genotyping of the inter-mated F4 population identified 14 progenies possessing all eight target QTLs/genes under homozygous conditions. All the fourteen progenies were forwarded up to F8 generation and evaluated for their yield and tolerance to dehydration, salinity, submergence, blast and bacterial leaf blight. All the 14 progenies exhibited enhanced tolerance to dehydration and salinity stresses by registering lesser reduction in their chlorophyll content, relative water content, root length, root biomass etc., against their recurrent parent Improved White Ponni/CBMAS 14065. All the 14 progenies harboring Sub1 loci from FR13A exhibited enhanced survival (90 - 95%) under 2 weeks of submergence /flooding when compared to their recurrent parent CBMAS 14065 which showed 100% susceptibility The inter-mated population showed a enhanced level of resistance to bacterial leaf blight (Score = 0 to 2) against blast (Score - 0) whereas the susceptible check CO 39 and the recurrent parent CBMAS 14065 recorded high level of susceptibility (Score = 7 to 9). Our study demonstrated the accelerated development of multiple stress tolerant rice genotypes through marker assisted pyramiding of target QTLs/genes using tightly linked markers. These multiple stress tolerant rice lines will serve as excellent genetic stocks for field testing/variety release and also as parental lines in future breeding programs for developing climate resilient super rice varieties.

Transcriptome analysis of differentially expressed genes in rice seedling leaves under different nitrate treatments on resistance to bacterial leaf blight.

Nitrogen (N), as one of the most abundant mineral elements in rice, not only is the primary limiting factor for rice yield, but also impacts plant disease resistance by modulating plant morphology, regulating biochemical characteristics, as well as enhancing metabolic processes. Bacterial blight, a severe bacterial disease caused by Xanthomonas oryzae pv. oryzae (Xoo), significantly impairing rice yield and quality. Previous studies have shown that moderate application of nitrate nitrogen can improve plant disease resistance. However, further exploration is urgently required to investigate the involvement of the nitrate nitrogen signaling pathway in conferring resistance against bacterial leaf blight. In this study, we employed transcriptome sequencing to analyze the differentially expressed genes under various concentrations of nitrate supply duringrice bacterial blight infection. Our research reveals that nitrate nitrogen supply influences rice resistance to bacterial leaf blight. Through transcriptomic profiling of rice leaves inoculated under different nitrate nitrogen concentrations, we identified 4815 differentially expressed genes (DEGs) among four comparison groups, with notable differences in DEG enrichment between low and high nitrate nitrogen conditions, with some members of the NPF family implicated and we preliminarily elucidated the molecular regulatory network in which nitrate nitrogen participates in bacterial leaf blight resistance. Our findings provide a novel insight into a mechanism involving the nitrate nitrogen drive wider defense in rice.

A disease predictive model based on epidemiological factors for the management of bacterial leaf blight of rice.

Rice is a widely consumed staple food for a large part of the world's human population. Approximately 90% of the world's rice is grown in Asian continent and constitutes a staple food for 2.7 billion people worldwide. Bacterial leaf blight (BLB) caused by Xanthomonas oryzae pv. oryzae is one of the devastating diseases of rice. A field experiment was conducted during the year 2016 and 2017 to investigate the influence of different meteorological parameters on BLB development as well as the computation of a predictive model to forecast the disease well ahead of its appearance in the field. The seasonal dataset of disease incidence and environmental factors was used to assess five rice varieties/ cultivars (Basmati-2000, KSK-434, KSK-133, Super Basmati, and IRRI-9). The accumulated effect of two year environmental data; maximum and minimum temperature, relative humidity, wind speed, and rainfall, was studied and correlated with disease incidence. Average temperature (maximum & minimum) showed a negative significant correlation with BLB disease and all other variables; relative humidity, rainfall, and wind speed had a positive correlation with BLB disease development on individual varieties. Stepwise regression analysis was performed to indicate potentially useful predictor variables and to rule out incompetent parameters. Environmental data from the growing seasons of July to October 2016 and 2017 revealed that, with the exception of the lowest temperature, all environmental factors contributed to disease development throughout the cropping season. A disease prediction multiple regression model was developed based on two-year data (Y = 214.3-3.691 Max T-0.508 Min T + 0.767 RH + 2.521 RF + 5.740 WS), which explained 95% variability. This disease prediction model will not only help farmers in early detection and timely management of bacterial leaf blight disease of rice but may also help reduce input costs and improve product quality and quantity. The model will be both farmer and environmentally friendly.

Model for Effective Rice Disease Recognition Based on Deep Learning Techniques

Iraq’s primary crop, crucial for both domestic consumption and exports, is rice. The prevalence of rice infections poses a significant challenge to farmers, impacting crop yield and resulting in substantial losses. Human identification of diseases relies on expertise, making early diagnosis crucial for sustaining rice plant health. To address the limited number of rice leaf images in the database, our approach incorporates augmentation and dilation rate. Integrating drone technology and machine learning algorithms offers a promising solution to efficiently diagnose rice leaf diseases. However, existing methods face challenges such as picture backgrounds, insufficient field image data, and symptom variations. This work introduces a robust methodology, leveraging a specialized Convolutional Neural Network (CNN) model for rice leaf photos, effectively enhancing disease classification accuracy. The proposed approach successfully identifies and diagnoses three distinct classes: leaf smut, brown spot, and bacterial leaf blight.

Efficacy of Rice Hull Ash against Bacterial Leaf Blight, Xanthomonas Oryzae pv. Oryzae

Efficacy of Rice Hull Ash against Bacterial Leaf Blight, Xanthomonas Oryzae pv. Oryzae