Sheath Blight Research Articles

Jasmonic acid limits Rhizoctonia solani AG1-IA infection in rice by modulating reactive oxygen species homeostasis

Sheath blight disease of rice caused by a soil-borne fungal pathogen Rhizoctonia solani AG1-IA is one of the major threats to rice production globally. During host-pathogen interactions, reactive oxygen species (ROS) play an important role in pathogen virulence and plant defense. For example, necrotrophic pathogens induce ROS production to damage host cells, whereas the host can incite ROS to kill the pathogen. From the host perspective, it is essential to understand how the antioxidant machinery maintains a delicate balance of ROS to protect itself from its lethal effects. Here, we investigated the pathogen-induced accumulation of ROS and implicated damage in two rice genotypes (PR114, susceptible; ShB, moderately tolerant) varying in the level of susceptibility to R. solani AG1-IA. Compared to PR114, ShB exhibited a better antioxidant response and reasonably lesser oxidative damage. Further, we observed elevated levels of jasmonic acid (JA) in ShB, which was otherwise decreased in PR114 in response to pathogen infection. As depicted, an elevated level of JA was in agreement with the expression profiles of genes involved in its biosynthesis and signaling. To further ascertain if the heightened antioxidant response is JA-dependent or independent, methyl jasmonate (MeJA) was exogenously applied to PR114, and antioxidant response in terms of gene expression, enzyme activities, and oxidative damage was studied in R. solani infected samples. Surprisingly, the exogenous application of MeJA complemented the antioxidant response and reduced oxidative damage in PR114, thus suggesting that the antioxidant defense system is under transcriptional control of JA.

Genetic Characterization of the Partial Disease Resistance of Rice to Bacterial Panicle Blight and Sheath Blight by Combined QTL Linkage and QTL-seq Analyses.

Bacterial panicle blight (BPB) and sheath blight (SB) are major diseases of rice and few cultivars have shown a high level of resistance to these diseases. A recombinant inbred line (RIL) population developed from the U.S. cultivars Jupiter (moderately resistant) and Trenasse (susceptible) was investigated to identify loci associated with the partial disease resistance to BPB and SB. Disease phenotypes in BPB and SB, as well as the days-to-heading (DTH) trait, were evaluated in the field. DTH was correlated to BPB and SB diseases, while BPB was positively correlated to SB in the field trials with this RIL population. Genotyping was performed using Kompetitive Allele Specific PCR (KASP) assays and whole-genome sequence (WGS) analyses. Quantitative trait locus (QTL) mapping and bulk segregant analysis using a set of WGS data (QTL-seq) detected a major QTL on the upper arm of chromosome 3 for BPB, SB, and DTH traits within the 1.0-1.9 Mb position. Additional QTLs associated with BPB and SB were also identified from other chromosomes by the QTL-seq analysis. The QTLs identified in this study contain at least nine candidate genes that are predicted to have biological functions in defense or flowering. These findings provide an insight into the complex nature of the quantitative resistance to BPB and SB, which may also be closely linked to the flowering trait.

Elevated CO2 and temperature under future climate change increase severity of rice sheath blight.

Sheath blight (ShB), caused by Rhizoctonia solani, is one of the major threats to rice (Oryza sativa L.) production. However, it is not clear how the risk of rice ShB will respond to elevated CO2 and temperature under future climate change. Here, we conducted, field experiments of inoculated R. solani under combinations of two CO2 levels (ambient and enriched up to 590 μmol mol-1) and two temperature levels (ambient and increased by 2.0°C) in temperature by free-air CO2 enrichment (T-FACE) system for two cultivars (a susceptible cultivar, Lemont and a resistant cultivar, YSBR1). Results indicate that for the inoculation of plants with R. solani, the vertical length of ShB lesions for cv. Lemont was significantly longer than that for cv. YSBR1 under four CO2 and temperature treatments. The vertical length of ShB lesions was significantly increased by elevated temperature, but not by elevated CO2, for both cultivars. The vertical length of ShB lesions under the combination of elevated CO2 and elevated temperature was increased by 21-38% for cv. Lemont and by -1-6% for cv. YSBR1. A significant increase in MDA level was related to a significant increase in the vertical length of ShB lesions under the combination of elevated CO2 and elevated temperature. Elevated CO2 could not compensate for the negative effect of elevated temperature on yield of both cultivars under future climate change. Rice yield and biomass were further decreased by 2.0-2.5% and 2.9-4.2% by an increase in the severity of ShB under the combination of elevated CO2 and elevated temperature. Thus, reasonable agronomic management practices are required to improve both resistance to ShB disease and grain yield for rice under future climate change.

Morpho-genetic variability of Rhizoctonia solani population causing sheath blight disease in rice (Oryza sativa L.)

Aim: The present study aims to investigate the morpho-pathological and molecular variability among the R. solani isolates from different geographical regions of India. Methodology: R. solani isolates were collected from sheath blight infected rice plants from diverse regions of Western Uttar Pradesh and Uttarakhand. Morphological variability among the isolates was studied in-vitro on PDA medium. The anastomosis grouping was determined by hyphal fusion reactions paired with tester strain and confirmed by AG-specific-PCR assay. Pathogenicity assay was conducted in-vivo on four rice varieties using artificial inoculation method under greenhouse conditions. Evolutionary relationship among the isolates was determined using rDNA-ITS-PCR with ITS1 & ITS4 primers. Further, genetic variability among the isolates was assessed using ISSR primers. Results: A total of 21 isolates of R. solani were recovered and based on morphological and sclerotial features, significant variation was observed among the isolates. All the isolates belonged to AG1-IA group which was confirmed by AG-specific PCR assay. Based on pathogenicity, eight isolates were found highly virulent, eight were moderately virulent and six were less virulent. ISSR markers showed high level of polymorphism and grouped all isolates into three major clusters showing partial correlation with geographical origin of the isolates. Sequence variations in ITS region were observed in the form of insertions or deletions of the nucleotide when rDNA-ITS sequences were compared that led to the interspecies diversity and diversity was observed in clad-specific manner. The phylogenetic tree separated the isolates into ten distinct clades showing high level of genetic diversity. Interpretation: The results of the present study may be helpful for the phylogenetic classification of complex R. solani species and provide information on the genetic divergence and occurrence of pathogenic races. This information will be helpful for the development of effective disease management strategies based on the molecular breeding and other approaches. Key words: Anastomosis, Genetic diversity, ISSR, Pathogenicity, R. solani, Sheath blight

Calcineurin B-like interacting protein kinase 31 confers resistance to sheath blight via modulation of ROS homeostasis in rice.

Sheath blight (ShB) severely threatens rice cultivation and production; however, the molecular mechanism of rice defence against ShB remains unclear. Screening of transposon Ds insertion mutants identified that Calcineurin B-like protein-interacting protein kinase 31 (CIPK31) mutants were more susceptible to ShB, while CIPK31 overexpressors (OX) were less susceptible. Sequence analysis indicated two haplotypes of CIPK31: Hap_1, with significantly higher CIPK31 expression, was less sensitive to ShB than the Hap_2 lines. Further analyses showed that the NAF domain of CIPK31 interacted with the EF-hand motif of respiratory burst oxidase homologue (RBOHA) to inhibit RBOHA-induced H2 O2 production, and RBOHA RNAi plants were more susceptible to ShB. These data suggested that the CIPK31-mediated increase in resistance is not associated with RBOHA. Interestingly, the study also found that CIPK31 interacted with catalase C (CatC); cipk31 mutants accumulated less H2 O2 while CIPK31 OX accumulated more H2 O2 compared to the wild-type control. Further analysis showed the interaction of the catalase domain of CatC with the NAF domain of CIPK31 by which CIPK31 inhibits CatC activity to accumulate more H2 O2 .

Nanoparticle carriers enhance RNA stability and uptake efficiency and prolong the protection against Rhizoctonia solani

Spray-induced gene silencing (SIGS) can inhibit plant diseases by topical application of double- (dsRNA) or single-stranded (sRNA) RNA molecules onto plants to silence virulence-related pathogen genes. However, the on-field application of SIGS is limited by the instability of naked RNA and low RNA uptake by pathogens. Nanoparticles have been used as RNA carriers to enhance RNA silencing. Rice sheath blight caused by Rhizoctonia solani (R. solani) is one of the most devastating fungal diseases in rice (Oryza sativa L.). In this study, we aimed to explore the protective effects of nanoparticle-delivered dsRNA against rice sheath blight. The key pathogenic genes, RsAGO1 and RsAGO2, of R. solani were screened as targets for dsRNA. Chitosan (CS), polyethyleneimine (PEI), protamine, carbon quantum dot (CQD), polyamidoamine (PAMAM), and chitosan/SPc complex (CSC) were selected as dsRNA carriers. All the evaluated nanoparticles could assemble with dsRNA to form nanoparticle-dsRNA complexes, and CQD and CSC showed improved dsRNA load capacity. Particularly, CSC could enhance the stability of dsRNA and cause a 7% reduction in fluorescence intensity after nuclease treatment. CSC and CS effectively enhanced the efficiency of dsRNA uptake by pathogens. Furthermore, CSC could reduce pathogen infection and prolong the protection time of dsRNA by up to 20 days. Overall, this study provides a novel and efficacious SIGS-based strategy for producing RNA-based fungicides.

Introgression of the QTL qSB11-1TT conferring sheath blight resistance in rice (Oryza sativa) into an elite variety, UKMRC 2, and evaluation of its backcross-derived plants.

Sheath blight (SB) is the most damaging fungal disease in rice caused by a soil-borne pathogenic fungus, Rhizoctonia solani Kuhn (R. solani). The disease resistance in rice is a complex quantitative trait controlled by a few major genes. UKMRC2 is a newly developed elite rice variety that possesses high yield potential but is susceptible to sheath blight disease indicating a huge risk of varietal promotion, mass cultivation, and large-scale adoption. The aim of our present study was the development of varietal resistance against R. solani in UKMRC2 to enhance its stability and durability in a wide range of environments and to validate the effects of an SB-resistance QTL on the new genetic background. In our study, we developed 290 BC1F1 backcross progenies from a cross between UKMRC2 and Tetep to introgress the QTL qSBR11-1TT into the UKMRC2 genetic background. Validation of the introgressed QTL region was performed via QTL analysis based on QTL-linked SSR marker genotyping and phenotyping against R. solani artificial field inoculation techniques. The QTL qSBR11-1TT was then authenticated with the results of LOD score (3.25) derived from composite interval mapping, percent phenotypic variance explained (14.6%), and additive effect (1.1) of the QTLs. The QTL region was accurately defined by a pair of flanking markers K39512 and RM7443 with a peak marker RM27360. We found that the presence of combination of alleles, RM224, RM27360 and K39512 demonstrate an improved resistance against the disease rather than any of the single allele. Thus, the presence of the QTL qSBR11-1TT has been validated and confirmed in the URMRC2 genetic background which reveals an opportunity to use the QTL linked with these resistance alleles opens an avenue to resume sheath blight resistance breeding in the future with marker-assisted selection program to boost up resistance in rice varieties.

Rice Plaque Detection and Identification Based on an Improved Convolutional Neural Network

Rice diseases are extremely harmful to rice growth, and achieving the identification and rapid classification of rice disease spots is an essential means to promote intelligent rice production. However, due to the large variety of rice diseases and the similar appearance of some rice diseases, the existing deep learning methods are less effective at classification and detection. Aiming at such problems, this paper took the spot images of five common rice diseases as the research object and constructed a rice disease data set containing 2500 images of rice bacterial blight, sheath blight, flax leaf spot, leaf streak and rice blast, including 500 images of each disease. An improved lightweight deep learning network model was proposed to realize the accurate identification of disease types and disease spots. A rice disease image classification network was designed based on the RlpNet (rice leaf plaque net) network model, Which is the underlying network, in addition to the YOLOv3 target detection network model in order to achieve the optimization of the feature extraction link, i.e., upsampling by transposed convolution and downsampling by dilated convolution. The improved YOLOv3 model was compared with traditional convolutional neural network models, including the AlexNet, GoogLeNet, VGG-16 and ResNet-34 models, for disease recognition, and the results showed that the average recall, average precision, average F1-score and overall accuracy of the network model for rice disease classification were 91.84%, 92.14%, 91.87% and 91.84%, respectively, which were all improved compared with the traditional algorithms. The improved YOLOv3 network model was compared with FSSD, Faster-RCNN, YOLOv3 and YOLOv4 for spot detection studies, and the results showed that it could achieve a mean average precision (mAP) of 86.72%, a detection rate (DR) of 93.92%, a frames per second (FPS) rate of 63.4 and a false alarm rate (FAR) of only 5.12%. In summary, the comprehensive performance of the proposed model was better than that of the traditional YOLOv3 algorithm, so this study provides a new method for rice disease identification and disease spot detection. It also had good performance in terms of the common detection and classification of multiple rice diseases, which provides some support for the common differentiation of multiple rice diseases and has some practical application value.

Durable Resistance of Rice to Major and Emerging Diseases: Present Status

Background Rice (Oryza sativa) is one of the most dominating cereal crop and half of the global people have chosen it as staple food. Rice production has increased significantly but the productivity is not increased significantly to combat the global need. One of the major constraints of low productivity is biotic stresses faced by rice growers. Some of the important biotic stresses of rice are major diseases like brown spot, bacterial blight, blast, sheath blight and, few emerging but significant diseases like false smut, bakanae and sheath rot play crucial role in reducing yield per unit area and quality of rice. Host plant resistance is the most effective, economic and eco-friendly approach of mitigating disease like biotic stress problem. Objective The objective of this review is to compile data related to resistance in rice against various major and emerging diseases as well as their application to develop gene pyramided varieties that increase resistance to those pathogens to achieve durable resistance. Methods Diseases are one of the most important constraints for sustainable or demanding production level as well as maintaining different quality parameters of the rice. Different management practices including majority by chemical means are not always solution as it add production cost many times vis-à-vis cause pollution in every aspect. Thus, development of durable resistant varieties are the best approaches. Result An array of robust molecular markers and genetic map of the crop has made application of marker assisted selection possible for the traits controlled by resistant genes or quantitative trait loci (QTLs) to induce durable resistance in the crop. Conclusion A comprehensive assessment on identification, sources and deployment of resistance genes/QTLs of major and emerging diseases of rice will help in development of varieties of rice with durable resistant to major and emerging disease-causing pathogens.

Genome Resource of Rhizoctonia solani Anastomosis Group 4 Strain AG4-JY, a Pathomycete of Sheath Blight of Foxtail Millet.

The basidiomycetous fungus Rhizoctonia solani Kühn (teleomorph Thanatephorus cucumeris [Frank] Donk) is a fungal pathogen that causes various diseases on economically important crops, such as foxtail millet, maize, and rice. Using the PacBio Sequel platform, we assembled a draft genome of an R. solani strain AG4-JY that was isolated from foxtail millet with sheath blight at the stem. The genome was approximately 43.43 Mb on 53 scaffolds, with a scaffold N50 length of 2.10 Mb. In all, 10,545 genes and 179 noncoding RNAs were predicted, and 10,488 genes had at least one database annotation. In addition, the proteins encoded by 709 genes were predicted as secretory proteins. The AG4-JY genome sequence provides a valuable resource for understanding the interactions between R. solani and foxtail millet and controls sheath blight in the world.

Biological Control Efficacy of Bacillus sp. REB711 on Sheath Blight of Rice

Sheath blight (ShB), caused by Rhizoctonia solani, is one of the economically important rice diseases in Louisiana and other rice-growing regions. Fungicides are used to manage ShB, but such chemical methods are not economically or ecologically sustainable. To develop new biological control agents for the management of ShB, bacteria isolated from rice plants in the field were initially screened in the laboratory based on their antagonistic activities against R. solani through plate assays that exhibit growth inhibition of the fungal pathogen. The efficacy of three selected strains of Bacillus spp. (RAB14R, REB711, and RRB985) in suppression of ShB was further evaluated under the greenhouse and field conditions. In field trials conducted in 2017 and 2018, foliar spray of Bacillus sp. REB711 significantly reduced the development of ShB compared with the nontreated control, although it was less effective than the azoxystrobin fungicide Quadris. In greenhouse tests, Bacillus sp. REB711 significantly reduced ShB development (disease severity and lesion length) through seed treatment, whereas the other two strains of Bacillus spp. did not. The observed efficacy of Bacillus sp. REB711 could result from competition, antibiosis, and/or induction of the plant defense system and suggests that this bacterial strain could be used as a potential biological agent for managing ShB by itself or in combination with fungicides to reduce the risk of fungicide resistance.

Sustainable management of sheath blight in rice (Rhizoctonia solani Kuhn)

A study was done to explore the various strategies to manage sheath blight of rice. During kharif 2018 and 2019, different treatments viz., foliar and soil application of Trichoderma viride, Pseudomonas fluorescens, mustard and radish leaf and their combination were applied at 30 and 60 days after transplanting (DAT), parameters such as disease severity, grain chaffiness, plant height and yield were evaluated at 45 and 75 DAT. Foliar application of propiconazole 25% EC @ 0.1% was most effective (50%-75.01%) followed by soil application of mustard leaf @ 5 kg/plot before transplanting and foliar application of P. fluorescens @ 5 g/L whereas foliar application of T. viride @ 5 g/L (9.64% and 46. 64%) was least effective. The foliar application of propiconazole 25% EC @ 0.1% recorded lowest percent of chaffiness (11-15%), highest yield of 4941.7-4991.7 kg/ha, whereas foliar application of T. viride @ 5 g/L showed highest percent of chaffiness (28.67-36.67%) with 3516.7-3475 kg/ha.

Sustainable management of sheath blight in rice (Rhizoctonia solani Kuhn)

Sustainable management of sheath blight in rice (Rhizoctonia solani Kuhn)

Rice Sheath Blight: A Comprehensive Review on the Disease and Recent Management Strategies

Rice Sheath Blight: A Comprehensive Review on the Disease and Recent Management Strategies

Identification of resistant sources and evaluation of biocontrol agents for suppression of banded leaf and sheath blight in little millet (Panicum sumatrense)

Identification of resistant sources and evaluation of biocontrol agents for suppression of banded leaf and sheath blight in little millet (Panicum sumatrense)

Effect of weather variables on banded leaf and sheath blight (Rhizoctonia solani f. sp. sasakii) of fodder maize and its integrated management

Effect of weather variables on banded leaf and sheath blight (Rhizoctonia solani f. sp. sasakii) of fodder maize and its integrated management

UGVs for Agri Spray with AI assisted Paddy Crop disease Identification

This research work involves data access and control of Unmanned Ground Vehicles (UGVs) which is designed for health monitoring of paddy crops as an exception from traditional monitoring system. The proposed scheme of autonomous navigation of drones is planned to be carried out as per the six milestones for disease detection and control in paddy crops. Drones serve as Unmanned Robotic Vehicles (URV) capable of performing desired tasks in unstructured, uncertain and potentially hostile environments and are remotely-operated without human intervention. URVs function completely as autonomous entities in diversified environments. Current UGVs adhere to different levels of automaticity. Typically the vehicle follows high level waypoints spaced for few hundred meters of distance to provide monitoring of agricultural fields and early detection of the various diseases that may occur in the paddy fields in a polyhouse. To increase the vehicle's abilities, tracking efficiency, obstacle avoidance, path planning or lead and follow up augmented control with Fuzzy Logic Controller (FLC) is incorporated. The distributed autonomous system for information gathering related to the paddy crops in polyhouse is enabled using different sensors, which is a data-intensive task. To increase the robustness of the system, fuzzy controllers are proposed to control the navigation of the proposed UGV in “All terrain conditions”. They are needed to offer problem specific heuristic control knowledge for the Inference Engine Design which occurs due to imprecision and uncertainty of the sensor readings. It also requires low computation time which favours the polyhouse situations. The navigation of UGV and the FLC action will in turn depend on “All terrain traversability” and “dead zone” monitoring. The proposed UGV model is capable of measuring the parameters associated with the paddy crops inside a polyhouse. The various diseases in paddy crops are False Smut (FS), Sheath Blight (SB), Rice Blast (RB), Leaf Scald (LS), Brown Spot (BS), Bacterial Leaf Blight (BLB) and Bakane (BE) which are detected using Convolutional Neural Network (CNN).

Integrated disease management of banded leaf and sheath blight caused by Rhizoctonia solani in proso millet

Integrated disease management of banded leaf and sheath blight caused by Rhizoctonia solani in proso millet

Performance of Peddapuram Station Maize Pre Release Hybrids to different diseases in all India testing during Kharif 2022

Diseases caused by pathogens are one among the major causes of yield loss in maize. These diseases not only affect its yield but can greatly impair the quality and year-wise stability of production, undermining the efforts to promote sustainable agriculture. Moreover, environmental and health hazards, resulting from the non-judicious application of numerous chemical fungicides are another cause of concern. Though maize is affected by more than 60 diseases, in India about a dozen are of serious concern. The four major diseases viz; turcicum leaf blight (TLB), maydis leaf blight (MLB), post-flowering stalk rots (PFSR), and banded leaf and sheath blight (BLSB) are of national importance. Host plant resistance (HPR) is considered to be most practical, feasible and effective way to control plant diseases. Though diseases can be managed through chemicals, these are neither farmer- nor environment-friendly. These are serious threat to soil and human health too. Further use of chemicals makes maize cultivation costly, reducing profit margin. Therefore, exploitation of HPR helps in minimizing inoculum in soil and yield loss in an eco-friendly and economic manner. One of the best approaches to address different diseases is to identify highly tolerant or resistant genotypes that can be used for genetic improvement. In present investigation three hybrids PH 22-420146, PH 22-420186 and PH 22-420208 were screened against major diseases of maize in different locations in India, among these PH 22-420208 showed resistance to Fusarium stalk rot, Curvularia leaf spot, sorghum downy mildew, Rajasthan downy mildew diseases and moderately resistance to maydis leaf blight, Charcoal rot and banded leaf and sheath blight diseases.

Management of sheath blight of rice using Bacillus amyloliquefaciens based biofungicide

Management of sheath blight of rice using Bacillus amyloliquefaciens based biofungicide