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Observations in Malaya on bud-rot of coconuts

Sharples A, Lambourne J

Ann Bot, 1922;os-36:55-70.
DOI: 10.1093/oxfordjournals.aob.a089787
Matched MeSH terms: Plant Diseases
Modelling induced resistance to plant diseases

Abdul Latif NS, Wake GC, Reglinski T, Elmer PA

J Theor Biol, 2014 Apr 21;347:144-50.
PMID: 24398025 DOI: 10.1016/j.jtbi.2013.12.023

Plant disease control has traditionally relied heavily on the use of agrochemicals despite their potentially negative impact on the environment. An alternative strategy is that of induced resistance (IR). However, while IR has proven effective in controlled environments, it has shown variable field efficacy, thus raising questions about its potential for disease management in a given crop. Mathematical modelling of IR assists researchers with understanding the dynamics of the phenomenon in a given plant cohort against a selected disease-causing pathogen. Here, a prototype mathematical model of IR promoted by a chemical elicitor is proposed and analysed. Standard epidemiological models describe that, under appropriate environmental conditions, Susceptible plants (S) may become Diseased (D) upon exposure to a compatible pathogen or are able to Resist the infection (R) via basal host defence mechanisms. The application of an elicitor enhances the basal defence response thereby affecting the relative proportion of plants in each of the S, R and D compartments. IR is a transient response and is modelled using reversible processes to describe the temporal evolution of the compartments. Over time, plants can move between these compartments. For example, a plant in the R-compartment can move into the S-compartment and can then become diseased. Once in the D-compartment, however, it is assumed that there is no recovery. The terms in the equations are identified using established principles governing disease transmission and this introduces parameters which are determined by matching data to the model using computer-based algorithms. These then give the best match of the model with experimental data. The model predicts the relative proportion of plants in each compartment and quantitatively estimates elicitor effectiveness. An illustrative case study will be given; however, the model is generic and will be applicable for a range of plant-pathogen-elicitor scenarios.

Matched MeSH terms: Plant Diseases*
A laudable strategy to manage bacterial panicle blight disease of rice using biocontrol agents

Ngalimat MS, Mohd Hata E, Zulperi D, Ismail SI, Ismail MR, Mohd Zainudin NAI, et al.

J Basic Microbiol, 2023 Nov;63(11):1180-1195.
PMID: 37348082 DOI: 10.1002/jobm.202300182

Bacterial panicle blight (BPB) disease is a dreadful disease in rice-producing countries. Burkholderia glumae, a Gram-negative, rod-shaped, and flagellated bacterium was identified as the primary culprit for BPB disease. In 2019, the disease was reported in 18 countries, and to date, it has been spotted in 26 countries. Rice yield has been reduced by up to 75% worldwide due to this disease. Interestingly, the biocontrol strategy offers a promising alternative to manage BPB disease. This review summarizes the management status of BPB disease using biological control agents (BCA). Bacteria from the genera Bacillus, Burkholderia, Enterobacter, Pantoea, Pseudomonas, and Streptomyces have been examined as BCA under in vitro, glasshouse, and field conditions. Besides bacteria, bacteriophages have also been reported to reduce BPB pathogens under in vitro and glasshouse conditions. Here, the overview of the mechanisms of bacteria and bacteriophages in controlling BPB pathogens is addressed. The applications of BCA using various delivery methods could effectively manage BPB disease to benefit the agroecosystems and food security.

Matched MeSH terms: Plant Diseases/microbiology; Plant Diseases/prevention & control
Fulltext Phylogenomic Analysis of a 55.1-kb 19-Gene Dataset Resolves a Monophyletic Fusarium that Includes the Fusarium solani Species Complex

Geiser DM, Al-Hatmi AMS, Aoki T, Arie T, Balmas V, Barnes I, et al.

Phytopathology, 2021 Jul;111(7):1064-1079.
PMID: 33200960 DOI: 10.1094/PHYTO-08-20-0330-LE

Scientific communication is facilitated by a data-driven, scientifically sound taxonomy that considers the end-user's needs and established successful practice. In 2013, the Fusarium community voiced near unanimous support for a concept of Fusarium that represented a clade comprising all agriculturally and clinically important Fusarium species, including the F. solani species complex (FSSC). Subsequently, this concept was challenged in 2015 by one research group who proposed dividing the genus Fusarium into seven genera, including the FSSC described as members of the genus Neocosmospora, with subsequent justification in 2018 based on claims that the 2013 concept of Fusarium is polyphyletic. Here, we test this claim and provide a phylogeny based on exonic nucleotide sequences of 19 orthologous protein-coding genes that strongly support the monophyly of Fusarium including the FSSC. We reassert the practical and scientific argument in support of a genus Fusarium that includes the FSSC and several other basal lineages, consistent with the longstanding use of this name among plant pathologists, medical mycologists, quarantine officials, regulatory agencies, students, and researchers with a stake in its taxonomy. In recognition of this monophyly, 40 species described as genus Neocosmospora were recombined in genus Fusarium, and nine others were renamed Fusarium. Here the global Fusarium community voices strong support for the inclusion of the FSSC in Fusarium, as it remains the best scientific, nomenclatural, and practical taxonomic option available.

Matched MeSH terms: Plant Diseases
Pattern and causes of the establishment of the invasive bacterial potato pathogen Dickeya solani and of the maintenance of the resident pathogen D. dianthicola

Blin P, Robic K, Khayi S, Cigna J, Munier E, Dewaegeneire P, et al.

Mol Ecol, 2021 01;30(2):608-624.
PMID: 33226678 DOI: 10.1111/mec.15751

Invasive pathogens can be a threat when they affect human health, food production or ecosystem services, by displacing resident species, and we need to understand the cause of their establishment. We studied the patterns and causes of the establishment of the pathogen Dickeya solani that recently invaded potato agrosystems in Europe by assessing its invasion dynamics and its competitive ability against the closely related resident D. dianthicola species. Epidemiological records over one decade in France revealed the establishment of D. solani and the maintenance of the resident D. dianthicola in potato fields exhibiting blackleg symptoms. Using experimentations, we showed that D. dianthicola caused a higher symptom incidence on aerial parts of potato plants than D. solani, while D. solani was more aggressive on tubers (i.e. with more severe symptoms). In co-infection assays, D. dianthicola outcompeted D. solani in aerial parts, while the two species co-existed in tubers. A comparison of 76 D. solani genomes (56 of which have been sequenced here) revealed balanced frequencies of two previously uncharacterized alleles, VfmBPro and VfmBSer , at the vfmB virulence gene. Experimental inoculations showed that the VfmBSer population was more aggressive on tubers, while the VfmBPro population outcompeted the VfmBSer population in stem lesions, suggesting an important role of the vfmB virulence gene in the ecology of the pathogens. This study thus brings novel insights allowing a better understanding of the pattern and causes of the D.solani invasion into potato production agrosystems, and the reasons why the endemic D. dianthicola nevertheless persisted.

Matched MeSH terms: Plant Diseases/microbiology*
Fulltext Exploring the potential of Bornean polypore fungi as biological control agents against pathogenic Ganoderma boninense causing basal stem rot in oil palm

Darlis D, Jalloh MB, Chin CFS, Basri NKM, Besar NA, Ahmad K, et al.

Sci Rep, 2023 Jun 26;13(1):10316.
PMID: 37365214 DOI: 10.1038/s41598-023-37507-0

Basal stem rot due to a fungal pathogen, Ganoderma boninense, is one of the most devastating diseases in oil palm throughout the major palm oil producer countries. This study investigated the potential of polypore fungi as biological control agents against pathogenic G. boninense in oil palm. In vitro antagonistic screening of selected non-pathogenic polypore fungi was performed. Based on in planta fungi inoculation on oil palm seedlings, eight of the 21 fungi isolates tested (GL01, GL01, RDC06, RDC24, SRP11, SRP12, SRP17, and SRP18) were non-pathogenic. In vitro antagonistic assays against G. boninense revealed that the percentage inhibition of radial growth (PIRG) in dual culture assay for SRP11 (69.7%), SRP17 (67.3%), and SRP18 (72.7%) was relatively high. Percentage inhibition of diameter growth (PIDG) in volatile organic compounds (VOCs) in dual plate assay of SRP11, SRP17, and SRP18 isolates were 43.2%, 51.6%, and 52.1%, respectively. Molecular identification using the internal transcribed spacer gene sequences of SRP11, SRP17, and SRP18 isolates revealed that they were Fomes sp., Trametes elegans, and Trametes lactinea, respectively.

Matched MeSH terms: Plant Diseases/microbiology
Transcriptional effects of carbon and nitrogen starvation on Ganoderma boninense, an oil palm phytopathogen

Nagappan J, Ooi SE, Chan KL, Kadri F, Nurazah Z, Halim MAA, et al.

Mol Biol Rep, 2024 Jan 25;51(1):212.
PMID: 38273212 DOI: 10.1007/s11033-023-09054-4

BACKGROUND: Ganoderma boninense is a phytopathogen of oil palm, causing basal and upper stem rot diseases.
METHODS: The genome sequence was used as a reference to study gene expression during growth in a starved carbon (C) and nitrogen (N) environment with minimal sugar and sawdust as initial energy sources. This study was conducted to mimic possible limitations of the C-N nutrient sources during the growth of G. boninense in oil palm plantations.
RESULTS: Genome sequencing of an isolate collected from a palm tree in West Malaysia generated an assembly of 67.12 Mb encoding 19,851 predicted genes. Transcriptomic analysis from a time course experiment during growth in this starvation media identified differentially expressed genes (DEGs) that were found to be associated with 29 metabolic pathways. During the active growth phase, 26 DEGs were related to four pathways, including secondary metabolite biosynthesis, carbohydrate metabolism, glycan metabolism and mycotoxin biosynthesis. G. boninense genes involved in the carbohydrate metabolism pathway that contribute to the degradation of plant cell walls were up-regulated. Interestingly, several genes associated with the mycotoxin biosynthesis pathway were identified as playing a possible role in pathogen-host interaction. In addition, metabolomics analysis revealed six metabolites, maltose, xylobiose, glucooligosaccharide, glycylproline, dimethylfumaric acid and arabitol that were up-regulated on Day2 of the time course experiment.
CONCLUSIONS: This study provides information on genes expressed by G. boninense in metabolic pathways that may play a role in the initial infection of the host.

Matched MeSH terms: Plant Diseases/genetics
Fulltext Transcriptome Profiling of the Resistance Response of Musa acuminata subsp. burmannicoides, var. Calcutta 4 to Pseudocercospora musae

Pinheiro TDM, Rego ECS, Alves GSC, Fonseca FCA, Cotta MG, Antonino JD, et al.

Int J Mol Sci, 2022 Nov 05;23(21).
PMID: 36362377 DOI: 10.3390/ijms232113589

Banana (Musa spp.), which is one of the world's most popular and most traded fruits, is highly susceptible to pests and diseases. Pseudocercospora musae, responsible for Sigatoka leaf spot disease, is a principal fungal pathogen of Musa spp., resulting in serious economic damage to cultivars in the Cavendish subgroup. The aim of this study was to characterize genetic components of the early immune response to P. musae in Musa acuminata subsp. burmannicoides, var. Calcutta 4, a resistant wild diploid. Leaf RNA samples were extracted from Calcutta 4 three days after inoculation with fungal conidiospores, with paired-end sequencing conducted in inoculated and non-inoculated controls using lllumina HiSeq 4000 technology. Following mapping to the reference M. acuminata ssp. malaccensis var. Pahang genome, differentially expressed genes (DEGs) were identified and expression representation analyzed on the basis of gene ontology enrichment, Kyoto Encyclopedia of Genes and Genomes orthology and MapMan pathway analysis. Sequence data mapped to 29,757 gene transcript models in the reference Musa genome. A total of 1073 DEGs were identified in pathogen-inoculated cDNA libraries, in comparison to non-inoculated controls, with 32% overexpressed. GO enrichment analysis revealed common assignment to terms that included chitin binding, chitinase activity, pattern binding, oxidoreductase activity and transcription factor (TF) activity. Allocation to KEGG pathways revealed DEGs associated with environmental information processing, signaling, biosynthesis of secondary metabolites, and metabolism of terpenoids and polyketides. With 144 up-regulated DEGs potentially involved in biotic stress response pathways, including genes involved in cell wall reinforcement, PTI responses, TF regulation, phytohormone signaling and secondary metabolism, data demonstrated diverse early-stage defense responses to P. musae. With increased understanding of the defense responses occurring during the incompatible interaction in resistant Calcutta 4, these data are appropriate for the development of effective disease management approaches based on genetic improvement through introgression of candidate genes in superior cultivars.

Matched MeSH terms: Plant Diseases/genetics; Plant Diseases/microbiology
Fulltext The wheat Sr22, Sr33, Sr35 and Sr45 genes confer resistance against stem rust in barley

Hatta MAM, Arora S, Ghosh S, Matny O, Smedley MA, Yu G, et al.

Plant Biotechnol J, 2021 Feb;19(2):273-284.
PMID: 32744350 DOI: 10.1111/pbi.13460

In the last 20 years, stem rust caused by the fungus Puccinia graminis f. sp. tritici (Pgt), has re-emerged as a major threat to wheat and barley production in Africa and Europe. In contrast to wheat with 60 designated stem rust (Sr) resistance genes, barley's genetic variation for stem rust resistance is very narrow with only ten resistance genes genetically identified. Of these, only one complex locus consisting of three genes is effective against TTKSK, a widely virulent Pgt race of the Ug99 tribe which emerged in Uganda in 1999 and has since spread to much of East Africa and parts of the Middle East. The objective of this study was to assess the functionality, in barley, of cloned wheat Sr genes effective against race TTKSK. Sr22, Sr33, Sr35 and Sr45 were transformed into barley cv. Golden Promise using Agrobacterium-mediated transformation. All four genes were found to confer effective stem rust resistance. The barley transgenics remained susceptible to the barley leaf rust pathogen Puccinia hordei, indicating that the resistance conferred by these wheat Sr genes was specific for Pgt. Furthermore, these transgenic plants did not display significant adverse agronomic effects in the absence of disease. Cloned Sr genes from wheat are therefore a potential source of resistance against wheat stem rust in barley.

Matched MeSH terms: Plant Diseases/genetics*; Plant Diseases/microbiology
Fulltext Review of the State of the Art of Deep Learning for Plant Diseases: A Broad Analysis and Discussion

Hasan RI, Yusuf SM, Alzubaidi L

Plants (Basel), 2020 Oct 01;9(10).
PMID: 33019765 DOI: 10.3390/plants9101302

Deep learning (DL) represents the golden era in the machine learning (ML) domain, and it has gradually become the leading approach in many fields. It is currently playing a vital role in the early detection and classification of plant diseases. The use of ML techniques in this field is viewed as having brought considerable improvement in cultivation productivity sectors, particularly with the recent emergence of DL, which seems to have increased accuracy levels. Recently, many DL architectures have been implemented accompanying visualisation techniques that are essential for determining symptoms and classifying plant diseases. This review investigates and analyses the most recent methods, developed over three years leading up to 2020, for training, augmentation, feature fusion and extraction, recognising and counting crops, and detecting plant diseases, including how these methods can be harnessed to feed deep classifiers and their effects on classifier accuracy.

Matched MeSH terms: Plant Diseases
Fulltext Introgression of bacterial leaf blight (BLB) resistant gene, Xa7 into MARDI elite variety, MR219 by marker assisted backcrossing (MABC) approach

Yazid SN, Ahmad K, Razak MSFA, Rahman ZA, Ramachandran K, Mohamad SNA, et al.

Braz J Biol, 2021;84:e248359.
PMID: 34730685 DOI: 10.1590/1519-6984.248359

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.

Matched MeSH terms: Plant Diseases/genetics
Fulltext Molecular profiling of bacterial blight resistance in Malaysian rice cultivars

Javed MA, Ali SW, Ashfaq M, Tabassam J, Ali M, IhsanUllah M, et al.

Braz J Biol, 2022;82:e256189.
PMID: 36541981 DOI: 10.1590/1519-6984.256189

Bacteria blight is one of the most serious bacterial diseases of rice worldwide. The identification of genetic potential against bacterial blight in the existing rice resources is a prerequisite to develop multigenic resistance to combat the threat of climate change. This investigation was conducted to evaluate alleles variation in 38 Malaysian cultivars using thirteen Simple Sequences Repeats markers and one Sequence Tagged Sites (STS) marker which were reported to be linked with the resistance to bacterial blight. Based on molecular data, a dendrogram was constructed which classified the rice cultivars into seven major clusters at 0.0, 0.28 and 0.3 of similarity coefficient. Cluster 5 was the largest group comprised of ten rice cultivars where multiple genes were identified. However, xa13 could not be detected in the current rice germplasm, whereas xa2 was detected in 25 cultivars. Molecular analysis revealed that Malaysian rice cultivars possess multigenic resistance.

Matched MeSH terms: Plant Diseases/genetics
Evidence for high gene flow, nonrandom mating, and genetic bottlenecks of Ganoderma boninense infecting oil palm (Elaeis guineensis Jacq.) plantations in Malaysia and Indonesia

Wong WC, Tung HJ, Nurul Fadhilah M, Midot F, Lau SYL, Melling L, et al.

Mycologia, 2022;114(6):947-963.
PMID: 36239960 DOI: 10.1080/00275514.2022.2118512

Ganoderma boninense, the causal agent of basal stem rot (BSR) disease, has been recognized as a major economic threat to commercial plantings of oil palm (Elaeis guineensis Jacq.) in Southeast Asia, which supplies 86% of the world's palm oil. High genetic diversity and gene flow among regional populations of 417 G. boninense isolates collected from Sabah, Sarawak, and Peninsular Malaysia (Malaysia) and Sumatra (Indonesia) were demonstrated using 16 microsatellite loci. Three genetic clusters and different admixed populations of G. boninense across regions were detected, and they appeared to follow the spread of the fungus from the oldest (Peninsular Malaysia and Sumatra) to younger generations of oil palm plantings (Sabah and Sarawak). Low spatial genetic differentiation of G. boninense (FST = 0.05) among the sampling regions revealed geographically nonrestricted gene dispersal, but isolation by distance was still evident. Analysis of molecular variance (AMOVA) confirmed the little to no genetic differentiation among the pathogen populations and the three genetic clusters defined by STRUCTURE and minimum spanning network. Despite G. boninense being highly outcrossing and spread by sexual spores, linkage disequilibrium was detected in 7 of the 14 populations. Linkage disequilibrium indicated that the reproduction of the fungus was not entirely by random mating and genetic drift could be an important structuring factor. Furthermore, evidence of population bottleneck was indicated in the oldest oil palm plantations as detected in genetic clusters 2 and 3, which consisted mainly of Peninsular Malaysia and Sumatra isolates. The population bottleneck or founding event could have arisen from either new planting or replanting after the removal of large number of palm hosts. The present study also demonstrated that migration and nonrandom mating of G. boninense could be important for survival and adaptation to new palm hosts.

Matched MeSH terms: Plant Diseases/microbiology
Fulltext Recent advances in the understanding of Xanthomonas citri ssp. citri pathogenesis and citrus canker disease management

Ference CM, Gochez AM, Behlau F, Wang N, Graham JH, Jones JB

Mol Plant Pathol, 2018 Jun;19(6):1302-1318.
PMID: 29105297 DOI: 10.1111/mpp.12638

Taxonomic status: Bacteria; Phylum Proteobacteria; Class Gammaproteobacteria; Order Xanthomonadales; Family Xanthomonadaceae; Genus Xanthomonas; Species Xanthomonas citri ssp. citri (Xcc). Host range: Compatible hosts vary in their susceptibility to citrus canker (CC), with grapefruit, lime and lemon being the most susceptible, sweet orange being moderately susceptible, and kumquat and calamondin being amongst the least susceptible. Microbiological properties: Xcc is a rod-shaped (1.5-2.0 × 0.5-0.75 µm), Gram-negative, aerobic bacterium with a single polar flagellum. The bacterium forms yellow colonies on culture media as a result of the production of xanthomonadin. Distribution: Present in South America, the British Virgin Islands, Africa, the Middle East, India, Asia and the South Pacific islands. Localized incidence in the USA, Argentina, Brazil, Bolivia, Uruguay, Senegal, Mali, Burkina Faso, Tanzania, Iran, Saudi Arabia, Yemen and Bangladesh. Widespread throughout Paraguay, Comoros, China, Japan, Malaysia and Vietnam. Eradicated from South Africa, Australia and New Zealand. Absent from Europe.

Matched MeSH terms: Plant Diseases/microbiology*
Fulltext Plant Disease Detection and Classification: A Systematic Literature Review

Ramanjot, Mittal U, Wadhawan A, Singla J, Jhanjhi NZ, Ghoniem RM, et al.

Sensors (Basel), 2023 May 15;23(10).
PMID: 37430683 DOI: 10.3390/s23104769

A significant majority of the population in India makes their living through agriculture. Different illnesses that develop due to changing weather patterns and are caused by pathogenic organisms impact the yields of diverse plant species. The present article analyzed some of the existing techniques in terms of data sources, pre-processing techniques, feature extraction techniques, data augmentation techniques, models utilized for detecting and classifying diseases that affect the plant, how the quality of images was enhanced, how overfitting of the model was reduced, and accuracy. The research papers for this study were selected using various keywords from peer-reviewed publications from various databases published between 2010 and 2022. A total of 182 papers were identified and reviewed for their direct relevance to plant disease detection and classification, of which 75 papers were selected for this review after exclusion based on the title, abstract, conclusion, and full text. Researchers will find this work to be a useful resource in recognizing the potential of various existing techniques through data-driven approaches while identifying plant diseases by enhancing system performance and accuracy.

Matched MeSH terms: Plant Diseases*
Fulltext PND-Net: plant nutrition deficiency and disease classification using graph convolutional network

Bera A, Bhattacharjee D, Krejcar O

Sci Rep, 2024 Jul 05;14(1):15537.
PMID: 38969738 DOI: 10.1038/s41598-024-66543-7

Crop yield production could be enhanced for agricultural growth if various plant nutrition deficiencies, and diseases are identified and detected at early stages. Hence, continuous health monitoring of plant is very crucial for handling plant stress. The deep learning methods have proven its superior performances in the automated detection of plant diseases and nutrition deficiencies from visual symptoms in leaves. This article proposes a new deep learning method for plant nutrition deficiencies and disease classification using a graph convolutional network (GNN), added upon a base convolutional neural network (CNN). Sometimes, a global feature descriptor might fail to capture the vital region of a diseased leaf, which causes inaccurate classification of disease. To address this issue, regional feature learning is crucial for a holistic feature aggregation. In this work, region-based feature summarization at multi-scales is explored using spatial pyramidal pooling for discriminative feature representation. Furthermore, a GCN is developed to capacitate learning of finer details for classifying plant diseases and insufficiency of nutrients. The proposed method, called Plant Nutrition Deficiency and Disease Network (PND-Net), has been evaluated on two public datasets for nutrition deficiency, and two for disease classification using four backbone CNNs. The best classification performances of the proposed PND-Net are as follows: (a) 90.00% Banana and 90.54% Coffee nutrition deficiency; and (b) 96.18% Potato diseases and 84.30% on PlantDoc datasets using Xception backbone. Furthermore, additional experiments have been carried out for generalization, and the proposed method has achieved state-of-the-art performances on two public datasets, namely the Breast Cancer Histopathology Image Classification (BreakHis 40 × : 95.50%, and BreakHis 100 × : 96.79% accuracy) and Single cells in Pap smear images for cervical cancer classification (SIPaKMeD: 99.18% accuracy). Also, the proposed method has been evaluated using five-fold cross validation and achieved improved performances on these datasets. Clearly, the proposed PND-Net effectively boosts the performances of automated health analysis of various plants in real and intricate field environments, implying PND-Net's aptness for agricultural growth as well as human cancer classification.

Matched MeSH terms: Plant Diseases*
Isolation and identification of antagonistic bacteria from phylloplane of rice as biocontrol agents for sheath blight

Akter S, Kadir J, Juraimi AS, Saud HM, Elmahdi S

J Environ Biol, 2014 Nov;35(6):1095-100.
PMID: 25522511

A total of 325 bacteria were isolated from both healthy and sheath blight infected leaf samples of rice plants, collected from different places of Malaysia, following dilution technique. Sheath blight pathogen was isolated from infected samples by tissue plating method. Out of 325, 14 isolates were found to be antagonist against the pathogen in pre evaluation test. All the 14 isolates were morphologically characterized. Antagonistic activity of these isolates was further confirmed by adopting the standard dual culture and extracellular metabolite tests. The best isolates were selected, based on the results. In dual culture test, the selected bacterial isolates KMB25, TMB33, PMB38, UMB20 and BMB42 showed 68.44%, 60.89%, 60.22%, 50.00% and 48.22% fungal growth inhibition, respectively and in extracellular metabolite test these bacterial isolates exhibited 93.33%, 84.26%, 69.82%, 67.96% and 39.26% of the same, respectively. Biochemical tests of selected isolates were performed following standard procedure. These bacterial isolates were tentatively identified as fluorescent pseudomonas by morphological and biochemical characterization. The identities were further confirmed by Biolog microstation system as P. fluorescens (UMB20), P. aeruginosa (KMB25, TMB33 and PMB38) and P. asplenii (BMB42) with similarity index ranging from 0.517 to 0.697. The effective bacterial isolates obtained from the present study can be used in the management of soil borne fungal pathogen Rhizoctonia solani, causing sheath blight of rice.

Matched MeSH terms: Plant Diseases/microbiology*; Plant Diseases/prevention & control
Fulltext Gene technology for papaya ringspot virus disease management

Azad MA, Amin L, Sidik NM

ScientificWorldJournal, 2014;2014:768038.
PMID: 24757435 DOI: 10.1155/2014/768038

Papaya (Carica papaya) is severely damaged by the papaya ringspot virus (PRSV). This review focuses on the development of PRSV resistant transgenic papaya through gene technology. The genetic diversity of PRSV depends upon geographical distribution and the influence of PRSV disease management on a sequence of PRSV isolates. The concept of pathogen-derived resistance has been employed for the development of transgenic papaya, using a coat protein-mediated, RNA-silencing mechanism and replicase gene-mediated transformation for effective PRSV disease management. The development of PRSV-resistant papaya via post-transcriptional gene silencing is a promising technology for PRSV disease management. PRSV-resistant transgenic papaya is environmentally safe and has no harmful effects on human health. Recent studies have revealed that the success of adoption of transgenic papaya depends upon the application, it being a commercially viable product, bio-safety regulatory issues, trade regulations, and the wider social acceptance of the technology. This review discusses the genome and the genetic diversity of PRSV, host range determinants, molecular diagnosis, disease management strategies, the development of transgenic papaya, environmental issues, issues in the adoption of transgenic papaya, and future directions for research.

Matched MeSH terms: Plant Diseases/genetics; Plant Diseases/therapy*
Fulltext Efficacy of combined formulations of fungicides with different modes of action in controlling botrytis gray mold disease in chickpea

Rashid MH, Hossain MA, Kashem MA, Kumar S, Rafii MY, Latif MA

ScientificWorldJournal, 2014;2014:639246.
PMID: 24723819 DOI: 10.1155/2014/639246

Botrytis gray mold (BGM) caused by Botrytis cinerea Pers. Ex. Fr. is an extremely devastating disease of chickpea (Cicer arietinum L.) and has a regional as well as an international perspective. Unfortunately, nonchemical methods for its control are weak and ineffective. In order to identify an effective control measure, six fungicides with different modes of action were evaluated on a BGM susceptible chickpea variety BARIchhola-1 at a high BGM incidence location (Madaripur) in Bangladesh for three years (2008, 2009, and 2010). Among the six fungicides tested, one was protectant [Vondozeb 42SC, a.i. mancozeb (0.2%)], two systemic [Bavistin 50 WP, a.i. carbendazim (0.2%), and Protaf 250EC, propiconazole (0.05%)], and three combination formulations [Acrobat MZ690, dimethomorph 9% + mancozeb 60%, (0.2%); Secure 600 WG, phenomadone + mancozeb (0.2%); and Companion, mancozeb 63% + carbendazim 12% (0.2%)]. The results showed superiority of combination formulations involving both protectant and systemic fungicides over the sole application of either fungicide separately. Among the combination fungicides, Companion was most effective, resulting in the lowest disease severity (3.33 score on 1-9 scale) and the highest increase (38%) of grain yield in chickpea. Therefore, this product could be preferred over the sole application of either solo protectant or systemic fungicides to reduce yield losses and avoid fungicide resistance.

Matched MeSH terms: Plant Diseases/microbiology*; Plant Diseases/prevention & control
Fulltext Analysis of simple sequence repeat markers linked with blast disease resistance genes in a segregating population of rice (Oryza sativa)

Ashkani S, Rafii MY, Sariah M, Siti Nor Akmar A, Rusli I, Abdul Rahim H, et al.

Genet. Mol. Res., 2011 Jul 06;10(3):1345-55.
PMID: 21751161 DOI: 10.4238/vol10-3gmr1331

Among 120 simple sequence repeat (SSR) markers, 23 polymorphic markers were used to identify the segregation ratio in 320 individuals of an F(2) rice population derived from Pongsu Seribu 2, a resistant variety, and Mahsuri, a susceptible rice cultivar. For phenotypic study, the most virulent blast (Magnaporthe oryzae) pathotype, P7.2, was used in screening of F(2) population in order to understand the inheritance of blast resistance as well as linkage with SSR markers. Only 11 markers showed a good fit to the expected segregation ratio (1:2:1) for the single gene model (d.f. = 1.0, P < 0.05) in chi-square (χ(2)) analyses. In the phenotypic data analysis, the F(2) population segregated in a 3:1 (R:S) ratio for resistant and susceptible plants, respectively. Therefore, resistance to blast pathotype P7.2 in Pongsu Seribu 2 is most likely controlled by a single nuclear gene. The plants from F(2) lines that showed resistance to blast pathotype P7.2 were linked to six alleles of SSR markers, RM168 (116 bp), RM8225 (221 bp), RM1233 (175 bp), RM6836 (240 bp), RM5961 (129 bp), and RM413 (79 bp). These diagnostic markers could be used in marker assisted selection programs to develop a durable blast resistant variety.

Matched MeSH terms: Plant Diseases/genetics*; Plant Diseases/microbiology*

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