Academic literature on the topic 'PLANT DISEASE DETECTION'
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Journal articles on the topic "PLANT DISEASE DETECTION"
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Manvi, Goutami G., Gayana K N, G. Ramya Sree, K. Divyanjali, and Dr Kirankumari Patil. "Plant Disease Detection." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (May 31, 2022): 4538–42. http://dx.doi.org/10.22214/ijraset.2022.43221.
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Abstract: Plant growth is major requirement for framers, as it creates a path for their living, plants getting affected and their growth is related hand in hand. Framers strive to cultivate healthy crops; in spite of it plants getting affected are the major cause of crop failure. Plant disease is now the risk factor not only for framers but also to customers, environment and global economy. Immoderate pesticide usage is the cause for major health issues in plants. Plant disease detection using image processing can be the best way to predict and get accurate results. This project is based on deep convolutional neural networks which enhances the accuracy and training efficiency. This application will help many farmers who are uneducated to get correct information about diseases and help increase their yield. We are fostering a web application that can distinguish plant infection. The objective is to distinguish different plant infection by checking picture out. By utilizing CNN Algorithm we can identify the plant disease precisely. By the results of accuracy it shows this model is better than any traditional framing. Keywords: Plant Diseases, Deep Learning, Convolutional Neural Networks
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Shelar, Nishant, Suraj Shinde, Shubham Sawant, Shreyash Dhumal, and Kausar Fakir. "Plant Disease Detection Using Cnn." ITM Web of Conferences 44 (2022): 03049. http://dx.doi.org/10.1051/itmconf/20224403049.
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Plants and crops that are infected by pests have an impact on the country's agricultural production. Usually, farmers or professionals keep a close eye on the plants in order to discover and identify diseases. However, this procedure is frequently time-consuming, costly, and imprecise. Plant disease detection can be done by looking for a spot on the diseased plant's leaves. The goal of this paper is to create a Disease Recognition Model that is supported by leaf image classification. To detect plant diseases, we are utilizing image processing with a Convolution neural network (CNN). A convolutional neural network (CNN) is a form of artificial neural network that is specifically intended to process pixel input and is used in image recognition.
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Monigari, Vaishnavi. "Plant Leaf Disease Prediction." International Journal for Research in Applied Science and Engineering Technology 9, no. VII (July 15, 2021): 1295–305. http://dx.doi.org/10.22214/ijraset.2021.36582.
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The Indian economy relies heavily on agriculture productivity. A lot is at stake when a plant is struck with a disease that causes a significant loss in production, economic losses, and a reduction in the quality and quantity of agricultural products. It is crucial to identify plant diseases in order to prevent the loss of agricultural yield and quantity. Currently, more and more attention has been paid to plant diseases detection in monitoring the large acres of crops. Monitoring the health of the plants and detecting diseases is crucial for sustainable agriculture. Plant diseases are challenging to monitor manually as it requires a great deal of work, expertise on plant diseases, and excessive processing time. Hence, this can be achieved by utilizing image processing techniques for plant disease detection. These techniques include image acquisition, image filtering, segmentation, feature extraction, and classification. Convolutional Neural Network’s(CNN) are the state of the art in image recognition and have the ability to give prompt and definitive diagnoses. We trained a deep convolutional neural network using 20639 images on 15 folders of diseased and healthy plant leaves. This project aims to develop an optimal and more accurate method for detecting diseases of plants by analysing leaf images.
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S, Dr Baskaran, Sampath P, Sarathkumar P, Sivashankar S, and Vasanth Kumar K. "Advances in Image Processing for Detection of Plant Disease." SIJ Transactions on Computer Science Engineering & its Applications (CSEA) 05, no. 02 (April 14, 2017): 08–10. http://dx.doi.org/10.9756/sijcsea/v5i2/05010140101.
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Halder, Monishanker, Ananya Sarkar, and Habibullah Bahar. "PLANT DISEASE DETECTION BY IMAGE PROCESSING: A LITERATURE REVIEW." SDRP Journal of Food Science & Technology 3, no. 6 (2018): 534–38. http://dx.doi.org/10.25177/jfst.3.6.6.
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Oo, Yin Min, and Nay Chi Htun. "Plant Leaf Disease Detection and Classification using Image Processing." International Journal of Research and Engineering 5, no. 9 (November 2018): 516–23. http://dx.doi.org/10.21276/ijre.2018.5.9.4.
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Rani, S. V. Jansi. "Plant Disease Detection using Transfer Learning in Precision Agriculture." AMBIENT SCIENCE 9, no. 3 (November 2022): 34–39. http://dx.doi.org/10.21276/ambi.2022.09.3.ta02.
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Save, Apurva, Aksham Gupta, Sarthak Pruthi, Divyanjana Nikam, and Prof Dr Shilpa Paygude. "Plant Disease Detection and Fertilizer Suggestion." International Journal for Research in Applied Science and Engineering Technology 10, no. 2 (February 28, 2022): 351–56. http://dx.doi.org/10.22214/ijraset.2022.40275.
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Abstract: Plant disease diagnosis is the foundation for efficient and precise plant disease prevention in today's complicated environment. Plant disease identification has become digitised and data-driven as smart farming has grown, allowing for advanced decision support, smart analysis, and planning. This work provides a deep learning-based mathematical model for detecting and recognising plant diseases, which improves accuracy, generality, and training efficiency. The prevention and control of plant disease have consistently been broadly talked about in light of the fact that plants are presented to the external climate and are profoundly inclined to diseases. Typically, the precise and quick diagnosis of disease assumes a significant part in controlling plant disease, since helpful protection measures are frequently carried out after right diagnosis Identification of the plant diseases is the way to prevent the misfortunes in the yield and amount of the rural item. Early Detection of Plant Leaf Disease is a significant need in a developing horticultural economy like India. Without legitimate recognizable proof of the disease, disease control measures can be an exercise in futility and cash and can prompt further plant misfortunes. Our task proposes a profound learning-based model which will be trained utilizing a dataset containing pictures of healthy and diseased crop leaves. The model will serve its target by ordering pictures of leaves into diseased classes dependent on the example of imperfection. The framework effectively recognizes various sorts of disease found in Tomato Crop. Index Terms: Convolutional Neural Networks (CNN), Deep Learning, Pretrained models, Inceptionv3, Xceptionv3, MobilenetV2.
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Sethi, Mohit. "Plant Disease Detection using Image Segmentation." International Journal of Ayurveda and Herbal Research (IJAHR) 1, no. 1 (2023): 15–18. http://dx.doi.org/10.54060/ijahr.v1i1.3.
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This paper presents a novel approach for detecting plant diseases using image segmentation techniques. The proposed method employs deep learning algorithms to segment images into healthy and infected areas, and then classifies the disease based on the segmented region. The use of image segmentation allows for the automated detection and quantification of diseases in plants, making it a valuable tool for farmers and researchers. Experimental results show that the proposed method achieves high accuracy in detecting various plant diseases, including leaf spot, powdery mildew, and rust. The method's performance was evaluated on a dataset of plant images, demonstrating its effectiveness in real-world applications. The proposed approach has the potential to revolutionize the way plant diseases are detected and managed, improving crop yields and reducing losses due to disease outbreaks.
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Verma, Shivam, Prashant Kumar Choudhary, Suraj Kumar, and Prof Dr Reena Gunjan. "Plant Disease Detection Using Deep Learning." International Journal for Research in Applied Science and Engineering Technology 10, no. 6 (June 30, 2022): 1009–13. http://dx.doi.org/10.22214/ijraset.2022.43700.
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Abstract: Crop diseases are a major threat to food security, but their rapid identification remains difficult inmany parts of the world due to the lack of thenecessary infrastructure. The combination of increasing global smartphone penetration and recent advances in computer vision made possible by deep learning has paved the way for smartphone-assisted disease diagnosis. Using a public dataset of 54,306 images of diseased andhealthy plant leaves collected under controlled conditions, we train a deep convolutional neuralnetwork to identify 14 crop species and 26 diseases (or absence thereof). The trained model achieves anaccuracy of 99.35% on a held-out test set, demonstrating the feasibility of this approach. Overall, the approach of training deep learning models on increasingly large and publicly availableimage datasets presents a clear path toward smartphone-assisted crop disease diagnosis on a massive global scale
Dissertations / Theses on the topic "PLANT DISEASE DETECTION"
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Heard, Stephanie. "Plant pathogen sensing for early disease control." Thesis, University of Manchester, 2014. https://www.research.manchester.ac.uk/portal/en/theses/plant-pathogen-sensing-for-early-disease-control(48949f80-2596-4ce2-912a-6513e72f6a8d).html.
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Sclerotinia sclerotiorum, a fungal pathogen of over 400 plant species has been estimated to cost UK based farmers approximately £20 million per year during severe outbreak (Oerke and Dehne 2004). S. sclerotiorum disease incidence is difficult to predict as outbreaks are often sporadic. Ascospores released from the fruiting bodies or apothecia can be dispersed for tens of kilometres. This makes disease control problematic and with no S. sclerotiorum resistant varieties available, growers are forced to spray fungicides up to three times per flowering season in anticipation of the arrival of this devastating disease. This thesis reports the development of the first infield S. sclerotiorum biosensor which aims to enable rapid detection of airborne ascospores, promoting a more accurate disease risk assessment and fungicide spraying regime. The sensor is designed to detect the presence of oxalic acid, the main pathogenicity factor secreted during early S. sclerotiorum ascospore germination. Upon electrochemical detection of this analyte in the biosensor, a binary output is relayed to farmer to warm him of a disease risk. This project focused on the development of a nutrient matrix which was designed to be contained within the biosensor. The role of this matrix was to promote the growth of captured airborne S. sclerotiorum ascospores and induce high levels of oxalic acid secretion. The use of the designed biological matrix to promote oxalic acid production was tested during three field trials in S. sclerotiorum artificially inoculated fields. This thesis describes the use of contemporary pathogenomics technologies to further investigate candidate genes involved in pathogenicity alongside the secretion of oxalic acid. A pre-described bioinformatics pipeline was used to predict the S. sclerotiorum secretome to identify potential effector proteins as well as explore proteins which are unique to S. sclerotiorum to be used as other novel targets for detection. GFP tagged constructs were designed to investigate the expression of the putative targets for S. sclerotiorum detection. The transcriptomes of wild type and oxalic acid deficient S. sclerotiorum strains during infection as well as during a saprotrophic stage were investigated. This study provided expression support for not only some of the unannotated genes identified in the putative secretome, but some candidate genes speculated to be involved in infection.
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Mendel, Julian L. "Laurel Wilt Disease: Early Detection through Canine Olfaction and "Omics" Insights into Disease Progression." FIU Digital Commons, 2017. http://digitalcommons.fiu.edu/etd/3475.
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Laurel wilt disease is a vascular wilt affecting the xylem and water conductivity in trees belonging to the family Lauraceae. The disease was introduced by an invasive species of ambrosia beetle, Xyleborus glabratus. The beetle, together with its newly described fungal symbiont Raffaelea lauricola (pathogenic to host trees), has lead to the devastation and destruction of over 300 million wild redbay trees in southeastern forests. Ambrosia beetles make up a very unique clade of beetle and share a co-evolved obligatory mutualistic relationship with their partner fungi. Rather than consuming host tree material, the beetles excavate galleries or canals within them. These galleries serve two purposes: reproduction and fungal gardening. The beetles house fungal spores within specialized sacs, mycangia, and essentially inoculate host trees with the pathogenic agent. They actively grow and cultivate gardens of the fungus in galleries to serve as their sole food source. Once the fungus reaches the xylem vessels of the host tree, it thrives and leads to the blockage of water flow, both because of fungal accumulation and to the host response of secreting gels, gums and tyloses to occlude vessels in an attempt to quarantine the fungus.
This disease spreads rapidly, and as a result, once symptoms become visible to the naked eye, it is already too late to save the tree, and it has likely already spread to adjacent ones. The present study presents the first documented study involving the early detection of disease from deep within a tree through the use of scent-discriminating canines. In addition, the present study has lead to the development of a novel sample collection device enabling the non-destructive sampling of beetle galleries. Finally, a metabolomics approach revealed key biochemical pathway modifications in the disease state, as well as potential clues to disease development.
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Kaneshiro, Wendy S. "Detection and characterization of virulent, hypovirulent, and nonvirulent Clavibacter Michiganensis subsp. Michiganensis." Thesis, University of Hawaii at Manoa, 2003. http://hdl.handle.net/10125/7001.
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Mewes, Thorsten [Verfasser]. "The impact of the spectral dimension of hyperspectral datasets on plant disease detection / Thorsten Mewes." Bonn : Universitäts- und Landesbibliothek Bonn, 2011. http://d-nb.info/101621667X/34.
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Mohamed, Maizatul-Suriza. "Phytophthora palmivora, the causal agent of bud rot disease of oil palm (Elaeis guineensis Jacq.) : biology, detection and control." Thesis, University of Nottingham, 2017. http://eprints.nottingham.ac.uk/41678/.
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Bud rot disease has been considered as a devastating disease of oil palm in Latin America. Severe outbreaks of this disease have been reported in Colombia, Brazil, Ecuador, Panama and Suriname. The causal agent of bud rot disease in Colombia has been identified as Phytophthora palmivora. This pathogen is known to be responsible for several tropical diseases such as black pod and stem canker disease of cocoa, especially during the rainy season. Phytophthora palmivora has also been reported to attack durian, rubber, pepper and jackfruit causing diseases in various parts of the plant such as fruit, leaves and stems. However, no outbreaks of the disease have been reported in oil palm in Malaysia or other Southeast Asian countries. Several aspects of research need to be conducted to understand why this pathogen causes problems in oil palm in South America but not in Southeast Asia. This study aimed to analyze variation between the Colombian P. palmivora isolates that cause bud rot disease in comparison with Malaysian isolates and other isolates gathered from different hosts and regions. Our hypothesis was that P. palmivora isolates from the different regions and/or hosts have different molecular characteristics and have dissimilar levels of pathogenicity. Sequence alignments of several genetic markers, the internal transcribed spacer (ITS) of the ribosomal RNA (rRNA) gene cluster, beta-tubulin (β-tubulin), translation elongation factor 1 alpha (EF-1α), cytochrome c oxidase subunit I (CoxI) and subunit II (CoxII) genes failed to distinguish between Colombian oil palm isolates and P. palmivora from different hosts and regions. It was concluded that these markers are more suitable for inter-specific studies between species but not for intra-specific evaluation within species of P. palmivora. However, a new marker named as P. palmivora hypothetical avirulence effector protein (PpHPAVR) along with analyses of amplified fragment length polymorphisms (AFLPs), separated the Malaysian and Colombian isolates into distinct clades. This indicates that there is genomic variation within P. palmivora isolates. The zoospores of P. palmivora from various hosts and demographic origin were shown to have the ability to cause infection to oil palm seedlings, durian and rubber. However, not enough evidence has been collected to confirm that pathogenicity correlates with the distinct clades observed with AFLPs and PpHPAVR. Phytophthora palmivora species-specific diagnostic using PCR and loop-mediated isothermal amplification (LAMP) have been developed based on the PpHPAVR region.
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Unver, Turgay. "Detection And Characterization Of Plant Genes Involved In Various Biotic And Abiotic Stress Conditions Using Ddrt-pcr And Isolation Of Interacting Proteins." Phd thesis, METU, 2008. http://etd.lib.metu.edu.tr/upload/12609805/index.pdf.
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The main objective of this thesis dissertation is functionally characterizing the genes involved in biotic and abiotic stresses of plants at molecular level. Previously, upon pathogen attack Rad6 gene expression was found to be changed in wheat and barley plants. To functionally characterize the Rad6 gene, VIGS (Virus induced gene silencing) system was used. HR (Hypersensitive response) like symptoms was detected in every silenced barley and wheat plants. To figure out, transcriptomes and proteomes of Rad6 silenced plants were analyzed. 2-D PAGE analysis was also performed on silenced and control wheat plants. No pathogen growth was observed in Rad6 silenced barley lines. Additionally, the susceptible wild type Arabidopsis plants showed resistant phenotype when any of the Rad6 gene copies is mutated. This suggests that Rad6 gene has a negative regulatory role in plant disease resistance which was proved for the first time. Yeast two hybrid protein interaction study suggests that RAD6 carrying out its function by interacting with SGT1 protein and regulating resistance related genes. It has been first time reported in this thesis that E2 (Ubiquitin conjugating enzyme) takes role in plant disease resistance.
Boron which is the other consideration in the scope of thesis as an abiotic stress factor at a very limited amount is necessary for the normal development of plants. This study is conducted on highly boron tolerant Gypsophila perfoliata L. collected from a location in the boron mining area. The plant samples were tested in the presence of high boron (35 mg/kg) concentrations. The transcriptomes of the plant samples treated with the excess levels of boron to that of the samples grown under normal concentration were compared using differential display PCR method. Thirty bands showing differential expression levels at varying time points were analyzed. 18 of them were confirmed via qRT-PCR.
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Patil, Neeraj. "Detection of Sclerotinia sclerotiorum using qPCR assay and comparison between three qPCR systems to check sensitivity." Thesis, Högskolan i Skövde, Institutionen för biovetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-20265.
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Sclerotinia sclerotiorum is a pathogenic fungus that infects around 400 species of host plants. Stem rot disease caused by this fungus is economically disastrous for Brassica napus cultivators in Sweden. Due to the lack of disease resistant cultivars, disease management has been solely dependent on fungicide application. The current disease prediction models are not scientifically accurate and take into account factors such as weather, previous disease incidence, and conomic effects which often result in unnecessary and excessive use of fungicides by cultivators. Real-Time Polymerase Chain Reaction has proven to be the fastest, most accurate and reliable technique for detecting plant pathogens as it gives an idea about disease severity by measuring pathogen concentration in environmental samples. Reproducible and able qPCR assays have the potential of being the main principle on which more scientifically accurate plant disease prediction and management models an be developed. The aim of this study was to validate a previously established qPCR assay to detect S. sclerotiorum. An absolute quantification experiment was performed by using plasmid DNA cloned with a target gene as template. Further, three different qPCR machines were compared to make a plausible conclusion regarding their sensitivity and efficiency in detecting minuscule amounts of DNA from the environment. While a solid conclusion could not be reached regarding the sensitivity of each of these machines, this study pointed out some basic trends about each machine that may help researchers in selecting the most efficient qPCR system when working with detection of plant pathogens.
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Lardner, Richard. "Early diagnosis and detection of Eutypa dieback of grapevines." Title page, table of contents and abstract only, 2003. http://hdl.handle.net/2440/37969.
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Eutypa dieback of grapevines, caused by Eutypa lata, is a major cause of reduced longevity in vineyards worldwide. The fungus grows in the woody tissue of infected vines, producing translocatable toxins that cause foliar symptoms of the disease. By the time foliar symptoms are evident the pathogen may have become well established in the vine. One aim of this study was to develop DNA markers to allow rapid reliable identification of E. lata and to detect the pathogen in infected wood. The second aim was to analyse secondary metabolite production by E. lata in order to gain information on the compounds responsible for the foliar symptoms of the disease and to identify metabolites which could be used as markers to detect the early stages of the disease prior to the expression of foliar symptoms. In addition, genetic variation of the pathogen was assessed using RFLP and RAPD analysis. Two techniques were used to develop DNA markers; first, SCAR markers derived from RAPD fragments were developed and, second, an E. lata genomic DNA library was constructed, from which DNA fragments specific to E. lata were identified. These markers were used in either PCR- or Southern hybridisation-based assays to detect the pathogen in infected wood. PCR-based detection of the pathogen in infected wood was prone to inhibition by phenolic compounds, however, Southern hybridisation techniques were capable of detecting E. lata in wood. Genetic variation among 38 isolates of E. lata was assessed using six randomly selected clones from the genomic DNA library. A subset of 11 isolates was subjected to RAPD analysis using 10 random primers. Considerable genetic diversity, in terms of RFLP and RAPD profiles, was observed among isolates. There was no apparent correlation between grouping of isolates following neighbour joining analysis and either host species or geographic origin of isolates. The RAPD and RFLP profiles of two isolates differed significantly from the majority of the other isolates. These isolates, which were morphologically similar to all other isolates, were subsequently found not to be E. lata. Secondary metabolite production of 11 isolates was analysed by HPLC following growth on a range of media. A wider range of secondary metabolites was detected in E. lata than has previously been reported. Two of the secondary metabolites, eutypine and an unidentified compound with a retention time of 19.6 min, were produced by eight of nine isolates of E. lata. Neither of the non-E. lata isolates produced these compounds. It was concluded that the remaining isolate of E. lata may have lost the ability to produce these compounds following storage. Whilst a wider range of isolates needs to be screened before a candidate marker can be selected, these results suggest that certain compounds are present in the majority of E. lata isolates and, hence, may prove suitable markers for the detection of the pathogen prior to the expression of foliar symptoms. The molecular probes developed in this study will allow the rapid and reliable identification and detection of E. lata in grapevine cane or wood. These probes also have the potential to be used as a research tool to gather information on the epidemiology of the disease and to assess the efficacy of potential control agents against E. lata. Suitable control measures could then be applied to vines which have been shown by the use of chemical markers to have latent infection. Used in combination, therefore, the DNA and biochemical markers could facilitate improved management of eutypa dieback.Thesis (Ph.D.) -- University of Adelaide, School of Agriculture and Wine, 2003.
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Ghaffari, Reza. "Non-destructive detection of diseases using plant emitted volatiles." Thesis, University of Warwick, 2013. http://wrap.warwick.ac.uk/61777/.
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The detection of plant diseases is an important part of commercial greenhouse crop production and can enable continued disease and pest control which will ultimately lead to the economical benefit as well as the significant reduction in use of chemical and biochemical treatments. A plant subject to infection typically releases exclusive volatile organic compounds (VOCs) which may be detected by appropriate sensors. A set of experiments were designed, constructed and conducted at University of Warwick in which the state-of-the-art gas sensors namely Electronic Nose (EN) and Field Asymmetric Ion Mobility Spectrometry (FAIMS) were employed to sample the VOC profiles in order to detect powdery mildew-infected and spider mite-infested tomato plants in a non-destructive manner. The data acquired from the EN and FAIMS devices was analysed using Principal Component Analysis, Linear Discriminant Analysis, Support Vector Machines and Artificial Neural Networks. Both EN and FAIMS proved to be able to distinguish between healthy and infected tomato plants with desirable accuracy when coupled with an appropriate data analysis technique. A review of the literature on plant diseases, destructive and non-destructive plant's disease detection tools as well as VOC sampling procedures and instrumentation will be given throughout this thesis. Moreover, the latter part of this thesis presents the master-slave synchronisation of identical chaotic dynamical systems using the open-plus close-loop (OPCL) control method. The study is mainly concerned with the behaviour of the synchronisation of chaotic dynamical systems in respect to an added bias and in the case of mismatch of parameters of master and slave systems. The link between the external bias and the synchronisation error generated as well as between the value of parameters mismatch and the synchronisation error is examined and discussed. The usability of the newly proposed approaches is assessed by the aid of two applications. The first application demonstrates that a weak bias acting on Nano-mechanical resonator shows the linear correlation with the synchronisation error and, consequently, the bias can be estimated via this error. The second application is related to the synchronisation of the cantilevers commonly found in ENs and Atomic Force Microscopy (AFM). It is suggested to use a novel scheme of coupled master{slave cantilevers and, estimate the difference in cantilever-surface interactions in master oscillator and in slave oscillator via measuring the synchronisation error. The scheme is particularly useful for using the master cantilever as a control and the slave cantilever as a unit device which measures surface properties. The study shows that by calculating the error of synchronisation, a precise measurements can be conducted when two cantilevers leave the synchronous region, that is when they de-synchronise. Thus, this thesis also contributes to the understanding of de-synchronisation of nano-scale chaotic systems (Nano electromechanical Systems) in respect to the addition of an external bias and/or parameters mismatch by outlining the possible applications.
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Retief, Estianne. "Molecular detection of Phaeomoniella chlamydospora in grapevine nurseries." Thesis, Stellenbosch : Stellenbosch University, 2005. http://hdl.handle.net/10019.1/20940.
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Thesis (MScAgric)--University of Stellenbosch, 2005.ENGLISH ABSTRACT: Phaeomoniella chlamydospora is the main causal organism of Petri disease, which causes severe decline and dieback of young grapevines (1-7 years old) and also predisposes the wood for infection by other pathogens. Knowledge about the epidemiology and especially inoculum sources of this disease is imperative for subsequent development of management strategies. Through isolation studies it was shown that Pa. chlamydospora is mainly distributed through infected propagation material in South Africa. However, the infection pathways and inoculum sources in grapevine nurseries are still unclear. The only existing method to detect this pathogen in various media is by means of isolation onto artificial growth media. This has proven to be problematic since this fungus is extremely slow growing (up to 4 weeks from isolation to identification) and its cultures are often over-grown by co-isolated fungi and bacteria before it can be identified. The aim of this study was (i) to develop a protocol for the molecular detection of Pa. chlamydospora in grapevine wood, and (ii) to use this protocol along with others, to test different samples (water, soil, rootstock and scion cuttings and callusing medium) collected from nurseries in South Africa at different nursery stages for the presence of Pa. chlamydospora. A protocol was developed and validated for the molecular detection of Pa. chlamydospora in grapevine wood. Firstly, several previously published protocols were used to develop a cost-effective and time-efficient DNA extraction method from rootstock pieces of potted grapevines. Subsequently, PCR amplification using species-specific primers (Pch1 and Pch2) was found to be sensitive enough to detect as little as 1 pg of Pa. chlamydospora genomic DNA from grapevine wood. The protocol was validated using various grapevine material from 3 different rootstock cultivars (101-14 Mgt, Ramsey and Richter 99) collected from each of 3 different nurseries, including grapevines that were subjected to hot water treatment. The basal end of the rootstock was parallel analysed for Pa. chlamydospora using isolations onto artificial medium and molecular detection. The identity of PCR products obtained from a subset of samples, that only tested positive for Pa. chlamydospora based on molecular detection, was confirmed to be Pa. chlamydospora specific through restriction digestion with AatII. Molecular detection was found to be considerably more sensitive than isolations, detecting Pa. chlamydospora from samples with positive as well as negative isolations. On average, the molecular technique detected Pa. chlamydospora in 80.9% of the samples, whereas only 24.1% of the samples tested positive for Pa. chlamydospora by means of isolations. Pa. chlamydospora was not isolated from hot water treated samples. The results confirm the importance of hot water treatment for proactive management of Petri disease in grapevine nurseries. However, Pa. chlamydospora DNA was molecularly detected in hot water treated samples in frequencies similar to that detected in non-hot water treated samples. As expected, the DNA in hot water treated plants was not destroyed and could be detected by the developed molecular detection protocol. This is an important consideration when using molecular detection for disease diagnosis or pathogen detection and shows that these methods should be used in conjunction with other diagnostic tools. Most importantly, the DNA extraction protocol was shown to be 10 to 15 times cheaper than commercial DNA extraction kits. Preliminary studies showed that the aforementioned molecular detection technique was not specific and sensitive enough for detection of Pa. chlamydospora in soil and water (unpublished data). Therefore, a one-tube nested-PCR technique was optimised for detecting Pa. chlamydospora in DNA extracted from soil, water, callusing medium and grapevine wood. Rootstock cane sections and soil samples were taking from the mother blocks from several nurseries. Water samples were collected from hydration and fungicide tanks during pre-storage and grafting. Scion and rootstock cuttings were also collected during grafting and soil were collected from the nursery beds prior to planting. The one-tube nested-PCR was sensitive enough to detect as little as 1 fg of Pa. chlamydospora genomic DNA from water and 10 fg from wood, callusing medium and soil. PCR analyses of the different nursery samples revealed the presence of several putative Pa. chlamydospora specific bands (360 bp). Subsequent sequence analyses and/or restriction enzyme digestions of all 360 bp PCR bands confirmed that all bands were Pa. chlamydospora specific, except for five bands obtained from callusing media and one band from water. Considering only Pa. chlamydospora specific PCR bands, the molecular detection technique revealed the presence of Pa. chlamydospora in 25% of rootstock cane sections and 17% of the soil samples collected from mother blocks, 42% of rootstock cuttings collected during grafting, 16% of scion cuttings, 40% of water samples collected after the 12- hour pre-storage hydration period, 67% of water samples collected during grafting and 8% of the callusing medium samples. These media should therefore be considered as potential inoculum sources or infection points of the pathogen during the nursery stages. The results furthermore confirmed previous findings that Pa. chlamydospora is mainly distributed through infected rootstock canes and cuttings. Infected scion cuttings were also shown to be potential carriers of the pathogen. Management strategies should include wound protection of rootstock mother plants, eradicating this pathogen from rootstock-cuttings (e.g. hot water treatment), biological or chemical amendments in the hydration water and callusing medium and wound protection from soil borne infections.
AFRIKAANSE OPSOMMING: Phaeomoniella chlamydospora is die hoof veroorsakende organisme van Petri se siekte wat lei tot die agteruitgang en terugsterwing van jong wingerdplante (1-7 jaar oud) en veroorsaak verhoogde vatbaarheid van hout vir infeksie deur ander patogene. Kennis oor die epidemiologie en veral die inokulumbronne van die siekte is noodsaaklik vir die daaropvolgende ontwikkeling van beheerstrategieë. Isolasies het getoon dat Pa. chlamydospora meestal versprei deur middel van geïnfekteerde voortplantingsmateriaal in Suid-Afrika. Die infeksieweë en inokulumbronne in wingerdkwekerye is egter steeds onbekend. Die enigste bestaande metode vir die opsporing van die patogeen, in verskeie mediums, is deur middel van isolasie op kunsmatige groeimediums. Dit is egter gevind om problematies te wees aangesien die swam uiters stadig groei (dit vat tot 4 weke vanaf isolasie tot identifikasie) en die kulture is telkens oorgroei deur ander organismes voordat identifikasie kan plaasvind. Die doel van die studie was (i) om ‘n protokol te ontwikkel vir die molekulêre opsporing van Pa. chlamydospora in wingerdhout, en (ii) om die protokol te gebruik, saam met ander, om verskillende monsters (water, grond, onderstok- en bostok-ente en kallusmedium) te toets, wat versamel is van kwekerye in Suid- Afrika, tydens verskillende kwekerystadiums, vir die teenwoordigheid van Pa. chlamydospora. ‘n Protokol is ontwikkel en geverifieer vir die molekulêre opsporing van Pa. chlamydospora in wingerdhout. Eerstens is verskeie protokols wat voorheen gepubliseer is, is as grondslag gebruik vir die ontwikkeling van ‘n ekonomiese en tydbesparende DNA ekstraksie protokol. Hierna is PKR (polimerase ketting reaksie) amplifikasie met spesie-spesifieke inleiers (Pch1 en Pch2) gevind om sensitief genoeg te wees om so min as 1 pg van Pa. chlamydospora genomiese DNA van wingerdhout op te spoor. Die protokol is geverifieer deur verskeie wingerdhoutmateriaal van 3 verskillende onderstokkultivars (101-14 Mgt, Ramsey en Richter 99) te gebruik, wat elk versamel is van 3 verskillende kwekerye. ‘n Aantal van die wingerstokke is ook onderwerp aan warmwaterbehandeling. Die basale kant van die onderstok is parallel geanaliseer vir Pa. chlamydospora deur gebruik te maak van isolasies op kunsmatige groeimedium asook molekulêre opsporing. Die identiteit van ‘n submonster van PKR produkte van verskeie monsters, wat slegs positief getoets het vir Pa. chlamydospora met die molekulêre opsporing, is bevestig om Pa. chlamydospora spesifiek te wees. Dit is gedoen deur middel van restriksie ensiem analise met AatII. Molekulêre opsporing is gevind om aansienlik meer sensitief te wees as isolasies, deurdat Pa. chlamydospora opgespoor is van positiewe sowel as negatiewe isolasies. Die molekulêre tegniek het Pa. chlamydospora in ‘n gemiddeld van 80.9% van die monsters opgespoor, terwyl slegs ‘n gemiddeld van 24.1% van die monsters postief getoets het vir Pa. chlamydospora, deur middel van isolasies. Pa. chlamydospora is nie geïsoleer van die monsters wat warmwaterbehandeling ondergaan het nie. Die resultate bevestig hoe belangrik warmwaterbehandeling is vir die proaktiewe beheer van Petri se siekte in wingerdkwekerye. Pa. chlamydospora DNA is met die molekulêre tegniek opgespoor, in warmwaterbehandelde monsters, in getalle wat ooreenstemmend is met die van niewarmwaterbehandelde monsters. Soos verwag, is DNA in warmwaterbehandelde plante nie vernietig nie en kon dit telke male opgespoor word deur die ontwikkelde molekulêre opsporing protokol. Dit is ‘n belangrike feit wat in ag geneem moet word wanneer molekulêre opsporing gebruik word in siekte diagnose en opsporing van patogene en dit is ‘n aanduiding dat die metodes gebruik moet word in samewerking met ander diagnostiese tegnieke. Die DNA ekstraksie protokol het getoon om tot en met 10 tot 15 kere goedkoper te wees as kommersiële DNA ekstraksie pakkette. Voorlopige studies het getoon dat die bogenoemde molekulêre opsporings tegniek nie spesifiek en sensitief genoeg is vir die opsporing van Pa. chlamydospora uit grond en water nie (ongepubliseerde data). Daarom is ‘n enkel-buis geneste-PKR tegniek geoptimiseer vir die opsporing van Pa. chlamydospora DNA wat geëkstraheer is vanaf grond, water, kallusmedium en wingerdhout. Dele van onderstokke en grond monsters is geneem vanaf moederblokke van verskeie kwekerye. Gedurende die voor-opberging en enting periodes is watermonsters versamel vanaf hidrasie en fungisied tenke. Bostok- en onderstokente is ook versamel gedurende enting en grond is versamel vanaf kwekerybeddens net voor uitplanting. Die enkelbuis geneste-PKR was sensitief genoeg om so min as 1 fg van Pa. chlamydospora genomiese DNA vanaf water en 10 fg vanaf hout, kallusmedium en grond op te spoor. PKR analise van die verskillende kwekerymonsters het getoon dat daar ‘n teenwoordigheid is van verskeie putatiewe Pa. chlamydospora spesifieke bande (360 bp). Daaropvolgende analise deur middel van DNA volgordebepaling en restriksie ensiem analise het bevestig dat al die 360 bp PKR bande wel Pa. chlamydospora spesifiek is, behalwe vir vyf bande wat verkry is vanaf kallusmedium en een band verkry vanaf water. As slegs Pa. chlamydospora spesifieke bande in ag geneem word, is daar met molekulêre opsporing die teenwoordigheid van Pa. chlamydospora gevind in 25% van die onderstokke, 17 % van die grond versamel vanaf moederblokke, 42% van die onderstokente versamel tydens enting, 16% van die bostokente, 40% van die watermonsters versamel voor die 12-uur hidrasie periode, 67% van die watermonsters versamel gedurende enting en 8% van die kallusmediummonsters. Hierdie mediums moet dus beskou word as potensiële inokulumbronne of infeksiepunte van die patogeen gedurende die kwekerystadiums. Die resultate bevestig ook verdere bevindinge wat aandui dat Pa. chlamydospora meestal versprei word deur geïnfekteerde onderstokke en ente. Geïnfekteerde bostokente is ook aangedui om potensiële draers van die patogeen te wees. Beheerstrategieë moet dus wondbeskerming van onderstok moederplante insluit, asook uitwissing van die patogeen vanaf onderstokente (bv. warmwaterbehandeling), toediening van biologiese of chemiese stowwe in die hidrasie water en kallusmedium en wondbeskerming teen grondgedraagde infeksies.
Books on the topic "PLANT DISEASE DETECTION"
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Narayanasamy, P. Plant pathogen detection and disease diagnosis. New York: Marcel Dekker, 1997.
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Narayanasamy, P. Plant pathogen detection and disease diagnosis. 2nd ed. New York: M. Dekker, 2001.
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Narayanasamy, P. Microbial Plant Pathogens-Detection and Disease Diagnosis:. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-9735-4.
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Narayanasamy, P. Microbial Plant Pathogens-Detection and Disease Diagnosis:. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-9754-5.
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Narayanasamy, P. Microbial Plant Pathogens-Detection and Disease Diagnosis:. Dordrecht: Springer Netherlands, 2011. http://dx.doi.org/10.1007/978-90-481-9769-9.
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service), SpringerLink (Online, ed. Microbial Plant Pathogens-Detection and Disease Diagnosis: Fungal Pathogens, Vol.1. Dordrecht: Springer Science+Business Media B.V., 2011.
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Narayanasamy, P. Microbial Plant Pathogens-Detection and Disease Diagnosis: Viral and Viroid Pathogens, Vol.3. Dordrecht: Springer Science+Business Media B.V., 2011.
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Narayanasamy, P. Microbial Plant Pathogens-Detection and Disease Diagnosis: Bacterial and Phytoplasmal Pathogens, Vol.2. Dordrecht: Springer Science+Business Media B.V., 2011.
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P, Martelli G., International Council for the Study of Viruses and Virus Diseases of the Grapevine., and Food and Agriculture Organization of the United Nations., eds. Graft-transmissible diseases of grapevines: Handbook for detection and diagnosis. Rome: Food and Agriculture Organization of the United Nations, 1993.
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M, Duncan J., and Torrance L, eds. Techniques for the rapid detection of plant pathogens. Oxford [England]: Published for the British Society of Plant Pathology by Blackwell Scientific Publications, 1992.
Find full textBook chapters on the topic "PLANT DISEASE DETECTION"
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Shakeel, Qaiser, Rabia Tahir Bajwa, Ifrah Rashid, Hafiz Muhammad Usman Aslam, Yasir Iftikhar, Mustansar Mubeen, Guoqing Li, and Mingde Wu. "Immunotechnology for Plant Disease Detection." In Trends in Plant Disease Assessment, 145–65. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-5896-0_9.
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Shah, Deshna, Nidhi Vora, Chansi Vora, and Bhakti Sonawane. "Image-Based Plant Disease Detection." In Data Intelligence and Cognitive Informatics, 651–66. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-6460-1_50.
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Yahaya, S. M. "Plant Disease Detection and Management: An Overview." In Plant Pathogens, 157–77. Includes bibliographical references and index.: Apple Academic Press, 2020. http://dx.doi.org/10.1201/9780429057212-8.
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Fletcher, Jacqueline, Francisco M. Ochoa Corona, and Mark Payton. "Plant Disease Diagnostics for Forensic Applications." In Detection and Diagnostics of Plant Pathogens, 103–15. Dordrecht: Springer Netherlands, 2014. http://dx.doi.org/10.1007/978-94-017-9020-8_7.
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Chakrabarti, Dilip Kumar, and Prabhat Mittal. "Disease Detection: Imaging Technology and Remote Sensing." In Plant Disease Forecasting Systems, 105–15. Singapore: Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-99-1210-0_11.
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Bhatia, Gresha S., Pankaj Ahuja, Devendra Chaudhari, Sanket Paratkar, and Akshaya Patil. "Plant Disease Detection Using Deep Learning." In Second International Conference on Computer Networks and Communication Technologies, 408–15. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-37051-0_47.
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Chhillar, Ankit, and Sanjeev Thakur. "Plant Disease Detection Using Image Classification." In Proceedings of International Conference on Big Data, Machine Learning and their Applications, 267–81. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-8377-3_23.
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Trisha, FarjanaYeasmin, and Mahmudul Hasan. "Rice Plant Disease Detection Using IoT." In Cybersecurity, 119–30. Boca Raton: CRC Press, 2021. http://dx.doi.org/10.1201/9781003145042-8.
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Ghesquiere, Matisse, and Mkhuseli Ngxande. "Deep Learning for Plant Disease Detection." In Advances in Computer Vision and Computational Biology, 69–84. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-71051-4_5.
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Manjula, K., S. Spoorthi, R. Yashaswini, and Divyashree Sharma. "Plant Disease Detection Using Deep Learning." In Lecture Notes in Electrical Engineering, 1389–96. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-3690-5_133.
Full textConference papers on the topic "PLANT DISEASE DETECTION"
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Alagesan, Mohanraj, Thangaraj Kesavan, Harshavardhan Murugesan, Mohanraj Thangavel, and Gowthaman Madesh. "Plant disease detection." In 24TH TOPICAL CONFERENCE ON RADIO-FREQUENCY POWER IN PLASMAS. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0164983.
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Amsavalli, Yogeswaran, P. S. Mayurappriyan, and M. Saravana Mohan. "Plant Disease Detection Robot." In 2021 International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA). IEEE, 2021. http://dx.doi.org/10.1109/icaeca52838.2021.9675776.
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Shrestha, Garima, Deepsikha, Majolica Das, and Naiwrita Dey. "Plant Disease Detection Using CNN." In 2020 IEEE Applied Signal Processing Conference (ASPCON). IEEE, 2020. http://dx.doi.org/10.1109/aspcon49795.2020.9276722.
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Archana, U., Amanulla Khan, Appani Sudarshanam, C. Sathya, Ashok Kumar Koshariya, and R. Krishnamoorthy. "Plant Disease Detection using ResNet." In 2023 International Conference on Inventive Computation Technologies (ICICT). IEEE, 2023. http://dx.doi.org/10.1109/icict57646.2023.10133938.
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Beri, Dilip Chakravarthy, and B. V. A. N. S. S. Prabhakar Rao. "Intelligent plant disease detection system." In PROCEEDINGS OF THE TIM20-21 PHYSICS CONFERENCE. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0150097.
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P., Deepthi, Dhinakaran M., and Yoganapriya R. "Fruit Disease Detection Using Image Processing." In The International Conference on scientific innovations in Science, Technology, and Management. International Journal of Advanced Trends in Engineering and Management, 2023. http://dx.doi.org/10.59544/bfbm3617/ngcesi23p87.
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Nowadays, production of mango fruit decreases because of climatic conditions and environmental concerns like heavy rain, high humidity, reduction in soil nutrients, diversity of associated diseases and disorder problems. Typically, the detection of mango Plant diseases is done by naked eye observation, which provides less accuracy. Low productivity of mango fruit is due to the various diseases affecting mango plants which are not recognized by the farmers as they are illiterate. This paper holds a survey on fruit disease detection using image processing techniques. DIP is a fast and accurate technique for detection of diseases in fruits. Identification and classification of diseases of fruits are done through various algorithms. This paper is fruit disease identification and classification techniques used by different authors. Techniques include clustering and CBS, ANN and different classifiers-based classification of diseases. The main focus of our work is obtaining the analysis of different fruit diseases detection techniques and also provides an overview of these techniques. All the work is done using Python and supporting libraries.
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Ramesh, Shima, Ramachandra Hebbar, Niveditha M., Pooja R., Prasad Bhat N., Shashank N., and Vinod P.V. "Plant Disease Detection Using Machine Learning." In 2018 International Conference on Design Innovations for 3Cs Compute Communicate Control (ICDI3C). IEEE, 2018. http://dx.doi.org/10.1109/icdi3c.2018.00017.
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Sandhu, Gurleen Kaur, and Rajbir Kaur. "Plant Disease Detection Techniques: A Review." In 2019 International Conference on Automation, Computational and Technology Management (ICACTM). IEEE, 2019. http://dx.doi.org/10.1109/icactm.2019.8776827.
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Khirade, Sachin D., and A. B. Patil. "Plant Disease Detection Using Image Processing." In 2015 International Conference on Computing Communication Control and automation(ICCUBEA). IEEE, 2015. http://dx.doi.org/10.1109/iccubea.2015.153.
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Chapaneri, Radhika, Maithili Desai, Anmolika Goyal, Shreya Ghose, and Sheona Das. "Plant Disease Detection: A Comprehensive Survey." In 2020 3rd International Conference on Communication System, Computing and IT Applications (CSCITA). IEEE, 2020. http://dx.doi.org/10.1109/cscita47329.2020.9137779.
Full textReports on the topic "PLANT DISEASE DETECTION"
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Whitcomb, R. F., Shlomo Rottem, T. A. Chen, and C. J. Chang. Mollicutes that Cause Plant Disease: Detection, Cultivation, and Physiology. United States Department of Agriculture, September 1986. http://dx.doi.org/10.32747/1986.7566864.bard.
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Sessa, Guido, and Gregory B. Martin. molecular link from PAMP perception to a MAPK cascade associated with tomato disease resistance. United States Department of Agriculture, January 2012. http://dx.doi.org/10.32747/2012.7597918.bard.
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The research problem: The detection of pathogen-associated molecular patterns (PAMPs) by plant pattern recognition receptors (PRRs) is a key mechanism by which plants activate an effective immune response against pathogen attack. MAPK cascades are important signaling components downstream of PRRs that transduce the PAMP signal to activate various defense responses. Preliminary experiments suggested that the receptor-like cytoplasmickinase (RLCK) Mai5 plays a positive role in pattern-triggered immunity (PTI) and interacts with the MAPKKK M3Kε. We thus hypothesized that Mai5, as other RLCKs, functions as a component PRR complexes and acts as a molecular link between PAMP perception and activation of MAPK cascades. Original goals: The central goal of this research was to investigate the molecular mechanisms by which Mai5 and M3Kε regulate plant immunity. Specific objectives were to: 1. Determine the spectrum of PAMPs whose perception is transmitted by M3Kε; 2. Identify plant proteins that act downstream of M3Kε to mediate PTI; 3. Investigate how and where Mai5 interacts with M3Kε in the plant cell; 4. Examine the mechanism by which Mai5 contributes to PTI. Changes in research directions: We did not find convincing evidence for the involvement of M3Kε in PTI signaling and substituted objectives 1 and 3 with research activities aimed at the analysis of transcriptomic profiles of tomato plants during the onset of plant immunity, isolation of the novel tomato PRR FLS3, and investigation of the involvement of the RLCKBSKs in PTI. Main achievements during this research program are in the following major areas: 1. Functional characterization of Mai5. The function of Mai5 in PTI signaling was demonstrated by testing the effect of silencing the Mai5 gene by virus-induced gene silencing (VIGS) experiments and in cell death assays. Domains of Mai5 that interact with MAPKKKs and subcellular localization of Mai5 were analyzed in detail. 2. Analysis of transcriptional profiles during the tomato immune responses to Pseudomonas syringae (Pombo et al., 2014). We identified tomato genes whose expression is induced specifically in PTI or in effector-triggered immunity (ETI). Thirty ETI-specific genes were examined by VIGS for their involvement in immunity and the MAPKKK EPK1, was found to be required for ETI. 3. Dissection of MAP kinase cascades downstream of M3Kε (Oh et al., 2013; Teper et al., 2015). We identified genes that encode positive (SGT and EDS1) and negative (WRKY1 and WRKY2) regulators of the ETI-associated cell death mediated by M3Kε. In addition, the MKK2 MAPKK, which acts downstream of M3Kε, was found to interact with the MPK3 MAPK and specific MPK3 amino acids involved interaction were identified and found to be required for induction of cell death. We also identified 5 type III effectors of the bacterial pathogen Xanthomonaseuvesicatoria that inhibited cell death induced by components of ETI-associated MAP kinase cascades. 4. Isolation of the tomato PRR FLS3 (Hind et al., submitted). FLS3, a novel PRR of the LRR-RLK family that specifically recognizes the flagellinepitope flgII-28 was isolated. FLS3 was shown to bind flgII-28, to require kinase activity for function, to act in concert with BAK1, and to enhance disease resistance to Pseudomonas syringae. 5. Functional analysis of RLCKs of the brassinosteroid signaling kinase (BSK) family.Arabidopsis and tomato BSKs were found to interact with PRRs. In addition, certain ArabidospsisBSK mutants were found to be impaired in PAMP-induced resistance to Pseudomonas syringae. Scientific and agricultural significance: Our research activities discovered and characterized new molecular components of signaling pathways mediating recognition of invading pathogens and activation of immune responses against them. Increased understanding of molecular mechanisms of immunity will allow them to be manipulated by both molecular breeding and genetic engineering to produce plants with enhanced natural defense against disease.
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Jordan, Ramon L., Abed Gera, Hei-Ti Hsu, Andre Franck, and Gad Loebenstein. Detection and Diagnosis of Virus Diseases of Pelargonium. United States Department of Agriculture, July 1994. http://dx.doi.org/10.32747/1994.7568793.bard.
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Pelargonium (Geranium) is the number one pot plant in many areas of the United States and Europe. Israel and the U.S. send to Europe rooted cuttings, foundation stocks and finished plants to supply a certain share of the market. Geraniums are propagated mainly vegetatively from cuttings. Consequently, viral diseases have been and remain a major threat to the production and quality of the crop. Among the viruses isolated from naturally infected geraniums, 11 are not specific to Pelargonium and occur in other crops while 6 other viruses seem to be limited to geranium. However, several of these viruses are not sufficiently characterized to conclude that they are distinct agents and their nomenclature and taxonomy are confusing. The ability to separate, distinguish and detect the different viruses in geranium will overcome obstacles te developing effective detection and certification schemes. Our focus was to further characterize some of these viruses and develop better methods for their detection and control. These viruses include: isolates of pelargonium line pattern virus (PLPV), pelargonium ringspot virus (PelRSV), pelargonium flower break virus (PFBV), pelargonium leaf curl (PLCV), and tomato ringspot virus (TomRSV). Twelve hybridoma cell lines secreting monoclonal antibodies specific to a geranium isolate of TomRSV were produced. These antibodies are currently being characterized and will be tested for the ability to detect TomRSV in infected geraniums. The biological, biochemical and serological properties of four isometric viruses - PLPV, PelRSV, and PFBV (and a PelRSV-like isolate from Italy called GR57) isolated from geraniums exhibiting line and ring pattern or flower break symptoms - and an isolate ol elderbeny latent virus (ELV; which the literature indicates is the same as PelRSV) have been determined Cloned cDNA copies of the genomic RNAs of these viruses were sequenced and the sizes and locations of predicted viral proteins deduced. A portion of the putative replicase genes was also sequenced from cloned RT-PCR fragments. We have shown that, when compared to the published biochemical and serological properties, and sequences and genome organizations of other small isometric plant viruses, all of these viruses should each be considered new, distinct members of the Carmovirus group of the family Tombusviridae. Hybridization assays using recombinant DNA probes also demonstrated that PLPV, PelRSV, and ELV produce only one subgenomic RNA in infected plants. This unusual property of the gene expression of these three viruses suggests that they are unique among the Carmoviruses. The development of new technologies for the detection of these viruses in geranium was also demonstrated. Hybridization probes developed to PFBV (radioactively-labeled cRNA riboprobes) and to PLPV (non-radioactive digoxigenin-labeled cDNAs) were generally shown to be no more sensitive for the detection of virus in infected plants than the standard ELISA serology-based assays. However, a reverse transcriptase-polymerase chain reaction assay was shown to be over 1000 times more sensitive in detecting PFBV in leaf extracts of infected geranium than was ELISA. This research has lead to a better understanding of the identity of the viruses infecting pelargonium and to the development of new tools that can be used in an improved scheme of providing virus-indexed pelargonium plants. The sequence information, and the serological and cloned DNA probes generated from this work, will allow the application of these new tools for virus detection, which will be useful in domestic and international indexing programs which are essential for the production of virus-free germplasm both for domestic markets and the international exchange of plant material.
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Davis, Robert E., Edna Tanne, James P. Prince, and Meir Klein. Yellow Disease of Grapevines: Impact, Pathogen Molecular Detection and Identification, Epidemiology, and Potential for Control. United States Department of Agriculture, September 1994. http://dx.doi.org/10.32747/1994.7568792.bard.
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Grapevine yellows diseases characterized by similar symptoms have been reported in several countries including Israel, the United States, France, Italy, Spain, Germany and Australia. These diseases are among the most serious known in grapevine, but precise knowledge of the pathogens' identities and modes of their spread is needed to devise effective control stratgegies. The overall goals of this project were to develop improved molecular diagnostic procedures for detection and identification of the presumed mycoplasmalike organism (MLO) pathogens, now termed phytoplasmas, and to apply these procedures to investigate impact and spread and potential for controlling grapevine yellows diseases. In the course of this research project, increased incidence of grapevine yellows was found in Israel and the United States; the major grapevine yellows phytoplasma in Israel was identified and tis 16S rRNA gene characterized; leafhopper vectors of this grapevine yellows phytoplasma in Israel were identified; a second phytoplasma was discovered in diseased grapevines in Israel; the grapevine yellows disease in the U.S. was found to be distinct from that in Israel; grapevine yellows in Virginia, USA, was found to be caused by two different phytoplasmas; both phytoplasmas in Virginia grapevines were molecularly characterized and classified; commercial grapevines in Europe were discovered to host a phytoplasma associated with aster yellow disease in the USA, but this phytoplasma has not been found in grapevine in the USA; the Australian grapevine yellows phytoplasma was found to be distinct from the grapevine phytoplasmas in Israel, the United States and Europe and was described and named "Candidatus phytoplasma australiense", and weed host plants acting as potential reservoirs of the grapevine phytoplasmas were discovered. These and other findings from the project should aid in the design and development of strategies for managing the grapevine yellows disease problem.
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Sessa, Guido, and Gregory Martin. role of FLS3 and BSK830 in pattern-triggered immunity in tomato. United States Department of Agriculture, January 2016. http://dx.doi.org/10.32747/2016.7604270.bard.
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Pattern-recognition receptors (PRRs) located on the plant cell surface initiate immune responses by perceiving conserved pathogen molecules known as pathogen-associated molecular patterns (PAMPs). PRRs typically function in multiprotein complexes that include transmembrane and cytoplasmickinases and contribute to the initiation and signaling of pattern-triggered immunity (PTI). An important challenge is to identify molecular components of PRR complexes and downstream signaling pathways, and to understand the molecular mechanisms that mediate their function. In research activities supported by BARD-4931, we studied the role of the FLAGELLIN SENSING 3 (FLS3) PRR in the response of tomato leaves to flagellin-derivedPAMPs and PTI. In addition, we investigated molecular properties of the tomato brassinosteroid signaling kinase 830 (BSK830) that physically interacts with FLS3 and is a candidate for acting in the FLS3 signaling pathway. Our investigation refers to the proposal original objectives that were to: 1) Investigate the role of FLS3 and its interacting proteins in PTI; 2) Investigate the role of BSK830 in PTI; 3) Examine molecular and phosphorylation dynamics of the FLS3-BSK830 interaction; 4) Examine the possible interaction of FLS3 and BSK830 with Pstand Xcveffectors. We used CRISPR/Cas9 techniques to develop plants carrying single or combined mutations in the FLS3 gene and in the paralogsFLS2.1 and FLS2.2 genes, which encode the receptor FLAGELLIN SENSING2 (FLS2), and analyzed their function in PTI. Domain swapping analysis of the FLS2 and FLS3 receptors revealed domains of the proteins responsible for PAMP detection and for the different ROS response initiated by flgII-28/FLS3 as compared to flg22/FLS2. In addition, in vitro kinase assays and point mutations analysis identified FLS2 and FLS3 domains required for kinase activity and ATP binding. In research activities on tomato BSK830, we found that it interacts with PRRs and with the co-receptor SERK3A and PAMP treatment affects part of these interactions. CRISPR/Cas9 bsk830 mutant plants displayed enhanced pathogen susceptibility and reduced ROS production upon PAMP treatment. In addition, BSK830 interacted with 8 Xanthomonastype III secreted effectors. Follow up analysis revealed that among these effectors XopAE is part of an operon, is translocated into plant cells, and displays E3 ubiquitinligase activity. Our investigation was also extended to other Arabidopsis and tomato BSK family members. Arabidopsis BSK5 localized to the plant cell periphery, interacted with receptor-like kinases, and it was phosphorylatedin vitro by the PEPR1 and EFRPRRs. bsk5 mutant plants displayed enhanced susceptibility to pathogens and were impaired in several, but not all, PAMP-induced responses. Conversely, BSK5 overexpression conferred enhanced disease resistance and caused stronger PTI responses. Genetic complementation suggested that proper localization, kinase activity, and phosphorylation by PRRs are critical for BSK5 function. BSK7 and BSK8 specifically interacted with the FLS2 PRR, their respective mutant plants were more susceptible to B. cinereaand displayed reduced flg22-induced responses. The tomato BSK Mai1 was found to interact with the M3KMAPKKK, which is involved in activation of cell death associated with effector-triggered immunity. Silencing of Mai1 in N. benthamianaplants compromised cell death induced by a specific class of immune receptors. In addition, co-expression of Mai1 and M3Kin leaves enhanced MAPKphosphorylation and cell death, suggesting that Mai1 acts as a molecular link between pathogen recognition and MAPK signaling. Finally, We identified the PP2C phosphatase Pic1 that acts as a negative regulator of PTI by interacting with and dephosphorylating the receptor-like cytoplasmickinase Pti1, which is a positive regulator of plant immunity. The results of this investigation shed new light on the molecular characteristics and interactions of components of the immune system of crop plants providing new knowledge and tools for development of novel strategies for disease control.
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Boyle, M., and Elizabeth Rico. Terrestrial vegetation monitoring at Fort Matanzas National Monument: 2019 data summary. National Park Service, May 2022. http://dx.doi.org/10.36967/nrds-2293409.
Full textAbstract:
The Southeast Coast Network (SECN) conducts long-term terrestrial vegetation monitoring as part of the nationwide Inventory and Monitoring Program of the National Park Service (NPS). The vegetation community vital sign is one of the primary-tier resources identified by SECN park managers, and it is currently conducted at 15 network parks (DeVivo et al. 2008). Monitoring plants and their associated communities over time allows for targeted understanding of ecosystems within the SECN geography, which provides managers information about the degree of change within their parks’ natural vegetation. 2019 marks the first year of conducting this monitoring effort at four SECN parks, including Fort Matanzas National Monument (FOMA). Nine vegetation plots, located on Anastasia and Rattlesnake Islands, were established at Fort Matanzas National Monument in June. Data collected in each plot included species richness across multiple spatial scales, species-specific cover and constancy, species-specific woody stem seedling/sapling counts and adult tree (greater than 10 centimeters [3.9 inches {in}]) diameter at breast height (DBH), overall tree health, landform, soil, observed disturbance, and woody biomass (i.e., fuel load) estimates. This report summarizes the baseline (year 1) terrestrial vegetation data collected at Fort Matanzas National Monument in 2019. Data were stratified across two dominant broadly defined habitats within the park (Maritime Upland Forests/Shrublands and Maritime Open Uplands). Noteworthy findings include: Eighty-two vascular plant taxa (species or lower) were observed across nine vegetation plots, including eight species not previously documented within the park. The most frequently encountered species in each broadly defined habitat included: Maritime Upland Forests and Shrublands: saw palmetto (Serenoa repens), yaupon (Ilex vomitoria), southern/eastern red cedar (Juniperus silicicola + virginiana), American beautyberry (Callicarpa americana), and American burnweed (Erectites hieraciifolius). Maritime Open Uplands: sea oats (Uniola paniculata), earleaf greenbriar (Smilax auriculata), and dixie sandmat (Euphorbia bombensis). ne non-native species, Brazilian pepper (Schinus terebinthifolia), categorized as invasive by the Florida Exotic Pest Plant Council (FLEPPC 2019) was encountered in one Maritime Upland Forest and Shrubland plot during this monitoring effort. There were not any rare plants tracked by the Florida Department of Agriculture and Consumer Services (FDACS 2020) found during this monitoring effort. All plants located in these monitoring plots are fairly common throughout Florida, as well as across the Southeast Coast. Three species observed, however, are on the FDACS 2020 list of commercially exploited plants within the state. These include saw palmetto, cinnamon fern (Osmundastrum cinnamomeum), and coontie (Zamia integrifolia var. umbrosa). Southern/eastern red cedar and cabbage palmetto (Sabal palmetto) were the most dominant species within the tree stratum of the Maritime Upland Forest and Shrubland habitat type. Species that dominated the sapling and seedling strata of this type included yaupon and cabbage palmetto. More than 75% of the trees measured in the parks Maritime Upland Forest and Shrubland habitat type were alive and experiencing healthy vigor. Of the 22 trees that were dead, more than 50% of those were southern/eastern red cedar. Most of those individuals that were observed with moderate or severe decline and greater than 50% dieback were southern/eastern red cedars. Although red bay (Persea borbonia) was identified as one of the “principal understory tree” species within Fort Matanzas National Monument’s maritime forests in 2004 (Zomlefer et al. 2004), tree-sized individuals were rarely detected on plots during this monitoring effort. This may be in part due to the detection of laurel wilt disease within St. Johns County in 2006 (USDA 2021). Based on the low detection...
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Gafny, Ron, A. L. N. Rao, and Edna Tanne. Etiology of the Rugose Wood Disease of Grapevine and Molecular Study of the Associated Trichoviruses. United States Department of Agriculture, September 2000. http://dx.doi.org/10.32747/2000.7575269.bard.
Full textAbstract:
Rugose wood is a complex disease of grapevines, characterized by modification of the woody cylinder of affected vines. The control of rugose wood is based on the production of healthy propagation material. Detection of rugose wood in grapevines is difficult and expensive: budwood from tested plants is grafted onto sensitive Vitis indicators and the appearance of symptoms is monitored for 3 years. The etiology of rugose wood is complex and has not yet been elucidated. Several elongated clostero-like viruses are consistently found in affected vines; one of them, grapevine virus A (GVA), is closely associated with Kober stem grooving, a component of the rugose wood complex. GVA has a single-stranded RNA genome of 7349 nucleotides, excluding a polyA tail at the 3' terminus. The GVA genome includes five open reading frames (ORFs 1-5). ORF 4, which encodes for the coat protein of GVA, is the only ORF for which the function was determined experimentally. The original objectives of this research were: 1- To produce antisera to the structural and non-structural proteins of GVA and GVB and to use these antibodies to establish an effective detection method. 2- Develop full length infectious cDNA clones of GVA and GVB. 3- Study the roll of GVA and GVB in the etiology of the grapevine rugose wood disease. 4- Determine the function of Trichovirus (now called Vitivirus) encoded genes in the virus life cycle. Each of the ORFs 2, 3, 4 and 5 genes of GVA were cloned and expressed in E. coli and used to produce antisera. Both the CP (ORF 4) and the putative MP (ORF 3) were detected with their corresponding antisera in-GVA infected N. benthamiana and grapevine. The MP was first detected at an early stage of the infection, 6-12 h after inoculation, and the CP 2-3 days after inoculation. The MP could be detected in GVA-infected grapevines that tested negative for CP, both with CP antiserum and with a commercially available ELISA kit. Antisera to ORF 2 and 5 encoded proteins could react with the recombinant proteins but failed to detect both proteins in GVA infected plants. A full-length cDNA clone of grapevine virus A (GVA) was constructed downstream from the bacteriophage T7 RNA polymerase promoter. Capped in vitro transcribed RNA was infectious in N. benthamiana and N. clevelandii plants. Symptoms induced by the RNA transcripts or by the parental virus were indistinguishable. The infectivity of the in vitro-transcribed RNA was confirmed by serological detection of the virus coat and movement proteins and by observation of virions by electron microscopy. The full-length clone was modified to include a gus reporter gene and gus activity was detected in inoculated and systemic leaves of infected plants. Studies of GVA mutants suggests that the coat protein (ORF 4) is essential for cell to cell movement, the putative movement protein (ORF 3) indeed functions as a movement protein and that ORF 2 is not required for virus replication, cell to cell or systemic movement. Attempts to infect grapevines by in-vitro transcripts, by inoculation of cDNA construct in which the virus is derived by the CaMV 35S promoter or by approach grafting with infected N. benthamiana, have so far failed. Studies of the subcellular distribution of GFP fusion with each of ORF 2, 3 and 4 encoded protein showed that the CP fusion protein accumulated as a soluble cytoplasmatic protein. The ORF 2 fusion protein accumulated in cytoplasmatic aggregates. The MP-GFP fusion protein accumulated in a large number of small aggregates in the cytoplasm and could not move from cell to cell. However, in conditions that allowed movement of the fusion protein from cell to cell (expression by a PVX vector or in young immature leaves) the protein did not form cytoplasmatic aggregates but accumulated in the plasmodesmata.
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Chen, Yona, Jeffrey Buyer, and Yitzhak Hadar. Microbial Activity in the Rhizosphere in Relation to the Iron Nutrition of Plants. United States Department of Agriculture, October 1993. http://dx.doi.org/10.32747/1993.7613020.bard.
Full textAbstract:
Iron is the fourth most abundant element in the soil, but since it forms insoluble hydroxides at neutral and basic pH, it often falls short of meeting the basic requirements of plants and microorganisms. Most aerobic and facultative aerobic microorganisms possess a high-affinity Fe transport system in which siderophores are excreted and the consequent Fe complex is taken up via a cognate specific receptor and a transport pathway. The role of the siderophore in Fe uptake by plants and microorganisms was the focus of this study. In this research Rhizopus arrhizus was found to produce a novel siderophore named Rhizoferrin when grown under Fe deficiency. This compound was purified and its chemical structure was elucidated. Fe-Rhizoferrin was found to alleviate Fe deficiency when applied to several plants grown in nutrient solutions. It was concluded that Fe-Rhizoferrin is the most efficient Fe source for plants when compared with other among microbial siderophores known to date and its activity equals that of the most efficient synthetic commercial iron fertilizer-Fe EDDHA. Siderophores produced by several rhizosphere organisms including Rhizopus Pseudomonas were purified. Monoclonal antibodies were produced and used to develop a method for detection of the siderophores produced by plant-growth-promoting microorganisms in barley rhizosphere. The presence of an Fe-ferrichrome uptake in fluorescent Pseudomonas spp. was demonstrated, and its structural requirements were mapped in P. putida with the help of biomimetic ferrichrome analogs. Using competition experiments, it was shown that FOB, Cop B and FC share at least one common determinant in their uptake pathway. Since FC analogs did not affect FOB or Cop-mediated 55Fe uptake, it could be concluded that these siderophores make use of a different receptor(s) than FC. Therefore, recognition of Cop, FOB and FC proceeds through different receptors having different structural requirements. On the other hand, the phytosiderophores mugineic acid (MA and DMA), were utilized indirectly via ligand exchange by P. putida. Receptors from different biological systems seem to differ in their structural requirements for siderophore recognition and uptake. The design of genus- or species-specific drugs, probes or chemicals, along with an understanding of plant-microbe and microbe-microbe relationships as well as developing methods to detect siderophores using monoclonal antibodies are useful for manipulating the composition of the rhizosphere microbial population for better plant growth, Fe-nutrition and protection from diseases.
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Sela, Hanan, Eduard Akhunov, and Brian J. Steffenson. Population genomics, linkage disequilibrium and association mapping of stripe rust resistance genes in wild emmer wheat, Triticum turgidum ssp. dicoccoides. United States Department of Agriculture, January 2014. http://dx.doi.org/10.32747/2014.7598170.bard.
Full textAbstract:
The primary goals of this project were: (1) development of a genetically characterized association panel of wild emmer for high resolution analysis of the genetic basis of complex traits; (2) characterization and mapping of genes and QTL for seedling and adult plant resistance to stripe rust in wild emmer populations; (3) characterization of LD patterns along wild emmer chromosomes; (4) elucidation of the multi-locus genetic structure of wild emmer populations and its correlation with geo-climatic variables at the collection sites. Introduction In recent years, Stripe (yellow) rust (Yr) caused by Pucciniastriiformis f. sp. tritici(PST) has become a major threat to wheat crops in many parts of the world. New races have overcome most of the known resistances. It is essential, therefore, that the search for new genes will continue, followed by their mapping by molecular markers and introgression into the elite varieties by marker-assisted selection (MAS). The reservoir of genes for disease and pest resistance in wild emmer wheat (Triticumdicoccoides) is an important resource that must be made available to wheat breeders. The majority of resistance genes that were introgressed so far in cultivated wheat are resistance (R) genes. These genes, though confering near-immunity from the seedling stage, are often overcome by the pathogen in a short period after being deployed over vast production areas. On the other hand, adult-plant resistance (APR) is usually more durable since it is, in many cases, polygenic and confers partial resistance that may put less selective pressure on the pathogen. In this project, we have screened a collection of 480 wild emmer accessions originating from Israel for APR and seedling resistance to PST. Seedling resistance was tested against one Israeli and 3 North American PST isolates. APR was tested on accessions that did not have seedling resistance. The APR screen was conducted in two fields in Israel and in one field in the USA over 3 years for a total of 11 replicates. We have found about 20 accessions that have moderate stripe rust APR with infection type (IT<5), and about 20 additional accessions that have novel seedling resistance (IT<3). We have genotyped the collection using genotyping by sequencing (GBS) and the 90K SNP chip array. GBS yielded a total 341K SNP that were filtered to 150K informative SNP. The 90K assay resulted in 11K informative SNP. We have conducted a genome-wide association scan (GWAS) and found one significant locus on 6BL ( -log p >5). Two novel loci were found for seedling resistance. Further investigation of the 6BL locus and the effect of Yr36 showed that the 6BL locus and the Yr36 have additive effect and that the presence of favorable alleles of both loci results in reduction of 2 grades in the IT score. To identify alleles conferring adaption to extreme climatic conditions, we have associated the patterns of genomic variation in wild emmer with historic climate data from the accessions’ collection sites. The analysis of population stratification revealed four genetically distinct groups of wild emmer accessions coinciding with their geographic distribution. Partitioning of genomic variance showed that geographic location and climate together explain 43% of SNPs among emmer accessions with 19% of SNPs affected by climatic factors. The top three bioclimatic factors driving SNP distribution were temperature seasonality, precipitation seasonality, and isothermality. Association mapping approaches revealed 57 SNPs associated with these bio-climatic variables. Out of 21 unique genomic regions controlling heading date variation, 10 (~50%) overlapped with SNPs showing significant association with at least one of the three bioclimatic variables. This result suggests that a substantial part of the genomic variation associated with local adaptation in wild emmer is driven by selection acting on loci regulating flowering. Conclusions: Wild emmer can serve as a good source for novel APR and seedling R genes for stripe rust resistance. APR for stripe rust is a complex trait conferred by several loci that may have an additive effect. GWAS is feasible in the wild emmer population, however, its detection power is limited. A panel of wild emmer tagged with more than 150K SNP is available for further GWAS of important traits. The insights gained by the bioclimatic-gentic associations should be taken into consideration when planning conservation strategies.
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Cohen, Yuval, Christopher A. Cullis, and Uri Lavi. Molecular Analyses of Soma-clonal Variation in Date Palm and Banana for Early Identification and Control of Off-types Generation. United States Department of Agriculture, October 2010. http://dx.doi.org/10.32747/2010.7592124.bard.
Full textAbstract:
Date palm (Phoenix dactylifera L.) is the major fruit tree grown in arid areas in the Middle East and North Africa. In the last century, dates were introduced to new regions including the USA. Date palms are traditionally propagated through offshoots. Expansion of modern date palm groves led to the development of Tissue Culture propagation methods that generate a large number of homogenous plants, have no seasonal effect on plant source and provide tools to fight the expansion of date pests and diseases. The disadvantage of this procedure is the occurrence of off-type trees which differ from the original cultivar. In the present project we focused on two of the most common date palm off-types: (1) trees with reduced fruit setting, in which most of the flowers turn into three-carpel parthenocarpic fruits. In a severe form, multi-carpel flowers and fruitlets (with up to six or eight carpels instead of the normal three-carpel flowers) are also formed. (2) dwarf trees, having fewer and shorter leaves, very short trunk and are not bearing fruits at their expected age, compared to the normal trees. Similar off-types occur in other crop species propagated by tissue culture, like banana (mainly dwarf plants) or oil palm (with a common 'Mantled' phenotype with reduced fruit setting and occurrence of supernumerary carpels). Some off-types can only be detected several years after planting in the fields. Therefore, efficient methods for prevention of the generation of off-types, as well as methods for their detection and early removal, are required for date palms, as well as for other tissue culture propagated crops. This research is aimed at the understanding of the mechanisms by which off-types are generated, and developing markers for their early identification. Several molecular and genomic approaches were applied. Using Methylation Sensitive AFLP and bisulfite sequencing, we detected changes in DNA methylation patterns occurring in off-types. We isolated and compared the sequence and expression of candidate genes, genes related to vegetative growth and dwarfism and genes related to flower development. While no sequence variation were detected, changes in gene expression, associated with the severity of the "fruit set" phenotype were detected in two genes - PdDEF (Ortholog of rice SPW1, and AP3 B type MADS box gene), and PdDIF (a defensin gene, highly homologous to the oil palm gene EGAD). We applied transcriptomic analyses, using high throughput sequencing, to identify genes differentially expressed in the "palm heart" (the apical meristem and the region of embryonic leaves) of dwarf vs. normal trees. Among the differentially expressed genes we identified genes related to hormonal biosynthesis, perception and regulation, genes related to cell expansion, and genes related to DNA methylation. Using Representation Difference Analyses, we detected changes in the genomes of off-type trees, mainly chloroplast-derived sequences that were incorporated in the nuclear genome and sequences of transposable elements. Sequences previously identified as differing between normal and off-type trees of oil palms or banana, successfully identified variation among date palm off-types, suggesting that these represent highly labile regions of monocot genomes. The data indicate that the date palm genome, similarly to genomes of other monocot crops as oil palm and banana, is quite unstable when cells pass through a cycle of tissue culture and regeneration. Changes in DNA sequences, translocation of DNA fragments and alteration of methylation patterns occur. Consequently, patterns of gene expression are changed, resulting in abnormal phenotypes. The data can be useful for future development of tools for early identification of off-type as well as for better understanding the phenomenon of somaclonal variation during propagation in vitro.