Academic literature on the topic 'Grey blight disease'

We proposed a novel deep convolutional neural network (DCNN) using inverted residuals and linear bottleneck layers for diagnosing grey blight disease on tea leaves. The proposed DCNN consists of three bottleneck blocks, two pairs of convolutional (Conv) layers, and three dense layers. The bottleneck blocks contain depthwise, standard, and linear convolution layers. A single-lens reflex digital image camera was used to collect 1320 images of tea leaves from the North Bengal region of India for preparing the tea grey blight disease dataset. The nongrey blight diseased tea leaf images in the dataset were categorized into two subclasses, such as healthy and other diseased leaves. Image transformation techniques such as principal component analysis (PCA) color, random rotations, random shifts, random flips, resizing, and rescaling were used to generate augmented images of tea leaves. The augmentation techniques enhanced the dataset size from 1320 images to 5280 images. The proposed DCNN model was trained and validated on 5016 images of healthy, grey blight infected, and other diseased tea leaves. The classification performance of the proposed and existing state-of-the-art techniques were tested using 264 tea leaf images. Classification accuracy, precision, recall, F measure, and misclassification rates of the proposed DCNN are 98.99%, 98.51%, 98.48%, 98.49%, and 1.01%, respectively, on test data. The test results show that the proposed DCNN model performed superior to the existing techniques for tea grey blight disease detection.

Grey blight is a foliar disease of tea plants (Camellia sinensis) caused by Pestalotiopsis. The grey blight pathogen was isolated from infected leaves of tea plants in the National Tea and High Value Crop Research Institute (NTHRI), Shinkiari, Khyber Pakhtunkhwa, Pakistan. Eight different varieties, Indonesian, Roupi, Jue King, P-5, P-3, Qi man, Chuy and P-1, were investigated for yield loss and resistance against the grey blight disease. All varieties displayed considerably different levels of resistance to Pestalotiopsis (p<0.05). The most resistant variety was Indonesian, which showed the lowest number of lesions (1.5 leaf-1) and the smallest lesion diameter (3.0 cm), whereas the most susceptible variety was P-1 which showed the highest number of lesions (3.83 leaf-1) and the largest lesion diameter (15.0 cm). The grey leaf blight pathogen significantly affected biomass and dry matter of the tested varieties. Compared to non-inoculated control, inoculation with Pestalotiopsis reduced the number of leaves by 40% (p<0.05), fresh leaf weight by 31% (p<0.05) and dry leaf weight by 59% (p<0.05). Whereas, the Indonesian variety was the least affected showing only 11% (p<0.05), 19% (p<0.05), and 28% (p<0.05) reduction in number of leaves, fresh weight and dry weight, respectively, over control. These results showed that Pestalotiopsis significantly reduced tea yield and that this disease can be managed by growing resistant varieties.

Grey blight disease caused by Pestalotiopsis disseminata, is one of the major foliar fungal diseases that constantly affects Persea bombycina Kost, a primary host plant of muga silkworm. Under nursery condition, grey blight disease was recorded mostly in SS and S6 morphotypes of som plants. Vermicompost, PGPR and AMF, alone and in combination were applied for the improvement of the growth of eight morphotypes of som plant as well as to reduce incidence. Growth in terms of height (cm), no. of leaves and no. of branches were studied. Analysis of some major defence related enzymes such as POX, PAL, CHT and GLU was also carried out to check induction of resistance after treatment. Artificial inoculation of som plants under nursery condition with spore suspension of P. disseminata was performed and disease progression noted for 7, 14, 21 and 28 days. It was clearly seen that disease progression was slow and less in treated inoculated plants. The results emphasize the fact that application of bioinoculants can be studied in larger scale for the upliftment of the health status of muga host plants.

Grey Blight of Mustard caused by Alternaria sp. is one of the most important diseases of oil producing crop of Bangladesh causing heavy yield loss which is approximately 30-40%. In this study the effectiveness of selected botanicals, chemicals and their combined effects were assessed to manage this disease. Fourteen treatments including control were evaluated viz. T1= Control, T2= Trichoderma harzianum suspension, T3= Autostin 50 WDG, T4= Rovral 50 WP, T5= Dithane M- 45, T6= Amistar Top 325 SC, T7= Neem leaf extract, T8= Allamanda leaf extract, T9 = Lantana leaf extract, T10= Datura leaf extract, T11= Neem leaf extract+ Rovral, T12= Datura leaf extract + Amistar Top, T13= Lantana leaf extract + Dithane M- 45 and T14= Allamanda leaf extract + Autostin. Among the chemicals, the lowest disease incidence (%), disease severity (%), disease severity index (%) and pod infection (%) was found in T5 treatment (Dithane M-45) which was 55.91%, 22.09%, 32.16% and 6.72%, respectively, at 70 and 75 DAS, respectively. While among the botanicals, the lowest disease incidence (%), disease severity (%), disease severity index (%) and pod infection (%) was found in T9 treatment (Lantana leaf extract) which was 65.05%, 28.89%, 37.96% and 13.79%, respectively, at 70 and 75 DAS, respectively. In case of combined treatments, the lowest disease incidence (%), disease severity (%), disease severity index (%) and pod infection (%) was found in T13 treatment (Lantana leaf extract + Dithane M-45) which was 59.14%, 26.32%, 38.20% and 12.30%, respectively, at 70 and 75 DAS respectively. While the highest disease incidence (%), disease severity (%), disease severity index (%) and pod infection (%) was found in T1 treatment (Control) which was 79.20%, 37.54%, 67.38% and 34.63%, respectively, 70 and 75 DAS, respectively. Among the treatments yield and yield attributers were found better in T5 (Dithane M-45), T9 (Lantana leaf extract) and T13 (Lantana leaf extract + Dithane M-45). From the results on different parameters studied, the treatment Lantana leaf extract (T9), Dithane M-45 (T5) and their combined treatment (T13) can be used for management of grey blight mustard after few field trialing in consecutive year. SAARC J. Agric., 19(2): 219-232 (2021)

Tea grey blight disease is one of the most destructive diseases that infects tea and is caused by the pathogen Pestalotiopsis theae (Sawada) Steyaert. L-theanine is a unique non-protein amino acid of the tea plant. Different concentrations of L-theanine exhibit significant inhibitory effects on the growth and sporulation ability of the pathogen causing tea grey blight disease. To understand the effect mechanism of L-theanine on P. theae, transcriptome profiling was performed on the pathogenic mycelium treated with three different concentrations of L-theanine: no L-theanine treatment (TH0), 20 mg/mL theanine treatment (TH2), and 40 mg/mL theanine treatment (TH4). The colony growths were significantly lower in the treatment with L-theanine than those without L-theanine. The strain cultured with a high concentration of L-theanine produced no spores or only a few spores. In total, 2344, 3263, and 1158 differentially expressed genes (DEGs) were detected by RNA-sequencing in the three comparisons, Th2 vs. Th0, Th4 vs. Th0, and Th4 vs. Th2, respectively. All DEGs were categorized into 24 distinct clusters. According to GO analysis, low concentrations of L-theanine primarily affected molecular functions, while high concentrations of L-theanine predominantly affected biological processes including external encapsulating structure organization, cell wall organization or biogenesis, and cellular amino acid metabolic process. Based on KEGG, the DEGs of Th2 vs. Th0 were primarily involved in pentose and glucuronate interconversions, histidine metabolism, and tryptophan metabolism. The DEGs of Th4 vs. Th0 were mainly involved in starch and sucrose metabolism, amino sugar, and nucleotide sugar metabolism. This study indicated that L-theanine has a significant impact on the growth and sporulation of the pathogen of tea grey blight disease and mainly affects amino acid metabolism, carbohydrate metabolism, and cellular structure-related biosynthesis processes of pathogenic fungi. This work provides insights into the direct control effect of L-theanine on pathogenic growth and also reveals the molecular mechanisms of inhibition of L-theanine to P. theae.

Leaf diseases on tea plants affect the quality of tea. This issue must be overcome since preparing tea drinks requires high-quality tea leaves. Various automatic models for identifying disease in tea leaves have been developed; however, their performance is typically low since the extracted features are not selective enough. This work presents a classification model for tea leaf disease that distinguishes six leaf classes: algal spot, brown, blight, grey blight, helopeltis, red spot, and healthy. Deep learning using a convolutional neural network (CNN) builds an effective model for detecting tea leaf illness. The Kaggle public dataset contains 5,980 tea leaf images on a white background. Pre-processing was performed to reduce computing time, which involved shrinking and normalizing the image prior to augmentation. Augmentation techniques included rotation, shear, flip horizontal, and flip vertical. The CNN model was used to classify tea leaf disease using the MobileNetV2 backbone, Adam optimizer, and rectified linear unit (ReLU) activation function with 224×224 input data. The proposed model attained the highest performance, as evidenced by the accuracy value 0.9455.

To analyze the effect of different pruning operation on the incidence and severity of different diseases of tea (Camellia sinensis) plant. An experiment was carried out at the Bilashchara Experimental Farm of Bangladesh Tea Research Institute (BTRI), Srimangal. Three places of the sections were selected randomly that received LP (Light Prune), DSK (deep skiff), MSK (medium skiff) and LSK (light skiff) operations. Every bush was critically observed before and after pruning operations and all infected diseases were recorded. Disease severity was expressed as percent disease index (PDI). MSTAT program was used for statistical snalysis. After pruning operation, maximum incidence 33.33% and severity 8.20% of Grey brown blight was found in LSK. Horse hair blight maximum incidence (18%) and maximum severity (6.27%) both were found in LSK. In thread blight maximum incidence was in MSK 22.67% and maximum severity was 7% in LSK. The highest % reduction of branch canker both in incidence and severity was observed in LP section followed by DSK, MSK and LSK. In case of Gall disease maximum incidence and severity both was LSK 24.67% and 7.60%. The highest incidence of black rot was in LSK 41.33% and severity 12.87% was in MSK. From the study, it was recommending that without using any chemicals, only by different pruning operations and proper cleaning can reduce the in incidence and severity of those diseases.J. bio-sci. 24: 01-09, 2016

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O milho é uma das culturas mais extensamente cultivadas em todo mundo. A incidência e a severidade de doenças têm aumentado significativamente nos últimos anos acarretando perdas no rendimento e afetando a qualidade dos grãos. Muitos trabalhos têm sido desenvolvidos na tentativa de identificar híbridos resistentes às principais doenças que acometem a cultura do milho, mas poucos são os relatos de estudos com linhagens. Dessa forma, o objetivo deste estudo foi: 1) identificar linhagens resistentes e susceptíveis com base na área abaixo da curva de progresso de doenças (AACPD) para os sintomas de ferrugem tropical (TR), ferrugem polissora (SR), cercosporiose (GLS), helmintosporiose (NLB), mancha marrom (PBS) e mancha branca (PLS); 2) identificar linhagens resistentes e suscetíveis com base nos parâmetros de adaptabilidade e estabilidade fenotípica para os sintomas de cercosporiose, helmintosporiose, mancha marrom e mancha branca; 3) identificar as melhores datas de semeadura, com a maior ocorrência das doenças, para fins de avaliação de linhagens e outros genótipos para resistência. Cinquenta linhagens, derivadas de populações com grãos flint e dent, foram avaliadas em blocos casualizados com três repetições, aos 45, 60, 75 e 90 dias após a semeadura em duas épocas, para medição da AACPD. Para a análise de adaptabilidade e estabilidade, 41 linhagens foram avaliadas em blocos casualizados com três repetições, 30 dias após o florescimento feminino, em onze épocas de semeadura, usando o método de análise de regressão. Foram atribuídas notas de 1, 2, 3, 4, 5, 6, 7, 8 e 9 correspondendo a 0, 1, 10, 20, 30, 40, 60, 80 e > 80% de área foliar com sintomas de doença. Para a AACPD, a análise de variância conjunta foi significativa para TR, SR, GLS e PLS e a interação linhagens x épocas foi significativa para ferrugem tropical e polissora. Para GLS e NLB as 41 linhagens foram classificadas como resistentes, sendo que as maiores severidades de doenças ocorreram nas semeaduras entre Junho e Setembro. As linhagens IVF1-3, IVF1-7, IVF1 -9, IVF1-10, IVF1 -11, IVF1 -25, IVF1-230, IVD1-2, IVD1 -2-1, IVD1-3, IVD1-9, IVD1 -12, 2F, 3F, 6F, 9F, 10F, 4C, 2D e 7D foram classificadas como resistentes para as doenças estudadas, sendo indicadas para o desenvolvimento de sintéticos. Para a mancha marrom e mancha branca, as semeaduras de Abril, Junho, Julho e Agosto apresentaram maiores severidades de doenças. As linhagens IVD1-9, IVD1-10, 7D, 10D e 2F podem ser indicadas no desenvolvimento de sintéticos resistentes.
Corn is one of the most widely cultivated crops in the worldwide. The incidence and severity of diseases affecting crops have increased significantly in the past years, leading to yield losses and affecting grain quality. Many studies have been carried out with the attempt to identify hybrids that are resistant to the main diseases, but few reports have studied inbred lines. Therefore, the objectives of this study were: 1) identify resistant and susceptible inbred lines based on the area under disease progress curve (AUDPC) for tropical rust, southern rust, gray leaf spot, northern leaf blight, physoderma brown spot and phaeosphaeria leaf spot; 2) identify resistant and susceptible inbred lines based on adaptability and stability parameters for symptoms of gray leaf spot (GLS), northern leaf blight (NLB), physoderma brown spot (PBS) and phaeosphaeria leaf spot (PLS); 3) identify the best planting dates, with the highest occurrence of diseases, for the purpose of evaluating inbred lines and other genotypes for resistance. For AUDPC, fifty inbred lines, derived from populations with flint and dent grains, were evaluated in randomized block designs with three replications, at 45, 60, 75 and 90 days after planting in two seasons. For the analysis of adaptability and stability, forty-one inbred lines were evaluated in randomized blocks with three replications, 30 days after silking, in eleven planting dates, using regression analysis method. The scale of scores from 1, 2, 3, 4, 5, 6, 7, 8 and 9 corresponding to 0, 1, 10, 20, 30, 40, 60, 80 and > 80% of leaf area with disease symptoms was used. For AUDPC, the joint analysis of variance was significant for TR, SR, GLS and PLS, while the interaction inbred lines x environments, was significant for TR and SR. For GLS and NLB, forty-one inbred lines were classified as resistant and the highest severities of diseases occurred in planting dates between June and September. The inbred lines IVF1-3, IVF1-7, IVF1 -9, IVF1-10, IVF1 -11, IVF1 -25, IVF1-230, IVD1-2, IVD1 -2-1, IVD1-3, IVD1-9, IVD1 -12, 2F, 3F, 6F, 9F, 10F, 4C, 2D and 7D were classified as resistant to the diseases studied and are indicated to produce synthetics. For PBS and PLS, the plating dates of April, June, July and August showed higher disease severity. The inbred lines IVD1-9, IVD1-10, 7D,10D and 2F may be indicated to produce synthetics.

Orientador: João Antonio da Costa Andrade
Resumo: O milho é uma das culturas mais extensamente cultivadas em todo mundo. A incidência e a severidade de doenças têm aumentado significativamente nos últimos anos acarretando perdas no rendimento e afetando a qualidade dos grãos. Muitos trabalhos têm sido desenvolvidos na tentativa de identificar híbridos resistentes às principais doenças que acometem a cultura do milho, mas poucos são os relatos de estudos com linhagens. Dessa forma, o objetivo deste estudo foi: 1) identificar linhagens resistentes e susceptíveis com base na área abaixo da curva de progresso de doenças (AACPD) para os sintomas de ferrugem tropical (TR), ferrugem polissora (SR), cercosporiose (GLS), helmintosporiose (NLB), mancha marrom (PBS) e mancha branca (PLS); 2) identificar linhagens resistentes e suscetíveis com base nos parâmetros de adaptabilidade e estabilidade fenotípica para os sintomas de cercosporiose, helmintosporiose, mancha marrom e mancha branca; 3) identificar as melhores datas de semeadura, com a maior ocorrência das doenças, para fins de avaliação de linhagens e outros genótipos para resistência. Cinquenta linhagens, derivadas de populações com grãos flint e dent, foram avaliadas em blocos casualizados com três repetições, aos 45, 60, 75 e 90 dias após a semeadura em duas épocas, para medição da AACPD. Para a análise de adaptabilidade e estabilidade, 41 linhagens foram avaliadas em blocos casualizados com três repetições, 30 dias após o florescimento feminino, em onze épocas de semeadura, us... (Resumo completo, clicar acesso eletrônico abaixo)
Doutor

The detection of corn (maize) crop diseases is traditionally carried out by farmers, based on their experience accumulated over a period of field practice. However, the visual observation may represent a risk of error due to subjective perception. This article presents an approach based on Deep Learning to identify diseases that affect corn crops. A public database with 3,852 images of maize plant leaves was used, dividedinto four classes: healthy corn, exserohilun leaf spot (northern leaf blight), common corn rust (common rust) and cercosporiosis (cercospora leaf/gray leaf). The proposed model used Convolutional Neural Networks (CNN) techniques for image classification. The four experiments indicated results with an average accuracy above 94.5%. These results in the identification and diagnosis of plant diseases can contribute significantly as atool to the improvement of the production chain that affect corn crops. All data are available at https://github.com/npcaufra/classificacao-doencas-milho .

The goal of this project is to enhance fungal resistance of carnation and tomato through the ectopic expression of osmotin and other pathogenesis-related (PR) proteins. The research objectives were to evaluate in vitro antifungal activity of osmotin and osmotin and other PR protein combinations against phytopathogens (including Fusarium oxysporum, Verticillium dahliae, Botrytus cinerea or Phytophthora infestans), develop protocols for efficient transformation of carnation and tomato, express PR proteins in transgenic carnation and tomato and evaluate fungal resistance of transgenic plants. Protocols for microprojectile bombardment and Agrobacterium-mediated transformation of carnation were developed that are applicable for the biotechnology of numerous commercial cultivars. Research established an efficient organogenetic regeneration system, optimized gene delivery and transgene expression and defined parameters requisite to the high frequency recovery of transgenic plants. Additionally, an efficient Agrobacterium-mediated transformation protocol was developed for tomato that is applicable for use with numerous commercial varieties. Rigorous selection and reducing the cytokinin level in medium immediately after shoot induction resulted in substantially greater frequency of adventitious shoots that developed defined stems suitable for rooting and reconstitution of transgenic plants. Transformation vectors were constructed for co-expression of genes encoding osmotin and tobacco chitinase Ia or PR-1b. Expression of osmotin, PR-1 and/or chitinase in transgenic carnation mediated a high level resistance of cv. White Sim (susceptible variety) to F. oxysporum f. sp. dianthi, race 2 in greenhouse assays. These plants are being evaluated in field tests. Comprehensive analysis (12 to 17 experiments) indicated that germination of B. cinerea conidia was unaffected by PR protein expression but germ tube elongation was reduced substantially. The disease severity was significantly attenuated by PR protein expression. Constitutive expression of osmotin in transgenic tomato increased resistance to B. cinerea, and P. infestans. Grey mold and late blight resistance was stable through the third selfed generation. The research accomplished in this project will have profound effects on the use of biotechnology to improve carnation and tomato. Transformation protocols that are applicable for efficient stable gene transfer to numerous commercial varieties of carnation and tomato are the foundation for the capacity to bioengineer these crops. The research further establishes that PR proteins provide a measure of enhanced disease resistance. However, considerations of PR protein combinations and conditional regulation and targeting are likely required to achieve; sustained level of resistance.