Artículos de revistas: "Grey blight disease"

1

Pandian, J. Arun, Sam Nirmala Nisha, K. Kanchanadevi, Abhay K. Pandey y Samira Kabir Rima. "Grey Blight Disease Detection on Tea Leaves Using Improved Deep Convolutional Neural Network". Computational Intelligence and Neuroscience 2023 (17 de enero de 2023): 1–11. http://dx.doi.org/10.1155/2023/7876302.

Texto completo

Resumen

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.

Los estilos APA, Harvard, Vancouver, ISO, etc.

2

Akbar, Asma, Gul Shad Ali, Brian Pearson, Farrukh Hamid y Sonia Sumreen. "Screening Camelia sinensis Germplasm Against Grey Leaf Blight of Tea". Journal of Agricultural Studies 5, n.º 4 (20 de noviembre de 2017): 123. http://dx.doi.org/10.5296/jas.v5i4.11991.

Texto completo

Resumen

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.

Los estilos APA, Harvard, Vancouver, ISO, etc.

3

Acharya, A., Usha Chakraborty, S. Ghosh y Biswanath Chakraborty. "Management of grey blight disease of Som plants using value added vermicompost with Glomus constrictum and Bacillus altitudinis". NBU Journal of Plant Sciences 9, n.º 1 (2015): 46–53. http://dx.doi.org/10.55734/nbujps.2015.v09i01.006.

Texto completo

Resumen

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.

Los estilos APA, Harvard, Vancouver, ISO, etc.

4

Kabir, MH, YA Ara, AJM Moin Uddin, MA Islam y MB Hossain. "Bio-Chemical Management of Grey Blight of Mustard Through Selected Botanicals and Chemicals". SAARC Journal of Agriculture 19, n.º 2 (2 de marzo de 2022): 219–32. http://dx.doi.org/10.3329/sja.v19i2.57683.

Texto completo

Resumen

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)

Los estilos APA, Harvard, Vancouver, ISO, etc.

5

Zhang, Yuqian, Feiyan Wang, Lijie Wang, Lingyun Zhang, Richard V. Espley, Kui Lin-Wang y Fanrong Cao. "The Response of Growth and Transcriptome Profiles of Tea Grey Blight Disease Pathogen Pestalotiopsis theae to the Variation of Exogenous L-Theanine". International Journal of Molecular Sciences 25, n.º 6 (20 de marzo de 2024): 3493. http://dx.doi.org/10.3390/ijms25063493.

Texto completo

Resumen

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.

Los estilos APA, Harvard, Vancouver, ISO, etc.

6

Hairah, Ummul, Anindita Septiarini, Novianti Puspitasari, Andi Tejawati, Hamdani Hamdani y Surya Eka Priyatna. "Classification of tea leaf disease using convolutional neural network approach". International Journal of Electrical and Computer Engineering (IJECE) 14, n.º 3 (1 de junio de 2024): 3287. http://dx.doi.org/10.11591/ijece.v14i3.pp3287-3294.

Texto completo

Resumen

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.

Los estilos APA, Harvard, Vancouver, ISO, etc.

7

Chen, Y. J., L. Zeng, Q. Meng y H. R. Tong. "Occurrence of Pestalotiopsis lushanensis Causing Grey Blight Disease on Camellia sinensis in China". Plant Disease 102, n.º 12 (diciembre de 2018): 2654. http://dx.doi.org/10.1094/pdis-04-18-0640-pdn.

Texto completo

Los estilos APA, Harvard, Vancouver, ISO, etc.

8

Ahmad, I., MNA Mamun, MS Islam, R. Ara, MAA Mamdud y AKMR Hoque. "Effect of different pruning operations on the incidence and severity of various diseases of tea plant". Journal of Bio-Science 24 (18 de julio de 2018): 1–9. http://dx.doi.org/10.3329/jbs.v24i0.37482.

Texto completo

Resumen

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

Los estilos APA, Harvard, Vancouver, ISO, etc.

9

Chen, Y. J., L. Zeng, N. Shu, H. Wang y H. R. Tong. "First Report of Pestalotiopsis camelliae causing Grey Blight Disease on Camellia sinensis in China". Plant Disease 101, n.º 6 (junio de 2017): 1034. http://dx.doi.org/10.1094/pdis-01-17-0033-pdn.

Texto completo

Los estilos APA, Harvard, Vancouver, ISO, etc.

10

Pallavi, R. Vidhya, P. Nepolean, A. Balamurugan, R. Jayanthi, T. Beulah y R. Premkumar. "In vitro studies of biocontrol agents and fungicides tolerance against grey blight disease in tea". Asian Pacific Journal of Tropical Biomedicine 2, n.º 1 (enero de 2012): S435—S438. http://dx.doi.org/10.1016/s2221-1691(12)60202-0.

Texto completo

Los estilos APA, Harvard, Vancouver, ISO, etc.

11

Sanjay, R., P. Ponmurugan y U. I. Baby. "Evaluation of fungicides and biocontrol agents against grey blight disease of tea in the field". Crop Protection 27, n.º 3-5 (marzo de 2008): 689–94. http://dx.doi.org/10.1016/j.cropro.2007.09.014.

Texto completo

Los estilos APA, Harvard, Vancouver, ISO, etc.

12

Shahriar, Saleh Ahmed, Abdul Omar Nur-Shakirah y Masratul Hawa Mohd. "Neopestalotiopsis clavispora and Pseudopestalotiopsis camelliae-sinensis causing grey blight disease of tea (Camellia sinensis) in Malaysia". European Journal of Plant Pathology 162, n.º 3 (29 de noviembre de 2021): 709–24. http://dx.doi.org/10.1007/s10658-021-02433-2.

Texto completo

Los estilos APA, Harvard, Vancouver, ISO, etc.

13

M. ABDULLAH, MAIZAH, NOORSHAZILA MOHD ALWI y AZWANI SAHIBU. "EVALUATION OF FOLIAR DISEASE INCIDENCE AND SEVERITY OF MANGROVES IN UNIVERSITI MALAYSIA TERENGGANU". Universiti Malaysia Terengganu Journal of Undergraduate Research 4, n.º 1 (25 de julio de 2022): 63–74. http://dx.doi.org/10.46754/umtjur.v4i1.261.

Texto completo

Resumen

Mangroves are an important ecosystem because of their ecological roles and services, particularly in nutrient cycling and carbon sequestration. However, habitats have declined over the year, mostly due to anthropogenic and natural threats. Mangrove plant diseases caused by pathogenic fungal invasion are poorly described. The status of diseased mangroves remained unknown, primarily in Malaysia. The current study evaluates the disease incidence and severity of mangrove trees in the Universiti Malaysia Terengganu (UMT) campus. This study aimed to determine the dominant type of foliar disease in the UMT campus and identify the most affected mangrove species using Disease Incidence and Disease Severity approach. 30 leaves from each of five mangrove species; Lumnitzera racemosa, Rhizophora apiculata, Hibiscus tiliaceus, Avicennia alba and Sonneratia caseolaris were collected, observed and analysed for the Disease Incidence and Disease Severity. A total of six types of foliar diseases were observed, with leaf blight as the dominant, followed by brown leaf spot, insect graze, grey leaf spot, black leaf spot and anthracnose. Mangrove trees at Jalan Biawak have the highest percentage value of Disease Incidence and Disease Severity compared to mangroves at Pusat Islam UMT. Fungal invasion rate variation could be caused by factors such as temperature, humidity and mangrove species’ resilience toward fungal invasion. Therefore, further study needs to be done to understand this issue better.

Los estilos APA, Harvard, Vancouver, ISO, etc.

14

Sbaihat, Layth, Keiko Takeyama, Takeharu Koga, Daigo Takemoto y Kazuhito Kawakita. "Induced Resistance inSolanum lycopersicumby Algal Elicitor Extracted fromSargassum fusiforme". Scientific World Journal 2015 (2015): 1–9. http://dx.doi.org/10.1155/2015/870520.

Texto completo

Resumen

Tomato (Solanum lycopersicum) production relies heavily on the use of chemical pesticides, which is undesired by health- and environment-concerned consumers. Environment-friendly methods of controlling tomato diseases include agroecological practices, organic fungicides, and biological control. Plants’ resistance against pathogens is induced by applying agents called elicitors to the plants and would lead to disease prevention or reduced severity. We investigated the ability of a novel elicitor extracted from the brown sea algae (Sargassum fusiforme) to elicit induced resistance in tomato. The studied elicitor induced hypersensitive cell death andO2-production in tomato tissues. It significantly reduced severities of late blight, grey mold, and powdery mildew of tomato. Taken together, our novel elicitor has not shown any direct antifungal activity against the studied pathogens, concluding that it is an elicitor of induced resistance.

Los estilos APA, Harvard, Vancouver, ISO, etc.

15

SAHIBU, A., SITI NORDAHLIAWATE, M. S. S y M. M. ABDULLAH. "PRESENCE OF FOLIAR DISEASES CAUSED BY FUNGI IN MANGROVES ON THE EAST COAST OF PENINSULAR MALAYSIA". Malaysian Applied Biology 49, n.º 4 (25 de diciembre de 2020): 181–86. http://dx.doi.org/10.55230/mabjournal.v49i4.1610.

Texto completo

Resumen

Mangrove health is very important for the ecosystem to survive the challenges and threats due to climate change and anthropogenic pressures. However, unhealthy mangroves due to pathogenic fungi causing diseases may demote the survival rate of younger plants to grow and information on the status of foliar disease incidence is limited. This study aimed 1) to observe the foliar disease symptoms that occurred on Rhizophora apiculata and Avicennia marina and 2) to identify the fungi isolated from the symptomatic leaves. Samples were collected from the mangrove area located in Universiti Malaysia Terengganu (UMT) campus, along the South China Sea. All isolates were identified based on their morphological characteristics. A total of five foliar disease symptoms were observed namely black leaf spot, grey leaf spot, leaf rot, sunken leaf blight, and anthracnose. Rhizophora apiculata has a greater number of leaf spots than A. marina. Four genera of fungi; Pestalotiopsis sp., Curvularia sp., Colletotrichum sp. and Rhizopus sp. were successfully isolated from symptomatic leaves where the most dominant was Pestalotiopsis sp. to both mangrove species. This finding highlights the need to obtain the status of foliar diseases and their impact on the resilience of mangroves in Malaysia.

Los estilos APA, Harvard, Vancouver, ISO, etc.

16

Shahriar, S. A., A. O. Nur-Shakirah y M. H. Mohd. "Correction to: Neopestalotiopsis clavispora and Pseudopestalotiopsis camelliae-sinensis causing grey blight disease of tea (Camellia sinensis) in Malaysia". European Journal of Plant Pathology 162, n.º 3 (15 de diciembre de 2021): 757. http://dx.doi.org/10.1007/s10658-021-02437-y.

Texto completo

Los estilos APA, Harvard, Vancouver, ISO, etc.

17

Rehman, Fazal Ur, Muhammad Adnan, Maria Kalsoom, Nageen Naz, Muhammad Ghayoor Husnain, Haroon Ilahi, Muhammad Asif Ilyas, Gulfam Yousaf, Rohoma Tahir y Usama Ahmad. "Seed-Borne Fungal Diseases of Maize (Zea mays L.): A Review". Agrinula : Jurnal Agroteknologi dan Perkebunan 4, n.º 1 (12 de febrero de 2021): 43–60. http://dx.doi.org/10.36490/agri.v4i1.123.

Texto completo

Resumen

Introduction: Maize (Zea mays) is one of the most important cereal crops. It is ranked as 3rd after wheat and rice. Due to its wide adaptability, diversified uses, and low production costs, it has great potential as a cereal crop. In the case of yield losses, various factors are involved. The fungal diseases of maize play a significant role in the reduction of both quantity as well as the quality of maize. Review Results: At the seedling stage, maize suffers from numerous diseases and many of them are seed-borne diseases. Anthracnose stalk rot (Colletotrichum graminicola), Charcoal rot of maize (Macrophomina phaseolina), Crazy top downy mildew disease (Sclerophthora macrospora), Corn grey leaf spot disease (Cercospora zeae-maydis), Aspergillus ear and kernel rot (Aspergillus flavus), Corn smut (Ustilago maydis), Southern corn leaf blight disease (Bipolaris maydis) etc. are important among these diseases.Chemical control of seed-borne pathogens of maize is rather difficult to achieve as a reasonably good. Due to the hazardous environmental effects of chemicals, the Integrated Management of the seed-borne fungal pathogens of corn is mostly preferred. The distribution, disease cycle, symptoms of the damage, effects of environmental factors, economical importance of disease, and integrated disease management options of major seed-borne fungal pathogens of maize have been reviewed in this review article from various currently available sources.

Los estilos APA, Harvard, Vancouver, ISO, etc.

18

Bawomon Neya, Fidele, Abasse Ouedraogo, Elisabeth Aboubie Zongo, Elise Sanon, Gilles Ibie Thio y Kadidia Koita. "EXPERIMENTATION OF AN APPLICATION OF EARLY DIAGNOSIS AND INVENTORY OF SOYBEAN DISEASES (GLYCINE MAX (L.) MERR.) IN BURKINA FASO". International Journal of Advanced Research 11, n.º 09 (30 de septiembre de 2023): 614–20. http://dx.doi.org/10.21474/ijar01/17567.

Texto completo

Resumen

Glycine max (L.) Merr also known as soya or soybean plays an important role in legume production in Burkina Faso. Every year, the country produces an average of 30,000 tonnes of soybean. It is grown for its oilseeds, which are rich in protein, fat, minerals and vitamins, making it an important food and feed crop. In addition, soya production is profitable for growers because it provides a real source of income through marketing operations. The lack of fertile land, adequate rainfall and phytosanitary protection in soya cultivation are not conducive for efficient production. Ignorance and lack of knowledge of the diseases encountered in soya production make it even more difficult to protect the crop, which further limits production.In order to improve knowledge of soybean diseases in Burkina Faso, an inventory of diseases associated with this crop was carried out using a plant pathology diagnostic application. In this study, the Plantix-Crop Doctor application, based on artificial intelligence with deep learning, was used in an Alpha Lattice experimental device. A disease identification form from the Quebec Agriculture and Agri-Food Research Centre was used as a reference. Among the diseases identified were Septoria leaf spot, grey leaf spot, anthracnose, bacterial blight, soybean blight, sudden death syndrome, downy mildew, powdery mildew and soybean rust. This list provides a database of soybean diseases that must be controlled by methods that consider environmental protection. The Plantix - your crop doctor application can be relied on to diagnose soybean diseases so that they can be treated at an early stage.

Los estilos APA, Harvard, Vancouver, ISO, etc.

19

Bora, Popy, Lohit Chandra Bora, R. P. Bhuyan, Abeer Hashem y Elsayed Fathi Abd-Allah. "Bioagent consortia assisted suppression in grey blight disease with enhanced leaf nutrients and biochemical properties of tea (Camellia sinensis)". Biological Control 170 (julio de 2022): 104907. http://dx.doi.org/10.1016/j.biocontrol.2022.104907.

Texto completo

Los estilos APA, Harvard, Vancouver, ISO, etc.

20

Ray, Manjit Kumar. "Control of Fungal Pathogen Pestalotiopsis Disseminata Causing Grey Blight Disease in Som (Persea Bombycina Kost.): An In Vitro Study". International Journal of Pure & Applied Bioscience 4, n.º 6 (30 de diciembre de 2016): 180–85. http://dx.doi.org/10.18782/2320-7051.2412.

Texto completo

Los estilos APA, Harvard, Vancouver, ISO, etc.

21

Pamungkas, Wisnu Gilang, Machammad Iqbal Putra Wardhana, Zamah Sari y Yufiz Azhar. "Leaf Image Identification: CNN with EfficientNet-B0 and ResNet-50 Used to Classified Corn Disease". Jurnal RESTI (Rekayasa Sistem dan Teknologi Informasi) 7, n.º 2 (26 de marzo de 2023): 326–33. http://dx.doi.org/10.29207/resti.v7i2.4736.

Texto completo

Resumen

Corn is the second largest commodity in Indonesia after rice. In Indonesia, East Java is the largest corn producer. The first symptom of the disease in corn plants is marked by small brownish oval spots which are usually caused by the fungus Helminthoporium maydis, if left unchecked, farmers can suffer losses due to crop failure. Therefore it is important to provide treatment for diseases in corn plants as early as possible so that diseases in corn plants do not spread to other plants. In this study, the dataset used was taken from the kaggle website entitled Corn or Maize Leaf Disease Dataset. This dataset has 4 classifications: Blight, Common Rust, Grey leaf spot, and Healthy. This study uses the Convolutional Neural Network method with 2 different models, namely the EfficientNet-B0 and ResNet-50 models. The architectures used are the dense layer, the dropout layer, and the GlobalAveragePooling layer with a dataset sharing ratio of 70% which is training data and 30% is validation data. After testing the two proposed scenarios, the accuracy results obtained in the test model scenario 1, namely EfficientNet- B0 is 94% and for the second test model scenario, namely ResNet-50, the accuracy is 93%.

Los estilos APA, Harvard, Vancouver, ISO, etc.

22

Ashritha, K., K. Sandhya, Y. Uday Kiran y V. N. L. N. Murthy. "Plant-Leaf Disease Prediction Using Deep Learning". International Journal for Research in Applied Science and Engineering Technology 11, n.º 3 (31 de marzo de 2023): 121–28. http://dx.doi.org/10.22214/ijraset.2023.49338.

Texto completo

Resumen

Abstract: Brown spot, Mosaic, Grey spot, and Rust all significantly reduce apple yield. Rust is a sign of Foliar illness in this instance. The primary factor influencing apple output is the occurrence of apple leaf diseases, which results in significant yearly economic losses. Therefore, it is very important to research apple leaf disease identification. Plants are frequently attacked by pests, bacterial diseases, and other microorganisms. Inspection of the leaves, stem, or fruit usually identifies the attack's signs. Powdery Mildew and Leaf Blight are two common plant diseases that can cause severe harm if not treated quickly. In the realm of agriculture, image processing is frequently utilized for classification, detection, grading, and quality control. Finding and identifying plant diseases is crucial, especially when trying to produce fruit of the highest caliber. The real-time identification of apple leaf diseases is addressed in this research using a deep learning strategy that is based on enhanced convolutional neural networks (CNNs). This study uses data augmentation and image annotation tools to create the foliar disease dataset, which is made up of complex images captured in the field and laboratories. Overall, we can identify the illness present in plants on a massive scale by utilizing machine learning to train the vast data sets that are publically available. The project explains how to identify plant leaf diseases, how they affect plant yield, and which pesticides should be used to treat them. in agriculture. To monitor huge plant fields and automatically identify disease symptoms as soon as they develop on plant leaves, research on automatic plant disease is crucial. In this essay, we'll demonstrate how to identify plant illnesses by obtaining photos of their leaves

Los estilos APA, Harvard, Vancouver, ISO, etc.

23

K. K. Nivethithaa, S. Vijayalakshmi. "Whale Optimized Deep Model for Paddy and Maize Leaf Disease Detection". Tuijin Jishu/Journal of Propulsion Technology 44, n.º 4 (16 de octubre de 2023): 6786–801. http://dx.doi.org/10.52783/tjjpt.v44.i4.2313.

Texto completo

Resumen

Plant disease management is an essential process to minimize loss in the field of agriculture. Plant leaf disease detection(PLDD) technology helps the formers to reduce the loss of quality yield production. This study focuses on detecting paddy and maize plant leaf disease-detecting methods. It contributes to a PLDD method to improve detection accuracy and overall performance. The PLDD method introduced a whales-optimized artificial neural network (WOANN) method for classifying the four Maize and four rice leaf disease-related classes. The WOANN uses the whale optimizer's food-searching functionalities to improve the performance and detection accuracy of the dense net model. This WOANN classifies the maize leaf light, maize grey leaf spot, maize common rust, rice bacterial leaf blight, rice bacterial leaf steak, rice brown spot, and healthy leaves of both Maize and paddy. It uses the Hilbert-Schmidt independent criterion lasso correlation algorithm to support the WOANN classifier in selecting the significant features. The performance analysis shows that the WOANN-based approach achieves a maximum of 99.35% detection accuracy for maize leaf disease and 99.13% for paddy leaf disease. Its efficiency analysis shows that the WOANN-based approaches achieve a maximum accuracy rate than comparison approaches.

Los estilos APA, Harvard, Vancouver, ISO, etc.

24

Chohan, Sobia, Rashida Perveen, Muhammad Abid, Atif H. Naqvi y Safina Naz. "MANAGEMENT OF SEED BORNE FUNGAL DISEASES OF TOMATO: A REVIEW". Pakistan Journal of Phytopathology 29, n.º 1 (12 de julio de 2017): 193. http://dx.doi.org/10.33866/phytopathol.029.01.0274.

Texto completo

Resumen

Plant diseases caused by different kinds of microorganisms either carried through air, water or present in soil, seeds or propagative planting materials have adverse impact on agriculture production and economy worldwide. Apart from other crops vegetables are also subjected to several seed borne fungal, bacterial and viral pathogens, which cause substantial yield loss upto 10 percent in Pakistan. This article gives vast information regarding significance and prevalence of various kinds of seed borne mycoflora (Alternaria solani, Fusarium oxysporum, F. solani, Botrytis cineria, A. alternata, Chaetomium globosum, Curvularia lunata, Aspergillus niger, Drechslera specifer and Rhizoctonia solani) particularly associated with seeds of tomato. These mycoflora are causative agents of devastating tomato diseases like early blight, fusarium wilt and foot rots, grey mold, root and fruit rots. A range of conventional and modern techniques employed for seed borne fungal detection and different control strategies including chemical and biological methods opted by researchers have been reviewed in present paper. A variety of factors like availability of susceptible plants, favorable environmental conditions and overhead irrigation are serious constraints for plant disease development. Under these conditions, monitoring of plant health and detection of diseases particularly using seed detection assays to screen infested seed lots before planting provide effective disease management strategy.

Los estilos APA, Harvard, Vancouver, ISO, etc.

25

Rajeena P. P., Fathimathul, Aswathy S. U., Mohamed A. Moustafa y Mona A. S. Ali. "Detecting Plant Disease in Corn Leaf Using EfficientNet Architecture—An Analytical Approach". Electronics 12, n.º 8 (20 de abril de 2023): 1938. http://dx.doi.org/10.3390/electronics12081938.

Texto completo

Resumen

The various corn diseases that affect agriculture go unnoticed by farmers. Each day, more crops fail due to diseases as there is no effective treatment or a way to identify the illness. Common rust, blight, and the northern leaf grey spot are the most prevalent corn diseases. The presence of a disease cannot be accurately detected by simply looking at the plant. This will lead to improper pesticide use, which harms people by bringing on chronic diseases. Therefore, maintaining food security depends on accurate and automatic disease detection. It might be possible to save time and stop crop degradation before it takes place by utilising digital technologies. Hence, applying modern digital technologies to identify the disease in the damaged corn fields automatically will be more advantageous to the farmers. Many academics have recently become interested in deep learning, which has aided in creating an exact and autonomous picture classification scheme. The use of deep learning techniques and their adjustments for detecting corn illnesses can greatly assist contemporary agriculture. To find plant leaf diseases, we employ image acquisition, preprocessing, and classification processes. Preprocessing includes procedures such as reading images, resizing images, and data augmentation. The suggested project is based on EfficientNet and improves the precision of the database of corn leaf diseases by tweaking the variables. Tests are run using DenseNet and Resnet on the test dataset to confirm the precision and robustness of this approach. The recognition accuracy of 98.85% that can be achieved using this method, according to experimental results, is significantly higher than those of other cutting-edge techniques.

Los estilos APA, Harvard, Vancouver, ISO, etc.

26

Jayaram, Miryabbelli, Gudikandhula Kalpana, Subba Reddy Borra y Battu Durga Bhavani. "A brief study on rice diseases recognition and image classification: fusion deep belief network and S-particle swarm optimization algorithm". International Journal of Electrical and Computer Engineering (IJECE) 13, n.º 6 (1 de diciembre de 2023): 6302. http://dx.doi.org/10.11591/ijece.v13i6.pp6302-6311.

Texto completo

Resumen

In the regions of southern Andhra Pradesh, rice brown spot, rice blast, and rice sheath blight have emerged as the most prevalent diseases. The goal of this research is to increase the precision and effectiveness of disease diagnosis by proposing a framework for the automated recognition and classification of rice diseases. Therefore, this work proposes a hybrid approach with multiple stages. Initially, the region of interest (ROI) is extracted from the dataset and test images. Then, the multiple features are extracted, such as color-moment-based features, grey-level cooccurrence matrix (GLCM)-based texture, and shape features. Then, the S-particle swarm optimization (SPSO) model selects the best features from the extracted features. Moreover, the deep belief network (DBN) model trained by SPSO is based on optimal features, which classify the different types of rice diseases. The SPSO algorithm also optimized the losses generated in the DBN model. The suggested model achieves a hit rate of 94.85% and an accuracy of 97.48% with the 10-fold cross-validation approach. The traditional machine learning (ML) model is significantly less accurate than the area under the receiver operating characteristic curve (AUC), which has an accuracy of 97.48%.

Los estilos APA, Harvard, Vancouver, ISO, etc.

27

Nayak, Anusha M., Pooja Rajendra Dhange, Farooqkhan y Muhammad Suhaib Ismayil M. "Fungal Bioagents and Botanicals Efficacy against Alternaria alternata Responsable for Leaf Blight Disease of Stevia rebaudiana". International Journal of Plant & Soil Science 35, n.º 22 (21 de noviembre de 2023): 254–60. http://dx.doi.org/10.9734/ijpss/2023/v35i224131.

Texto completo

Resumen

Stevia rebaudiana, a herbaceous perennial prized for its natural sweetness, has gained global acclaim and found in various parts of India including Karnataka. An exploration into leaf spot disease (caused by Alternaria alternata (FR.) Keissler) in Stevia was conducted under the conditions of southern Karnataka to identify effective management strategies. The symptoms initially manifested as petite circular spots of a light brown colour, subsequently evolving into irregular shapes ranging from dark brown to grey. Some spots maintained their circular form, exhibiting concentric rings or zones. Severely affected leaves exhibited the merging of numerous spots, forming expansive necrotic areas. On older leaves, concentric spots were predominantly found at the tips. The diameter of the leaf spots ranged from 2 to 18 mm. The conidial dimensions varied from 10 to 40 × 6-12 mm, displaying a mid to dark brown or olive-brown color. They were short-beaked, arranged in long chains, and had an oval and bean-shaped structure with 3–5 transverse septa. Considering the adverse effects of chemical fungicides, the exploration for a safer alternative to control the pathogen became a preferable option. This led to experiments involving the use of bioagents for pathogen control. The six known bioagents were evaluated by dual culture, pathogen at periphery and pathogen at the center technique to monitor antagonistic effect. The results revealed that out of all the six bioagents used, two bioagents namely Trichoderma viride (74.77%, 69.04% and 79.45%) and T. harzianum (71.25%, 59.96% and 74.78%) showed maximum growth inhibition in dual culture, pathogen at periphery and pathogen at the center methods, respectively. among the botanicals used neem (36.63%) and ginger (36.42%) found to be effective in inhibiting mycelial growth. Unraveled the strong antagonistic effect to inhibit the mycelia growth of the pathogen significantly.

Los estilos APA, Harvard, Vancouver, ISO, etc.

28

Das, Ranjana, M. Chutia, K. Das y D. K. Jha. "Factors affecting sporulation of Pestalotiopsis disseminata causing grey blight disease of Persea bombycina Kost., the primary food plant of muga silkworm". Crop Protection 29, n.º 9 (septiembre de 2010): 963–68. http://dx.doi.org/10.1016/j.cropro.2010.05.012.

Texto completo

Los estilos APA, Harvard, Vancouver, ISO, etc.

29

Hassan, Jawad, Kaleem Razzaq Malik, Ghulam Irtaza, Ali Ghulam y Ashfaq Ahmad. "Disease Identification using Deep Learning in Agriculture: A Case Study of Cotton Plant". VFAST Transactions on Software Engineering 10, n.º 4 (30 de diciembre de 2022): 104–15. http://dx.doi.org/10.21015/vtse.v10i4.1224.

Texto completo

Resumen

Among all the agrician products, cotton is known as “Ready Cash Crop” and it plays the significant role in the stability of the economy of a country. Therefore, it is extremely important to monitor the cotton crop from the numerous diseases. Unfortunately, sometimes human eyes not be able to analyze these diseases at earlier stage and that will affect not only the quality and also the quantity of the cotton crops. To address this early monitoring issue we proposed an interactive framework based on target feature extraction and deep learning model for cotton leaf screening to deal with these well-known dangerous diseases; Grey Mildew, Cercospora, Bacterial Blight and Alternaria. In this study we chosen our own collected dataset that contains 522 images of cotton leaves that were collected from the field (Cotton agricultural areas near the Multan city). The performance evaluation matric indicates the algorithm secure; 85.42% overall accuracy, 0.8542 precision, 0.8542 recall, 0.854 F1 score and 0.817 kappa coefficient indicates the generalization and acceptability of the model. The proposed framework not only assists the agronomist but also the farmer because of early identification of diseases from cotton crop and to avoid from the massive loss. It make better decisions for cotton crop management and contributes in the sustainability of the economy.

Los estilos APA, Harvard, Vancouver, ISO, etc.

30

Ivanová, Helena. "Morphological features of Camarosporium pini – the fungus associated to health state degradation in Austrian and Ponderosa pine". Folia Oecologica 44, n.º 1 (27 de junio de 2017): 54–57. http://dx.doi.org/10.1515/foecol-2017-0007.

Texto completo

Resumen

AbstractThe subject of this study is escalated occurrence of the pathogenic fungus Camarosporium pini in the needle tissue of symptomatic trees P. nigra and P. ponderosa var. jeffreyi growing in urbanized settings and parks. C. pini induces severe infections and initiates a blight and premature loss of second-year foliage in pine trees. The fungus was identified microscopically and on base of morphological keys. The affected needles displayed a distinct bluish-grey necrotic band in the centre. On the surface of infected needles, there were formed pycnidia producing brown, oval conidia with three transversal and one or two vertical walls. Disease symptoms, some important characteristics in pure culture, and distinctive morphological features of C. pini associated to the health state degradation in Austrian and Ponderosa pine are described and compared. Cumulative effects of these stressful biotic and various abiotic factors may explain the current situation concerning the decline in the P. nigra and P. ponderosa var. jeffreyi in Slovakia.

Los estilos APA, Harvard, Vancouver, ISO, etc.

31

Et. al., S. Vanitha,. "Decision Support Model for Prioritization of Cotton Plant Diseases using Integrated FAHP-TOPSIS approach". Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, n.º 10 (28 de abril de 2021): 7587–96. http://dx.doi.org/10.17762/turcomat.v12i10.5668.

Texto completo

Resumen

Cotton, the essential cash crop of India plays a predominant part in the agricultural and industrial enlargement of the world. The evolution of cotton plant begins with the germination of seed and its growth depends on the accessibility of temperature, soil moisture and oxygen. The desirable characteristics combined in cotton make no other fiber to duplicates its value. There are beyond 75 critical diseases leads to the substantial destruction and economic losses in cotton crop. Premature analysis of the cotton plant diminishes the disease, results in the significant enhancement in the superiority of the product. Massive yield of cotton crop is vanished each year due to fast incursion by insects and pests. Verticilium wilt, grey mildew, leaf spot and leaf blight are some of major cotton disease in cotton plant which extremely affects the productivity. This research discusses the multi criteria decision making evaluation tool to identify the major disease causing factors of cotton crop. Fuzzy AHP, a Multi Criteria Decision making method (MCDM) is applied to impact the disease causing risk factors by determining the weights of the criteria. Moreover, a Fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), a ranking MCDM methodology has been applied to rank the alternatives. The outcomes and methods described in this research based on the derived criteria and sub criteria of risk factors will be a noble orientation in producing more perfect, active and efficient decision support tool for the farmers to identify and diagnose the risk factors during the cultivation of the cotton crop

Los estilos APA, Harvard, Vancouver, ISO, etc.

32

Batchelor, William D., L. M. Suresh, Xiaoxing Zhen, Yoseph Beyene, Mwaura Wilson, Gideon Kruseman y Boddupalli Prasanna. "Simulation of Maize Lethal Necrosis (MLN) Damage Using the CERES-Maize Model". Agronomy 10, n.º 5 (15 de mayo de 2020): 710. http://dx.doi.org/10.3390/agronomy10050710.

Texto completo

Resumen

Maize lethal necrosis (MLN), maize streak virus (MSV), grey leaf spot (GLS) and turcicum leaf blight (TLB) are among the major diseases affecting maize grain yields in sub-Saharan Africa. Crop models allow researchers to estimate the impact of pest damage on yield under different management and environments. The CERES-Maize model distributed with DSSAT v4.7 has the capability to simulate the impact of major diseases on maize crop growth and yield. The purpose of this study was to develop and test a method to simulate the impact of MLN on maize growth and yield. A field experiment consisting of 17 maize hybrids with different levels of MLN tolerance was planted under MLN virus-inoculated and non-inoculated conditions in 2016 and 2018 at the MLN Screening Facility in Naivasha, Kenya. Time series disease progress scores were recorded and translated into daily damage, including leaf necrosis and death, as inputs in the crop model. The model genetic coefficients were calibrated for each hybrid using the 2016 non-inoculated treatment and evaluated using the 2016 and 2018 inoculated treatments. Overall, the model performed well in simulating the impact of MLN damage on maize grain yield. The model gave an R2 of 0.97 for simulated vs. observed yield for the calibration dataset and an R2 of 0.92 for the evaluation dataset. The simulation techniques developed in this study can be potentially used for other major diseases of maize. The key to simulating other diseases is to develop the appropriate relationship between disease severity scores, percent leaf chlorosis and dead leaf area.

Los estilos APA, Harvard, Vancouver, ISO, etc.

33

Palanisamy, Senthilkumar y Abul Kalam Azad Mandal. "Susceptibility Against Grey Blight Disease-Causing Fungus Pestalotiopsis sp. in Tea (Camellia sinensis (L.) O. Kuntze) Cultivars Is Influenced by Anti-oxidative Enzymes". Applied Biochemistry and Biotechnology 172, n.º 1 (26 de septiembre de 2013): 216–23. http://dx.doi.org/10.1007/s12010-013-0529-z.

Texto completo

Los estilos APA, Harvard, Vancouver, ISO, etc.

34

Tuset, J. J., C. Hinarejos y J. L. Mira. "First Report of Leaf Blight on Sweet Persimmon Tree by Pestalotiopsis theae in Spain". Plant Disease 83, n.º 11 (noviembre de 1999): 1070. http://dx.doi.org/10.1094/pdis.1999.83.11.1070c.

Texto completo

Resumen

During July 1998, a leaf blight caused by Pestalotiopsis theae (Saw.) Stey. was observed at an incidence of 18 to 20% in sweet persimmon (Diospyros kaki L.fil.) orchards in Huelva Province (southwestern Spain). Symptoms appeared on leaves as large grayish brown circular ringspots. Usually, they were solitary, but occasionally, two to three spots occurred on an affected leaf. In severe cases, lesions developed on more than one-third of the leaf, resulting in defoliation. Small black acervular conidiomata were visible in the surface of spots. These conidiomata produced fusiform conidia that were straight or rarely curved, four five-celled euseptate, including three olivaceous or dark brown median cells, and hyaline apical and basal cells with appendages that were slightly constricted at septa. Conidiomata were up to 240 μm in diameter; conidiogenous cells were 6 to 13 × 1.2 to 2.8 μm; conidia were 24.7 × 7.8 μm; three median cells were 16.7 μm long; two to three apical appendages (rarely four) were 28.3 μm long; and straight basal appendage was 5.7 μm. P. theae was consistently isolated on potato dextrose agar from diseased leaves and conidiomata. To confirm pathogenicity, both mycelial plugs and a conidial suspension (1.5 × 106 conidia per ml) of the fungus were used as inocula. Young completely developed leaves from persimmon tree cvs. Sharon and Hanafuyu were inoculated in the laboratory and maintained in a moist chamber for 5 days. Lesions resembling symptoms that occurred in the field were observed on leaves after 5 days. Symptoms were not observed on control leaves inoculated with agar media or sprayed with water. The fungus reisolated from diseased leaves was identical to the original isolates. Based on the morphological characteristics of conidiomata and conidia as well as pathogenicity, the fungus was identified as P. theae (1). This is the first report of this fungus as a pathogen of D. kaki in Europe. Possibly the introduction of P. theae to Spain has been through young imported persimmon plants. Unusual climatic conditions (heavy rainfalls during 1997 in southwestern Spain) have been favorable for disease development. The hot and dry conditions that usually occur during flowering, growing, and maturation of persimmon fruits normally prevent dissemination of inoculum and infection of leaves. For these reasons, the wet areas of southwestern Spain could be more favorable for “grey blight” of persimmon trees. Reference: (1) T.-H. Chang et al. Korean J. Plant Pathol. 12:377, 1996.

Los estilos APA, Harvard, Vancouver, ISO, etc.

35

Wu, Zhi Hua. "Distribution of Culturable Myxobacteria in Central Inner Mongolia and their Activity against Phytophthora infestans". International Journal of Agriculture and Biology 25, n.º 06 (1 de junio de 2021): 1292–302. http://dx.doi.org/10.17957/ijab/15.1791.

Texto completo

Resumen

Myxobacteria can produce rich and varied biological active substances against bacteria, fungi and viruses, which have great development and research value in medicine and agriculture. In this study, the diversity of culturable myxobacteria in central Inner Mongolia in China was studied and the effects of soil utilization mode, soil type and environmental parameters on the distribution of myxobacteria in this region were analyzed. Furthermore, the activities of myxobacteria against potato late blight pathogen were tested. The results showed that Myxococcus, Corallococcus, Pyxidicoccus, Cystobacter, Archangium and Mellittangium were the dominant genera of myxobacteria in this region. Soil utilization mode and soil types have obvious influence on the distribution of myxobacteria. The populations of myxobacteria were abundant in grassland and cultivated land samples, but few in woodland and unused land samples. The diversity of myxobacteria in the soil samples from fuvo-aquic soils, grey-cinnamon soils, castanozems, and bog soils was relatively rich, while the richness of myxobacteria in aeolian soils, solonetzs, skeletol soils and castano-cinnamon soils was poor. There was no significant correlation between myxobacteria distribution and soil environmental parameters (including the water content, pH value, content of organic matter, content of available phosphorus, content of hydrolytic nitrogen and content of available potassium). Most of the myxobacterial strains isolated in this area (83%) showed the activity against P. infestans, among which the proportion of the disease-resistant strains belonging to Myxococcus and Corallococcus was high, the proportion of the strains belonging to Cystobacter and Mellittangium in the medium, and the proportion of the strains belonging to Pyxidicoccus and Archangium low. The completion of this work will enrich the myxobacteria resource bank in Inner Mongolia and lay a foundation for the further study on myxobacteria and the development of biological pesticide against potato late blight. © 2021 Friends Science Publishers

Los estilos APA, Harvard, Vancouver, ISO, etc.

36

Kasson, M. T., J. R. Pollok, E. B. Benhase y J. G. Jelesko. "First Report of Seedling Blight of Eastern Poison Ivy (Toxicodendron radicans) by Colletotrichum fioriniae in Virginia". Plant Disease 98, n.º 7 (julio de 2014): 995. http://dx.doi.org/10.1094/pdis-09-13-0946-pdn.

Texto completo

Resumen

Colletotrichum fioriniae is a member of the large cosmopolitan C. acutatum species complex (2). Known agricultural hosts of C. acutatum include apple, European blueberry, grape, olive, papaya, and strawberry (2). In contrast, the life history of C. fioriniae ranges from an epizootic of certain scale insect populations to an endophyte of plants (3,4). The present study extends the phytopathology of C. fioriniae to include poison ivy seedlings. Poison ivy (Toxicodendron radicans) drupes were collected from solitary lianas in Roanoke and Montgomery counties, Virginia. These drupes were subjected to experiments aimed at producing sterile seedlings (1); however, there was extensive blighting and wilting in the germinated seedlings. Associated with the drupes and seedlings was a fungus with white to pale olivaceous grey mycelium with orange blister-like conidiomata and sclerotial masses enclosing the drupe mesocarp as well as conidiomata emerging from blighted, necrotic leaves. Condiomata were plated onto acidified potato dextrose agar (APDA) and oatmeal agar (OA). This consistently yielded colonies identical to those described from diseased tissues and were putatively identified as C. acutatum based on the presence of acervuli containing hyaline, smooth-walled, aseptate conidia with acute ends, the absence of setae, and formation of red pigments in culture (2). Conidial dimensions of four isolates most closely aligned with reported measurements for C. fioriniae (4): mean length ± SD × width ± SD = 15.1 ± 1.7 × 4.9 ± 0.3 μm, L/W ratio = 3.04 on OA. Fungal DNA was isolated and used as template in PCR reactions using oligonucleotide primer pairs corresponding to the internal transcribed spacer (ITS) region, and a portion of the glyceraldehyde-3-phosphate dehydrogenase (GAPDH) genes. The resulting PCR fragments were sequenced and used as queries in BLASTN searches of the GenBank NR database. All of the amplified ITS DNA sequences (497 bp KF944356 and KF944357) were identical to Glomerella/Colletotrichum fioriniae (JN121190 and KF278459). Similarly, the amplified (672 bp) GAPDH sequences (KF944354 and KF944355) were 99.6% similar over the 254 bp overlapping with C. fioriniae (JQ948622). Pathogenicity of two randomly chosen C. fioriniae isolates, TR-123 and TR-126, was confirmed by placing 4.75 mm diam. inoculated agar plugs from 8-day-old fungal cultures or a sterile plug (negative control) at the base of an axenic young seedling ~1.5 to 6.5 cm in height with at least one set of true leaves (1). Each treatment was replicated five times. Acute wilt and blighting of leaves and production of orange acervuli on cotyledons disease symptoms developed by 3 weeks post inoculation (WPI). By 7 WPI all but one of the Colletotrichum-inoculated plants were dead, whereas all of the control plants were healthy with significantly lower area under the disease progress curve values. Colletotrichum was consistently re-isolated, and confirmed morphologically and molecularly, from six of seven diseased seedlings, whereas two of two randomly chosen control seedlings remained asymptomatic and did not yield Colletotrichum. In summary, C. fioriniae may represent a natural biocontrol agent against poison ivy and scale insect herbivores thereof. References: (1) E. Benhase and J. Jelesko. HortScience 48:1, 2013. (2) U. Damm et al. Stud. Mycol. 73:37, 2012. (3) J. Marcelino et al. J. Insect Sci. 9:25, 2009. (4) R. Shivas et al. Fungal Divers. 39:111.

Los estilos APA, Harvard, Vancouver, ISO, etc.

37

Bomok, S., B. Taktaiev, M. Pikovskyi y O. Marieva. "Biochemical changes in affected potato tubers". Karantin i zahist roslin, n.º 1 (19 de marzo de 2020): 9–12. http://dx.doi.org/10.36495/2312-0614.2020.01.9-12.

Texto completo

Resumen

Goal. To establish biochemical changes (contents of dry matter, vitamin C, starch and carotene) in potato tubers in different degree affected by fungal diseases. Methods. Potato tubers (variety Bella Rosa) was selected in the conditions of private sector, Brusilovsky district, Zhytomyr region. Diagnosed disease by the visual method and a microscopic analysis with the subsequent identification of the pathogens. Biochemical analysis of potato tubers on dry matter content, vitamin C, starch, and carotene were performed according to standard techniques of the Institute of potato NAAS. The results of the research. The result of phytopathological examination of potato tubers during storage revealed fungal diseases: rot, Fusarium dry, Pomona, white, grey and verticillata; scab — plain and black or black scurf. Is established, that biochemical parameters in potatoes with different degree of damage differed. The amount of solids in healthy potato tubers were 21.0% in severely infected by Fusarium 14.5%, and famosa 13.9% and the usual scab — 18.2%; the blight of 15.6%. Starch in healthy tubers was 15.4% strongly struck by Fusarium is 7.5%, famosa — 6.9%, the usual scab — 11.2%, a Rhizoctonia — 9.8%. The content of vitamin C in healthy tubers was 0.17 percent, and in severe cases, Fusarium and 0.12%, famosa — 0.12%, ordinary scab and 0.12%, a Rhizoctonia — 0.12%. Biochemical indicators of carotene in healthy tubers was 0.18%, and in severely infected by Fusarium was reduced to 0.09%, famosa up to 0.06%, the usual scab — up to 0.11%, a Rhizoctonia — up to 0.10%. Conclusions. In potato tubers with different degrees of lesions of fungal diseases of reduced the content of dry matter, starch, vitamin C and carotene, which worsens their quality.

Los estilos APA, Harvard, Vancouver, ISO, etc.

38

Jensen, B. D., A. Massawe y I. S. Swai. "First Report of Gummy Stem Blight Caused by Didymella bryoniae on Watermelon and Confirmation of the Disease on Pumpkin in Tanzania". Plant Disease 95, n.º 6 (junio de 2011): 768. http://dx.doi.org/10.1094/pdis-01-11-0044.

Texto completo

Resumen

Foliar, stem, and fruit lesions were observed on watermelon (Citrullus lanatus (Thunb.) Matsum. & Nakai) and pumpkin (Cucurbita maxima Duchesne) in two separate research fields in the district of Arusha, Tanzania during the warm, rainy season from February to April 2010. Similar symptoms were observed in commercial watermelon fields and intercropped pumpkin fields in Same and Moshi districts with as much as 100% fruit loss in watermelon. Disease symptoms on watermelon were dark brown, V-shaped leaf lesions. On pumpkin, V-shaped leaf lesions were light brown. On both hosts, stems showed water-soaked lesions after rain, which dried up and cracked. On pumpkin, a gummy, amber exudate was seen after rain on stem and fruit lesions. Flowers and fruits of both hosts developed black rot spots and aborted. Isolation of the causal agent on potato dextrose agar (PDA) from leaf and stem pieces of watermelon and pumpkin plants in Arusha showed white-to-olivaceous green mycelium. Pycnidia formed on one-quarter-strength PDA and produced hyaline, oblong conidia mainly with two guttules, nonseptate, 5 to 11 × 3 to 5 μm. Pathogenicity was tested with three isolates from watermelon and one from pumpkin on four 1-month-old plants per watermelon cvs. Sugar Baby and Charleston Grey and pumpkin cv. Small Sugar per isolate. The test was repeated on the watermelon cultivars. One site on the main stem and two leaves per plant were misted, pricked with a scalpel, inoculated with 3-day-old mycelial plugs (5 × 5 mm), and kept humid at 20 to 30°C in cellophane bags for 3 days. All plants developed leaf and/or stem lesions. Detached, misted leaves were also laid on 2% water agar and inoculated as above. Water-soaked lesions developed around inoculation sites and microscopy of infected tissue revealed pycnidia with conidia as described above. All isolates infected both hosts. A set of control plants and detached leaves, mock inoculated with agar plugs, remained symptomless. The fungus was reisolated from infected leaves and stems of both hosts. On the basis of the morphological characteristics, the fungus was identified as Didymella bryoniae (Auersw.) Rehm (anamorph Phoma cucurbitacearum (Fr.:Fr.) Sacc.) (1,3) and this was confirmed by amplification of species-specific PCR products. The isolates from both hosts were cultured in liquid medium, and DNA was extracted using a DNeasy Plant Mini Kit (Qiagen, Valencia, CA). PCR and multiplex PCR involving D. bryoniae-unique primer sequences D6 and D7S, in combination with primer UNLO28S22, produced the expected band sizes (2). To our knowledge, this is the first report of gummy stem blight and black fruit rot of watermelon caused by D. bryoniae in Tanzania, which confirms a previous report of leaf spot on pumpkin (4), and the first report of black fruit rot on pumpkin. The disease was previously an unidentified problem in watermelon and the severe outbreak was associated with favorable weather conditions. References: (1) A. P. Keinath et al. Phytopathology 85:364, 1995. (2) C. A. Koch and R. S. Utkhede. Can. J. Plant Pathol. 26:291, 2004. (3) E. Punithalingam and P. Holliday. No. 332 in: Descriptions of Pathogenic Fungi and Bacteria. CMI, Kew, Surrey, UK, 1972. (4) E. A. Riley. Mycol. Pap. 75:1, 1960.

Los estilos APA, Harvard, Vancouver, ISO, etc.

39

Preetham, Anusha, Sayed Sayeed Ahmad, Ihab Wattar, Pooja Singh, Sandeep Rout, Mejdal A. Alqahtani y Enoch Tetteh Amoatey. "Instinctive Recognition of Pathogens in Rice Using Reformed Fractional Differential Segmentation and Innovative Fuzzy Logic-Based Probabilistic Neural Network". Journal of Food Quality 2022 (20 de junio de 2022): 1–17. http://dx.doi.org/10.1155/2022/8662254.

Texto completo

Resumen

Rice is an essential primary food crop in the world, and it plays a significant part in the country’s economy. It is the most often eaten stable food and is in great demand in the market as the world’s population continues to expand. Rice output should be boosted to fulfil the growing demand. As a result, the yield of plant crops diminishes, creating an environment conducive to the spread of infectious illnesses. To boost the production of agricultural fields, it is necessary to remove plant diseases from the environment. This study presents ways for recognising three types of rice plant diseases, as well as a healthy leaf, in rice plants. This includes image capture, image preprocessing, segmentation, feature extraction, and classification of three rice plant illnesses, as well as classification of a healthy leaf, among other techniques. Following the K-means segmentation, the features are extracted utilising three criteria, which are colour, shape, and texture, to generate a final product. Colour, shape, and texture are the parameters used in the extraction of the features. It is proposed that a novel intensity-based technique is used to retrieve colour features from the infected section, whereas the form parameters of the infected section, such as the area and diameter, and the texture characteristics of the infected section are extracted using a grey-level co-occurrence matrix. The colour features are retrieved depending on the characteristics of the features. All three previous techniques were surpassed by the proposed fuzzy logic-based probabilistic neural network on a range of performance metrics, with the new network obtaining greater accuracy. Finally, the result is validated using the fivefold cross-validation method, with the final accuracy for the diseases such as bacterial leaf blight, brown spot, healthy leaf, and rice blast being 95.20 percent, 97.60 percent, 99.20 percent, and 98.40 percent, respectively, and 95.40 percent for the disease brown spot.

Los estilos APA, Harvard, Vancouver, ISO, etc.

40

Yadesa, Lemi, Debela Diro y Zelalem Tafa. "General and Specific Combining Ability of Quality Protein Maize (Zea mays L.) Inbred Lines for Major Foliar Diseases, Grain Yield and Other Agronomic Traits Evaluated at Mid-altitude Agroecology of Ethiopia". Middle East Research Journal of Agriculture and Food Science 1, n.º 1 (28 de diciembre de 2021): 7–17. http://dx.doi.org/10.36348/merjafs.2021.v01i01.002.

Texto completo

Resumen

Abstract: Despite the fact that maize is a crucial cereal crop for food security, several foliar diseases are the main threats and limitations maize production in Ethiopia, resulting in low yields, particularly quality protein maize (QPM). Accordingly, national maize research program of Ethiopia has released QPM maize varieties adapted to the mid-altitude, low moisture stress and highland agro-ecologies of the country. Nonetheless, the market share of these varieties is generally small due to these reason and other features that have limited their adoption by farmers. General and specific combining ability analysis is one of the powerful instruments in identifying the best combiners that may be used in crosses to accumulate biotic resistance and productive alleles. A line x tester analysis involving 36 crosses generated by crossing 9 selected maize inbred lines with 4 testers were evaluated for different desirable agronomic traits during 2019/2020 main season at Bako and Jimma. The purpose of the experiment were to determine the GCA and SCA combining ability of QPM inbred lines, adapted to mid altitude agroecology of Ethiopia for grain yield and major foliar diseases. The crosses were evaluated in alpha lattice design replicated 3 times. For analysis of days to silking interval, days to maturity, turcicum leaf blight, grey leaf spot, common rust disease severity index, and grain yield were recorded. Analyses of variances showed significant mean squares due to crosses for almost all the traits studied. GCA mean squares due to lines and testers were significant (P<0.05 or P<0.01) for most studied traits. SCA mean squares were also significant for most attributes and major foliar maize diseases across locations. The comparative importance of GCA and SCA variances observed in the current study for most studied traits. Inbred lines L1, L2, L5 and L8 exhibited negative and highly significant GCA effects for husk cover. From this conduct it can be decided that better performing hybrids, inbred lines with desirable GCA and cross combinations with desirable SCA effects for grain yield, major foliar maize diseases and other traits were successfully identified.

Los estilos APA, Harvard, Vancouver, ISO, etc.

41

Chen, Yingjuan, Liang Zeng, Na Shu, Maoyuan Jiang, Han Wang, Yunjin Huang y Huarong Tong. "Pestalotiopsis-Like Species Causing Gray Blight Disease on Camellia sinensis in China". Plant Disease 102, n.º 1 (enero de 2018): 98–106. http://dx.doi.org/10.1094/pdis-05-17-0642-re.

Texto completo

Resumen

Gray blight of tea, caused by several Pestalotiopsis-like species, is one of the most destructive foliar diseases in tea cultivation yet the characteristics of these pathogens have not been confirmed until now. With morphological and multigene phylogenetic analyses, we have identified the gray blight fungi as Pseudopestalotiopsis camelliae-sinensis, Neopestalotiopsis clavispora, and Pestalotiopsis camelliae. Phylogenetic analyses derived from the combined internal transcribed spacer, β-tubulin, and translation elongation factor 1-α gene regions successfully resolved most of the Pestalotiopsis-like species used in this study with high bootstrap supports and revealed three major clusters representing these three species. Differences in colony appearance and conidia morphology (shape, size, septation, color and length of median cells, and length and number of apical and basal appendages) were consistent with the phylogenetic grouping. Pathogenicity tests validated that all three species isolated from tea leaves were causal agents of gray blight disease on tea plant (Camellia sinensis). This is the first description of the characteristics of the three species Pseudopestalotiopsis camelliae-sinensis, N. clavispora, and Pestalotiopsis camelliae as causal agents of tea gray blight disease in China.

Los estilos APA, Harvard, Vancouver, ISO, etc.

42

Guzeeva, A. A., I. A. Kapitova, S. V. Dolgov y Yu V. Burmenko. "Advances and outlook of horticultural bioengineering". Horticulture and viticulture, n.º 6 (30 de diciembre de 2021): 17–29. http://dx.doi.org/10.31676/0235-2591-2021-6-17-29.

Texto completo

Resumen

A Branch of modern biotechnology for creating unique relevant genotypes is bioengineering that harnesses a spectrum of plant genome modification technologies. The study aimed to analyse the current state of the art in genome modification of fruit and berry crops for more significant (vs. premium pure breeding varieties) deviations of norm in the traits and properties of biotic and abiotic resistance, productivity, fruit quality, etc. First horticultural crop transformation studies aimed at developing protocols based on selectable enzyme marker genes of phosphorylationmediated aminoglycoside antibiotics detoxification. Neomycin phosphotransferase nptII constitutes the most common system of transgenic fruit and berry crop selection. In pome crops, the transgenic selection priorities were resistance to scab (Venturia inaequalis (Wint.) Cke), rust (Gymnosporangium juniper-virginianae Schwein.) and bacterial blight (Erwinia amylovora Burrill, Winslow et al.), higher fruit quality, including bright colouring, and reduced enzymatic browning. In stone crops, it was tolerance to plum pox (PPV), papaya ringspot (PRSV) and Prunus necrotic ringspot (PNRSV) viruses. In berry crops — resistance to Sphaerotheca humuli (DC.) Burrill fungus, grey mould (Botrytis cinerea Pers.), root rot (Phytophthora cactorum (Lebert & Cohn) J.Schrot.) and powdery mildew (Oidium tuckeri Berkeley), as well as higher fruit quality. In citruses — resistance to bacterial canker (Xanthomonas citri sub sp.), citrus ulcer (Xanthomonas axonopodis pv citri), greening disease (Huanglongbing (HLB)) and fungi (Trichoderma harzianum Rifai). In tropical crops — resistance to papaya ringspot (PRSV) and banana streak (eBSV) viruses. Unique FT-phenotype transgenic fruit lines are leveraged in the new FasTrack breeding strategy. Nine fruit and berry transgenic crop lines have now been registered worldwide. Transgenic Arctic apples (Golden, Granny, Fuji), plums (Honey Sweet) and papaya (Rainbow, SunUp, Laie Gold) are industry-approved in fresh and processed form. The transgenic list regulated in the Russian Federation does not include fruit or berry crops.

Los estilos APA, Harvard, Vancouver, ISO, etc.

43

Jadhav, Sachin B., Vishwanath R. Udup y Sanjay B. Patil. "Soybean leaf disease detection and severity measurement using multiclass SVM and KNN classifier". International Journal of Electrical and Computer Engineering (IJECE) 9, n.º 5 (1 de octubre de 2019): 4077. http://dx.doi.org/10.11591/ijece.v9i5.pp4077-4091.

Texto completo

Resumen

Soybean fungal diseases such as Blight, Frogeye leaf spot and Brown Spot are a significant threat to soybean plant due to the severe symptoms and lack of treatments. Traditional diagnosis of the thease diseases relies on disease symptom identification based on neaked eye observation by pathalogiest, which can lead to a high rate of false-recognition. This work present a novel system, utilizing multiclass support vector machine and KNN classifiers, for detection and classification of soybean diseases using color images of diseased leaf samples. Images of healthy and diseased leaves affected by Blight, Frogeye leaf spot and Brown Spot were acquired by a digital camera. The acquired images are preprocessed using image enhancement techniques. The background of each image was removed by a thresholding method and the Region of Interest (ROI) is obtained. Color-based segmentation technique based on K-means clustering is applied to the region of interest for partitioning the diseased region. The severity of disease is estimated by quantifying a number of pixels in the diseased region and in total leaf region. Different color features of segmented diseased leaf region were extracted using RGB color space and texture features were extracted using Gray Level Co-occurrence Matrix (GLCM) to compose a feature database. Finally, the support vector machine (SVM) and K-Nearest Negbiour (KNN) classifiers are used for classifying the disease. This proposed classifers system is capable to classify the types of blight, brown spot, frogeye leaf spot diseases and Healthy samples with an accuracy of 87.3% and 83.6 % are achieved.

Los estilos APA, Harvard, Vancouver, ISO, etc.

44

Serdyuk, O. A., V. S. Trubina y L. A. Gorlova. "Analysis of diseases affecting winter and spring forms of Brassica napus L. and Brassica juncea L. in the central zone of the Krasnodar region". IOP Conference Series: Earth and Environmental Science 937, n.º 3 (1 de diciembre de 2021): 032114. http://dx.doi.org/10.1088/1755-1315/937/3/032114.

Texto completo

Resumen

Abstract The purpose of the research was a comparative evaluation of the disease affection of spring and winter forms of Brassica napus and Brassica juncea on the central zone of the Krasnodar region. Phytosanitary monitoring of diseases was carried out from the seedling stage. In 2011-2020, there were identified the diseases affecting winter and spring crops Brassica napus and Brassica juncea to the same extent: the occurrence frequency of downy mildew and powdery mildew was high, of Alternaria blight – from medium to high, of phytoplasma and bacterial blight – low. Differences are established for Sclerotinia disease, Phoma rot, Fusarium blight, white rust, gray rot. The occurrence frequency of Sclerotinia disease on winter form of Brassica napus and Brassica juncea varied in research years from low to medium, of Phoma rot – from medium to high; on spring forms, these diseases were noted in certain years with the low frequency. Fusarium blight affected only sowings of spring forms of Brassica napus and Brassica juncea with medium and high frequency, except for 2018-2019, when it was low. White rust affected only spring from of Brassica napus, gray rot – only winter forms of Brassica napus and Brassica juncea in certain years with the low frequency.

Los estilos APA, Harvard, Vancouver, ISO, etc.

45

Rachmad, Aeri, Mohammad Syarief, Silfia Rifka, Fifin Sonata, Wahyudi Setiawan y Eka Mala Sari Rochman. "Corn Leaf Disease Classification Using Local Binary Patterns (LBP) Feature Extraction". Journal of Physics: Conference Series 2406, n.º 1 (1 de diciembre de 2022): 012020. http://dx.doi.org/10.1088/1742-6596/2406/1/012020.

Texto completo

Resumen

Abstract Corn is a plant that is widely grown in developing countries such as Indonesia. To increase maize yields, researchers are always innovating on the current state of technology for classifying maize plant diseases. Three kinds of diseases attack corn leaves, namely Gray leaf Spot, Blight, and Common Rush. The amount of data that we use is 3500 data consisting of 500 Gray Leaf Spots, 1000 Blights, 1000 Common Rushes, and 1000 healthy leaves. This study aims to develop an artificial intelligence model. The artificial intelligence model that we developed uses LBP feature extraction combined with k-NN for the classifier. In addition to using the k-NN method, our tests were carried out using several classification methods such as Naïve Bayes and Adaboost. The result of our test is that the k-NN method has the highest value compared to the Naïve Bayes and Adaboost methods. The results of the performance using k-NN with k=5 resulted in a value of 81.1%, the AUC value of 94.1%, the F1-Score of 80.9%, Precision of 81.8%, and Recall of 81.1%.

Los estilos APA, Harvard, Vancouver, ISO, etc.

46

Wang, Bin, Yongyan Zhang, Jiapeng Liu, Ou Sheng, Fan Liu, Dongliang Qiu, Peitao Lü, Guiming Deng y Chunzhen Cheng. "A New Leaf Blight Disease Caused by Alternaria jacinthicola on Banana in China". Horticulturae 8, n.º 1 (23 de diciembre de 2021): 12. http://dx.doi.org/10.3390/horticulturae8010012.

Texto completo

Resumen

A leaf blight disease with an incidence level of about 50% was found on Robusta banana in Guangdong province of China in September 2020. The early symptom appeared as pale gray to black brown, irregular, small, necrotic lesions mainly on the top 3–5 leaves. Severely infected leaves were withered and necrotic. Two representative fungus strains, strain L1 and strain L2, were isolated from affected banana leaves, and morphological and molecular identification analysis confirmed that the two fungi were both Alternaria jacinthicola. Many Alternaria species have been reported to cause wilting, decay, leaf blight and leaf spots on plants and lead to serious economic losses in their production, including A. alternata, causing leaf blight and leaf sport diseases on banana. The Koch’s postulates of A. jacinthicola causing the leaf blight disease was further fulfilled, which confirmed that it is the causal agent of this disease. To our knowledge, this is the first report of A. jacinthicola causing leaf blight on banana in China.

Los estilos APA, Harvard, Vancouver, ISO, etc.

47

Tan, Rongrong, Long Jiao, Danjuan Huang, Xun Chen, Hongjuan Wang y Yingxin Mao. "Comparative Transcript Profiling of Resistant and Susceptible Tea Plants in Response to Gray Blight Disease". Agronomy 14, n.º 3 (11 de marzo de 2024): 565. http://dx.doi.org/10.3390/agronomy14030565.

Texto completo

Resumen

Gray blight disease stands as one of the most destructive ailments affecting tea plants, causing significant damage and productivity losses. However, the dynamic roles of defense genes during the infection of gray blight disease remain largely unclear, particularly concerning their distinct responses in resistant and susceptible cultivars. In the pursuit of understanding the molecular interactions associated with gray blight disease in tea plants, a transcriptome analysis unveiled that 10,524, 17,863, and 15,178 genes exhibited differential expression in the resistant tea cultivar (Yingshuang), while 14,891, 14,733, and 12,184 genes showed differential expression in the susceptible tea cultivar (Longjing 43) at 8, 24, and 72 h post-inoculation (hpi), respectively. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses highlighted that the most up-regulated genes were mainly involved in secondary metabolism, photosynthesis, oxidative phosphorylation, and ribosome pathways. Furthermore, plant hormone signal transduction and flavonoid biosynthesis were specifically expressed in resistant and susceptible tea cultivars, respectively. These findings provide a more comprehensive understanding of the molecular mechanisms underlying tea plant immunity against gray blight disease.

Los estilos APA, Harvard, Vancouver, ISO, etc.

48

Vafin, Ilshat y Radik Safin. "The effectiveness of using Metallocene fertilizers for the spray-dressing of winter wheat". BIO Web of Conferences 37 (2021): 00184. http://dx.doi.org/10.1051/bioconf/20213700184.

Texto completo

Resumen

This article presents the impact assessment results for the spay-dressing of different Metallocene compound fertilizers containing chelated microelements on the yield and quality of winter wheat seeds of the Kazanskaya 560 variety. The research was carried out on the grey forest soils in the Kama region of the Republic of Tatarstan in 2017–2020. The plants were dressed with fertilizers in the autumn and the spring and summer period. In the autumn, we used the fertilizer containing manganese (Metallocene D), and in the spring and summer period (the tillering and earing stages of the winter wheat), we used the Metallocene Universal compound fertilizer with several microelements. During the research, we established that applying the manganese-containing Metallocene D in the autumn has a significant positive effect on the growth and dry biomass accumulation of the winter wheat. The dressing with Metallocene Universal during the tillering and earing stages following the application of Metallocene D in the autumn resulted in an increased/stimulated plant growth and development. The highest yield of winter wheat (3.45 t/ha or 46 % above the reference value) was obtained through the dressing of Metallocene D at a rate of 2 l/ha in the autumn, and the spraying of the plants with Metallocene Universal done twice during the spring and summer period. The autumn application of Metallocene D and the twofold application of Metallocene Universal improve the qualitative parameters of new winter wheat seeds. The use of fertilizers in questions improved the laboratory germination of the seeds and significantly reduced the root rot agent infection rate. The twofold dressing during the spring and summer period following the autumn dressing helped to suppress the most dangerous infections, such as the fusarium blight and the Helmintosporium disease, in the new seeds almost completely. The research conducted showed that Metallocene fertilizers can be successfully used to improve the production of winter wheat and seeds.

Los estilos APA, Harvard, Vancouver, ISO, etc.

49

Borovskaya, I. y V. Petrenkova. "Zonal pathogen complex of sunflower in the left bank Forest-Steppe of Ukraine". Agricultural Science and Practice 5, n.º 1 (15 de abril de 2018): 67–72. http://dx.doi.org/10.15407/agrisp5.01.067.

Texto completo

Resumen

Aim. To determine a set of sunfl ower pathogens and their variability infl uenced by hydrothermal conditions of the crop growing season. Methods. Over the period of 2007–2016, due to phytosanitary monitoring of breeding crops of the scientifi c crop rotation of the Plant Production Institute named after V.Ya. Yuriev of NAAS, the prevalence degree, development intensity and variability of sunfl ower diseases in the Eastern Forest-Steppe of Ukraine were estimated. The hydrothermal coeffi cient (HTC) is presented for the sunfl ower growing season and by developmental phases of the crop. Results. Phomopsis blight (Phomopsis/Diaporthe helianthi Munt.- Cvet. et al.), gray mold (Botrytis cinerea Pers.), dry rot (Rhizopus sp.), charcoal rot (Sclerotium bataticolaTaub), and downy mildew (Plasmopara helianthi Novot. f. helianthi) were the most common diseases on sunfl ower in the Eastern Forest-Steppe of Ukraine in 2007–2016. The weather conditions of 2007–2016 considerably varied and were characterized by fl uctuations in the hydrothermal coeffi cient (HTC) from 0.57 in 2009 to 1.1 in 2014. Assessing the incidence of the fi ve most common and harmful sunfl ower diseases (dry rot, charcoal rot, gray mold, Phomopsis blight, downy mildew) by cluster analysis for the ten-year study period in relation to the weather conditions of a year, we found that both dry and charcoal rots were co-associated with aridity, while downy mildew and gray mold were frequently promoted by waterlogging during a certain period of sunfl ower development. Unlike the other diseases, Phomopsis blight, being an annual disease, appears to have no clear dependence on any specifi c conditions. Conclusions. Based on the phytosanitary monitoring results of crops in the Eastern Forest-Steppe of Ukraine, the sunfl ower phytopathogen complex composition was determined. The prevalence degrees for Phomopsis blight, gray mold, dry rot, charcoal rot, and downy mildew as well as the development intensities of Phomopsis and gray mold were established. The co-incidence of the fi ve most harmful sunfl ower diseases in the Eastern Forest-Steppe of Ukraine (dry rot, charcoal rot, gray mold, Phomopsis blight, downy mildew) was evaluated during the ten-year study period, depending on the weather conditions of a year.

Los estilos APA, Harvard, Vancouver, ISO, etc.

50

Zheng, Shiqin, Zhenghua Du, Xiaxia Wang, Chao Zheng, Zonghua Wang y Xiaomin Yu. "Metabolic Rewiring in Tea Plants in Response to Gray Blight Disease Unveiled by Multi-Omics Analysis". Metabolites 13, n.º 11 (1 de noviembre de 2023): 1122. http://dx.doi.org/10.3390/metabo13111122.

Texto completo

Resumen

Gray blight disease, which is caused by Pestalotiopsis-like species, poses significant challenges to global tea production. However, the comprehensive metabolic responses of tea plants during gray blight infection remain understudied. Here, we employed a multi-omics strategy to characterize the temporal transcriptomic and metabolomic changes in tea plants during infection by Pseudopestalotiopsis theae, the causal agent of gray blight. Untargeted metabolomic profiling with ultra-performance liquid chromatography–quadrupole time-of-flight mass spectrometry (UPLC-QTOFMS) revealed extensive metabolic rewiring over the course of infection, particularly within 24 h post-inoculation. A total of 64 differentially accumulated metabolites were identified, including elevated levels of antimicrobial compounds such as caffeine and (−)-epigallocatechin 3-gallate, as well as oxidative catechin polymers like theaflavins, theasinensins and theacitrins. Conversely, the synthesis of (+)-catechin, (−)-epicatechin, oligomeric proanthocyanidins and flavonol glycosides decreased. Integrated omics analyses uncovered up-regulation of phenylpropanoid, flavonoid, lignin biosynthesis and down-regulation of photosynthesis in response to the pathogen stress. This study provides novel insights into the defense strategies of tea plants against gray blight disease, offering potential targets for disease control and crop improvement.

Los estilos APA, Harvard, Vancouver, ISO, etc.

Artículos de revistas sobre el tema "Grey blight disease"

Crea una cita precisa en los estilos APA, MLA, Chicago, Harvard y otros