scholarly journals Measurement of Leaf Spot Disease Severity in Turmeric Plant

2020 ◽  
Vol 3 (12) ◽  
pp. 164-167
Author(s):  
Manjula R. Chougala ◽  
A. C. Ramachandra
Keyword(s):  
Image Processing ◽  
Leaf Spot ◽  
Cost Effective ◽  
Area Measurement ◽  
Leaf Spot Disease ◽  
Agriculture Sector ◽  
Major Constraint ◽  
Hands On ◽  
Infected Area ◽  
Colour Feature

Digital Image Processing (DIP) applications in agriculture sector is becoming popular because of its fast, cost-effective and accurate solutions related to diseases and marketing. The hands-on solutions are being provided through various applications. Leaf Sopot disease has become the major constraint in the turmeric cultivation in India. Colletotrichum capsici is a fungal disease commonly known as leaf Spot. The brown spots of 4-5 cm length and 2-3 cm width with a grey centre are found on either surface of the leaves. If not treated timely, it causes the heavy loss in terms of quality and quantity. This paper proposes the methodology using Image Processing for measuring the severity of this disease in plant pathology. The image acquisition of infected leaves is done in the first stage then the images are pre-processed. Histogram is used for colour feature extraction The Edge detection methodology is used for infected area measurement and the results are fed to disease classifier to identify the stage of disease. This helps the plant pathologist in preparing consultative module to eradicate the disease completely.

TWO NEW SEVERE LEAF SPOT DISEASE ON FOREST TREES OF JALGAON (MAHARASTRA) INDIA

2017 ◽  
Vol 23 (2) ◽  
Author(s):  
S. A. FIRDOUSI
Keyword(s):  
Leaf Spot ◽  
Fungal Disease ◽  
Leaf Spot Disease ◽  
Forest Trees ◽  
First Report ◽  
Spot Disease ◽  
Severe Leaf

During the survey of the forest fungal disease, of Jalgaon district, two severe leaf spot diseases on Lannae coromandelica and ( Ougenia dalbergioides (Papilionaceae) were observed in Jalgaon, forest during July to September 2016-17. The casual organism was identified as Stigmina lanneae and Phomopsis sp. respectively1-4,7. These are first report from Jalgaon and Maharashtra state.

Rapid Inoculation Technique and Biological Control of Leaf Spot Disease in Oil Palm

2019 ◽  
Vol 2 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Delia Agustina ◽  
◽  
Cahya Prihatna ◽  
Antonius Suwanto ◽  
◽  
...  
Keyword(s):  
Biological Control ◽  
Oil Palm ◽  
Leaf Spot ◽  
Leaf Spot Disease ◽  
Inoculation Technique ◽  
Spot Disease

scholarly journals Registration of three peanut allotetraploid interspecific hybrids resistant to late leaf spot disease and tomato spotted wilt

2021 ◽  
Author(s):  
Ye Chu ◽  
H. Thomas Stalker ◽  
Kathleen Marasigan ◽  
Chandler M. Levinson ◽  
Dongying Gao ◽  
...  
Keyword(s):  
Leaf Spot ◽  
Interspecific Hybrids ◽  
Leaf Spot Disease ◽  
Late Leaf Spot ◽  
Spot Disease ◽  
Tomato Spotted Wilt

scholarly journals Laminarin Induces Defense Responses and Efficiently Controls Olive Leaf Spot Disease in Olive

Molecules ◽  
2021 ◽  
Vol 26 (4) ◽  
pp. 1043
Author(s):  
George T. Tziros ◽  
Anastasios Samaras ◽  
George S. Karaoglanidis
Keyword(s):  
Leaf Spot ◽  
Defense Responses ◽  
Copper Accumulation ◽  
Leaf Spot Disease ◽  
Biological Control Agents ◽  
Olive Leaf ◽  
Control Efficacy ◽  
Resistance Inducers ◽  
Kinetics Of ◽  
Potential Use

Olive leaf spot (OLS) caused by Fusicladiumoleagineum is mainly controlled using copper fungicides. However, the replacement of copper-based products with eco-friendly alternatives is a priority. The use of plant resistance-inducers (PRIs) or biological control agents (BCAs) could contribute in this direction. In this study we investigated the potential use of three PRIs (laminarin, acibenzolar-S-methyl, harpin) and a BCA (Bacillus amyloliquefaciens FZB24) for the management of OLS. The tested products provided control efficacy higher than 68%. In most cases, dual applications provided higher (p < 0.05) control efficacies compared to that achieved by single applications. The highest control efficacy of 100% was achieved by laminarin. Expression analysis of the selected genes by RT-qPCR revealed different kinetics of induction. In laminarin-treated plants, for most of the tested genes a higher induction rate (p < 0.05) was observed at 3 days post application. Pal, Lox, Cuao and Mpol were the genes with the higher inductions in laminarin-treated and artificially inoculated plants. The results of this study are expected to contribute towards a better understanding of PRIs in olive culture and the optimization of OLS control, while they provide evidence for potential contributions in the reduction of copper accumulation in the environment.

scholarly journals First report of chick peach (Prunus persica L.) leaf spot disease caused by Didymella glomerata in China

2021 ◽  
Author(s):  
Yiping Cui ◽  
Aitian Peng ◽  
Xiaobing Song ◽  
Baoping Cheng ◽  
Jinfeng Ling ◽  
...  
Keyword(s):  
Leaf Spot ◽  
Prunus Persica ◽  
Leaf Spot Disease ◽  
First Report ◽  
Spot Disease

scholarly journals The Utility of the Upcoming HyspIRI’s Simulated Spectral Settings in Detecting Maize Gray Leafy Spot in Relation to Sentinel-2 MSI, VENµS, and Landsat 8 OLI Sensors

Agronomy ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. 846
Author(s):  
Mbulisi Sibanda ◽  
Onisimo Mutanga ◽  
Timothy Dube ◽  
John Odindi ◽  
Paramu L. Mafongoya
Keyword(s):  
Food Security ◽  
Precision Agriculture ◽  
Leaf Spot ◽  
Gray Leaf Spot ◽  
Economic Losses ◽  
Leaf Spot Disease ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Maize Crop ◽  
Sentinel 2

Considering the high maize yield loses caused by incidences of disease, as well as incomprehensive monitoring initiatives in crop farming, there is a need for spatially explicit, cost-effective, and consistent approaches for monitoring, as well as for forecasting, food-crop diseases, such as maize Gray Leaf Spot. Such approaches are valuable in reducing the associated economic losses while fostering food security. In this study, we sought to investigate the utility of the forthcoming HyspIRI sensor in detecting disease progression of Maize Gray Leaf Spot infestation in relation to the Sentinel-2 MSI and Landsat 8 OLI spectral configurations simulated using proximally sensed data. Healthy, intermediate, and severe categories of maize crop infections by the Gray Leaf Spot disease were discriminated based on partial least squares–discriminant analysis (PLS-DA) algorithm. Comparatively, the results show that the HyspIRI’s simulated spectral settings slightly performed better than those of Sentinel-2 MSI, VENµS, and Landsat 8 OLI sensor. HyspIRI exhibited an overall accuracy of 0.98 compared to 0.95, 0.93, and 0.89, which were exhibited by Sentinel-2 MSI, VENµS, and Landsat 8 OLI sensor sensors, respectively. Furthermore, the results showed that the visible section, red-edge, and NIR covered by all the four sensors were the most influential spectral regions for discriminating different Maize Gray Leaf Spot infections. These findings underscore the potential value of the upcoming hyperspectral HyspIRI sensor in precision agriculture and forecasting of crop-disease epidemics, which are necessary to ensure food security.

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