Fungal disease detection in plants: Traditional assays, novel diagnostic techniques and biosensors

2017 ◽  
Vol 87 ◽  
pp. 708-723 ◽  
Author(s):  
Monalisa Ray ◽  
Asit Ray ◽  
Swagatika Dash ◽  
Abtar Mishra ◽  
K. Gopinath Achary ◽  
...  

Agriculture productivity is the main factor for improving economic status of India. Reduction in production rate is mainly due to various diseases in plants. Identification of plant disease in early stage is the main challenge for improving the production rate as well as economic status. This paper presents automatic disease detection in cotton crop for three types of diseases Alternaria Leaf Spot Fungal Disease (ALSFD), Grey Mildew Cotton Disease (GMCD), and Rust Foliar Fungal Disease (RFFD). The K-means clustering algorithm is used for disease segmentation for cotton leaf. The diseased cluster is segmented into three clusters. From cluster 2 the features Mean , Contrast, Energy, Correlation, Standard Deviation, Variance , Entropy, and Kurtosis are extracted. The extracted features for 30 samples are given to Artificial Neural Network (ANN) and Support Vector Machine (SVM) classifiers for disease classification. The performance of these classifiers are compared. The ALSF disease is classified 77.4% for ANN and 84.3% for SVM, GMC disease is 87.8% for ANN and 98.7% in SVM, RFF disease is 90.1%for ANN and 93.2% for SVM. The overall average accuracy of ANN classifier is 85.1% for three diseases and overall average accuracy for SVM is 92.06% for three diseases. It is clearly observed from the analysis SVM classifier gives accurate disease detection compared to ANN.


2008 ◽  
Vol 13 (2) ◽  
pp. 6-8
Author(s):  
Lorne Direnfeld ◽  
Christopher R. Brigham ◽  
Elizabeth Genovese

Abstract The AMA Guides to the Evaluation of Permanent Impairment (AMA Guides), does not provide a Diagnosis-based estimate of impairment due to syringomyelia, a disorder in which a cyst (syrinx), develops within the central spinal cord and destroys neural tissue as it expands. The AMA Guides, however, does provide an approach to rating a syringomyelia based on objective findings of neurological deficits identified during a neurological examination and demonstrated by standard diagnostic techniques. Syringomelia may occur after spinal cord trauma, including a contusion of the cord. A case study illustrates the rating process: The case patient is a 46-year-old male who fell backwards, landing on his upper back and head; over a five-year period he received a T5-6 laminectomy and later partial corpectomies of C5, C6, and C7, cervical discectomy C5-6 and C6-7; iliac crest strut graft fusion of C5-6 and C6-7; and anterior cervical plating of C5 to C7 for treatment of myelopathy; postoperatively, the patient developed dysphagia. The evaluating physician should determine which conditions are ratable, rate each of these components, and combine the resulting whole person impairments without omission or duplication of a ratable impairment. The article includes a pain disability questionnaire that can be used in conjunction with evaluations conducted according to Chapter 3, Pain, and Chapter 17, The Spine.


EDIS ◽  
2017 ◽  
Vol 2017 (4) ◽  
Author(s):  
Keith W. Wynn ◽  
Nicholas S. Dufault ◽  
Rebecca L. Barocco

This ten-page fact sheet includes a summary of various fungicide spray programs for fungal disease control of early leaf spot, late leaf spot, and white mold/stem rot of peanut in 2012-2016 on-farm trials in Hamilton County. Written by K.W. Wynn, N.S. Dufault, and R.L. Barocco and published by the Plant Pathology Department.http://edis.ifas.ufl.edu/pp334


2017 ◽  
Vol 23 (2) ◽  
Author(s):  
S. A. FIRDOUSI

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.


Author(s):  
Johnny Borghetto ◽  
Alfredo Contin ◽  
Andrea Morotti ◽  
Andrea Pegoiani ◽  
Giovanni Pirovano ◽  
...  

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