Early Visualization Detection of Gray Mold (Botrytis) on Eggplant Leaves Based on Multi-Spectral Image

2015 ◽  
Vol 741 ◽  
pp. 323-327
Author(s):  
Yan Yang
Keyword(s):  
Detection Method ◽  
Early Stage ◽  
Gray Mold ◽  
Usual Method ◽  
Excessive Amount ◽  
Disease Spread ◽  
Spectral Image ◽  
Fungal Strains ◽  
Entire Field ◽  
Fungus Disease

Gray mold (Botrytis) is a common fungus disease on eggplants,it can reduce the production by 20-30% at worse. Most disease infestations are not evenly distributed across the cultivation area but in patches [1]. The usual method of prevention is spraying fungicide on entire field, which would requires an excessive amount of fungicide and resulting, increases cost of production, pollutes the environment, and improves of resistance fungal strains [2]. In fact, the fungicide can be spray only the area infected which is rather small on the early stage and it is fully capable of controlling disease spread. Therefore, rapid disease detection is the key. The accurate and effective detection method would be helpful for reducing the dosage of fungicide and preventing disease spread.

scholarly journals Spread and Increase of Ratoon Stunting Disease of Sugarcane and Comparison of Disease Detection Methods

Plant Disease ◽  
1999 ◽  
Vol 83 (12) ◽  
pp. 1170-1175 ◽  
Author(s):  
J. W. Hoy ◽  
M. P. Grisham ◽  
K. E. Damann
Keyword(s):  
Yield Loss ◽  
Detection Method ◽  
Xylem Sap ◽  
Disease Spread ◽  
Detection Methods ◽  
Disease Detection ◽  
Correct Identification ◽  
Dot Blot ◽  
Ratoon Stunting Disease ◽  
Enzyme Immunoassays

The spread and increase of ratoon stunting disease (RSD) resulting from two mechanical harvests were compared in eight sugarcane cultivars at two locations. RSD spread and increase were detected in the ratoon crops grown after each harvest and varied among cultivars and locations. Disease spread and increase were greater in plants grown from stalks collected at the first harvest than in the first ratoon growth from the harvested field. RSD infection was determined using five disease detection methods: alkaline-induced metaxylem autofluorescence; microscopic examination of xylem sap; and dot blot, evaporative-binding, and tissue blot enzyme immunoassays. The tissue blot enzyme immunoassay was the most accurate RSD detection method. The dot blot and evaporative-binding enzyme immunoassays were the least sensitive for detection of RSD-infected stalks, and alkaline-induced metaxylem autofluorescence was least accurate for correct identification of noninfected stalks. The results indicate that disease spread and increase are variable even among cultivars susceptible to yield loss due to RSD, and the greatest threat of disease spread and increase occurs at planting.

COMPUTATIONAL FRAMEWORK TO EXPLORE IMPACT OF ENVIRONMENTAL STRESS ON EPIDEMICS

2020 ◽  
Vol 32 (06) ◽  
pp. 2050047
Author(s):  
Ayesha Sohail ◽  
Muhammad Idrees ◽  
Maria Sajjad ◽  
Sahrish Iftikhar ◽  
Sümeyye Tunc
Keyword(s):  
Reverse Engineering ◽  
Environmental Stress ◽  
Early Stage ◽  
Environmental Stresses ◽  
Vital Role ◽  
Disease Spread ◽  
Mutation Rates ◽  
Vector Borne Diseases ◽  
Adaptive Shifts ◽  
The Impact

In the field of epidemiology, not only the disease and the carriers, but also the surrounding environment and the associated stresses play a vital role. Environmental stresses in a novel habitat may facilitate adaptive shifts. Organisms living under environmental stresses often experience higher mutation rates and display greater phenotypic and genetic variation. There is controversial evidence available in the literature about the impact of environmental stresses on the organisms and the resulting variation in mutation rates and the immune responses. In nature, “selection” and the high energetic costs of stress usually reduce this variation. The prior knowledge of the interaction between the stress and disease epidemics may help to control the disease spread at an early stage. A mathematical model of epidemiology, specifically focusing on the vector borne diseases, with environmental stress is reported in this paper. The model is validated with the aid of stability analysis. During this research, a set of parametric values is obtained using reverse engineering. For this purpose, the parametric evaluation is reported with the help of Monte Carlo Markov Chain (MCMC) reverse engineering. Among other factors, the environmental stresses are also responsible for different dynamics of the same disease, in different continents of the world. The proposed research methodology will help in forecasting the epidemiological problems such as the current threat of coronavirus.

scholarly journals A Miniaturized Pump Out Method for Characterizing Molecule Interaction with ABC Transporters

2019 ◽  
Vol 20 (22) ◽  
pp. 5529 ◽  
Author(s):  
Emmanuel Sevin ◽  
Lucie Dehouck ◽  
Romain Versele ◽  
Maxime Culot ◽  
Fabien Gosselet
Keyword(s):  
Abc Transporters ◽  
Detection Method ◽  
Cell Model ◽  
Early Stage ◽  
Cell Monolayer ◽  
Efflux Pumps ◽  
Apparent Permeability ◽  
Traditional Use ◽  
Molecule Design ◽  
Molecule Interaction

Characterizing interaction of newly synthetized molecules with efflux pumps remains essential to improve their efficacy and safety. Caco-2 cell line cultivated on inserts is widely used for measuring apparent permeability of drugs across biological barriers, and for estimating their interaction with efflux pumps such as P-gp, BCRP and MRPs. However, this method remains time consuming and expensive. In addition, detection method is required for measuring molecule passage across cell monolayer and false results can be generated if drugs concentrations used are too high as demonstrated with quinidine. For this reason, we developed a new protocol based on the use of Caco-2 cell directly seeded on 96- or 384-well plates and the use of fluorescent substrates for efflux pumps. We clearly observed that the new method reduces costs for molecule screening and leads to higher throughput compared to traditional use of Caco-2 cell model. This accelerated model could provide quick feedback regarding the molecule design during the early stage of drug discovery and therefore reduce the number of compounds to be further evaluated using the traditional Caco-2 insert method.

scholarly journals Metabolic Profiling to Identify the Latent Infection of Strawberry by Botrytis cinerea

2019 ◽  
Vol 15 ◽  
pp. 117693431983851 ◽  
Author(s):  
Zhihong Hu ◽  
Xunian Chang ◽  
Tan Dai ◽  
Lei Li ◽  
Panqing Liu ◽  
...  
Keyword(s):  
Least Squares ◽  
Botrytis Cinerea ◽  
Partial Least Squares ◽  
Metabolic Profiling ◽  
Latent Infection ◽  
Early Stage ◽  
Interaction Mechanism ◽  
Gray Mold ◽  
Plant Pathogen Interaction ◽  
Metabolome Profiling

In plant-pathogen interaction systems, plant metabolism is usually agitated in the early stages of infection and much before visible symptoms appear. To identify the latent infection of strawberry by Botrytis cinerea by metabolome profiling, a metabolomics method based on gas chromatography and mass spectrometry was applied to identify the affected metabolites and discriminate diseased plants from healthy ones. An orthogonal partial least squares (OPLS) score plot showed that the metabolic profiling well separated B. cinerea-infected strawberry plants at 2, 5, and 7 days after infection from non-infected healthy plants. Combined analysis of variance (ANOVA) and OPLS analysis revealed candidate biomarkers of plant resistance and of infection and expansion of the pathogen in the plants. Among them, hexadecanoic acid, octadecanoic acid, sucrose, β-lyxopyranose, melibiose, and 1,1,4a-Trimethyl-5,6-dimethylenedecahydronaphthalene were closely related to the early stage of disease development when symptoms were not visible. A discrimination method that could distinguish Botrytis gray mold diseased strawberry plants from healthy ones was established based on the partial least squares discriminant analysis (PLS-DA) model with a correct recognition accuracy of 100%. This research offers a good application of metabolome profiling for early diagnosis of plant disease and interaction mechanism exploration.

scholarly journals Forecasting Confirmed Cases, Deaths, and Recoveries from COVID-19 in China during the Early Stage

2020 ◽  
Vol 2020 ◽  
pp. 1-4
Author(s):  
Lianyi Liu ◽  
Yan Chen ◽  
Lifeng Wu
Keyword(s):  
Theoretical Basis ◽  
Prevention And Control ◽  
Early Stage ◽  
Grey Model ◽  
Disease Spread ◽  
Forecasting Accuracy ◽  
And Control

To provide a theoretical basis for the prevention and control of COVID-19 in China, confirmed cases, deaths, and recoveries from COVID-19 in China were predicted using a fractional grey model. The results indicated that the grey model has high forecasting accuracy in the prediction of disease spread.

Detecting Loosening of Bolted Connections in a Pipeline Using Changes in Natural Frequencies

2011 ◽  
Author(s):  
K. He ◽  
W. D. Zhu
Keyword(s):  
Damage Detection ◽  
Natural Frequencies ◽  
Detection Method ◽  
Complex Geometry ◽  
Early Stage ◽  
Measurement Noise ◽  
Modeling Error ◽  
Bolted Connections ◽  
Bolted Connection ◽  
Stiffness Reduction

Loosening of bolted connections in a structure can significantly reduce the load-bearing capacities of the structure. Detecting loosening of bolted connections at an early stage can avoid failure of the structure. Due to the complex geometry of a bolted connection and the material discontinuity between the clamped components, it is difficult to detect loosening of a bolted connection using conventional non-destructive test methods. A vibration-based method that uses changes in natural frequencies of a structure to detect the locations and extent of damage can be used to detect loosening of bolted connections, since the method focuses on detecting a stiffness reduction, which can result from loosening of the bolted connections. Experimental and numerical damage detection using the vibration-based method was conducted to detect the loosening of the bolted connections in a fullsize steel pipeline with bolted flanges. With the recent development of a predictive modeling technique for bolted connections in thin-walled structures, an accurate physics-based finite element model of the pipeline that is required by the vibration-based damage detection method is developed. A trust-region search strategy is employed to improve the damage detection method so that convergence of the damage detection algorithm can be ensured for under-determined systems, and the robustness of the algorithm can be enhanced when relatively large modeling error and measurement noise are present. The location and extent of the loosened bolted connections were successfully detected in experimental damage detection using changes in the natural frequencies of the first several modes; the exact location and extent of the loosened bolted connections can be detected in the numerical simulation where there are no modeling error and measurement noise.

The Consumer Credit Act 1974

1975 ◽  
Vol 34 (1) ◽  
pp. 79-130 ◽  
Author(s):  
R. M. Goode
Keyword(s):  
Early Stage ◽  
Consumer Credit ◽  
Legal Framework ◽  
The State ◽  
Close Attention ◽  
Entire Field ◽  
The Law ◽  
Credit Law

The Consumer Credit Act, which after many vicissitudes was passed on 31 July 1974, represents the product of nearly six years' concentrated labour. The genesis of the Act was the appointment in 1968 of the Crowther Committee on Consumer Credit, whose twovolume Report covering the entire field of consumer credit, and much else besides, was published in March 1971. The Committee devoted close attention to the state of the law governing credit transactions, and at an early stage in its deliberations concluded that consumer credit could not be considered in isolation from the general legal framework within which credit was provided, whether for business or for consumers. Among the seven major defects in credit law identified by the Committee, three were fundamental.

Detecting Loosening of Bolted Connections in a Pipeline Using Changes in Natural Frequencies

2014 ◽  
Vol 136 (3) ◽  
Author(s):  
K. He ◽  
W. D. Zhu
Keyword(s):  
Damage Detection ◽  
Natural Frequencies ◽  
Detection Method ◽  
Complex Geometry ◽  
Early Stage ◽  
Measurement Noise ◽  
Modeling Error ◽  
Bolted Connections ◽  
Bolted Connection ◽  
Stiffness Reduction

Loosening of bolted connections in a structure can significantly reduce its load-bearing capacity. Detecting loosening of bolted connections at an early stage can prevent failure of the structure. Due to the complex geometry of a bolted connection and material discontinuity between clamped components, it is difficult to detect loosening of a bolted connection using conventional nondestructive test methods. A vibration-based method that uses changes in natural frequencies of a structure to detect locations and extent of damage can be used to detect loosening of bolted connections since the method focuses on detecting a stiffness reduction, which can result from loosening of bolted connections. Experimental and numerical damage detection was conducted to detect loosening of bolted connections in a full-size steel pipeline with bolted flanges using the vibration-based method. With the recent development of a modeling technique for bolted connections in thin-walled structures, an accurate physics-based finite element model of the pipeline that is required by the vibration-based damage detection method is developed. A trust-region search strategy is employed to improve the damage detection method so that global convergence of the damage detection algorithm can be ensured for underdetermined systems, and robustness of the algorithm can be enhanced when relatively large modeling error and measurement noise are present. The location and extent of loosened bolted connections were successfully detected in experimental damage detection using changes in natural frequencies of the first several elastic modes of the pipeline; the exact location and extent of the loosened bolted connections can be detected in numerical simulation where there are no modeling error and measurement noise.

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