scholarly journals Effect of Concentration, Composition, and Osmotic Pressure of Nutrient Solution on the Occurrence and Development of Cucumber Downy Mildew.

2000 ◽  
Vol 69 (3) ◽  
pp. 346-352
Author(s):  
Shoko Tanaka ◽  
Tadashi Ito ◽  
Yasufumi Ochi ◽  
Yasukatsu Someya ◽  
Tetsuo Hirabayashi
2002 ◽  
Vol 71 (3) ◽  
pp. 405-410
Author(s):  
Shoko Tanaka ◽  
Tadashi Ito ◽  
Yasufumi Ochi ◽  
Yasukatsu Someya ◽  
Tetsuo Hirabayashi

2007 ◽  
Vol 50 (5) ◽  
pp. 1261-1268 ◽  
Author(s):  
Xinting Yang ◽  
Ming Li ◽  
Chunjiang Zhao ◽  
Zheng Zhang ◽  
Yanlin Hou

Plant Disease ◽  
2017 ◽  
Vol 101 (4) ◽  
pp. 562-567 ◽  
Author(s):  
Shiling Sun ◽  
Sen Lian ◽  
Shulian Feng ◽  
Xiangli Dong ◽  
Caixian Wang ◽  
...  

Cucumber downy mildew, caused by Pseudoperonospora cubensis, is a worldwide disease that causes severe damage to cucumber production. The effects of temperature and moisture on sporulation and infection by P. cubensis were investigated by inoculating cucumber (‘85F12’) cotyledons with sporangia and examining the sporangia produced on the inoculated cotyledons under artificially controlled environments. The result showed that the temperature required for sporangium infection by P. cubensis and sporulation of the downy mildew lesions occurred at 5 to 30°C. The optimal temperature estimated by the fitted model was 18.8°C for sporangium infection and 16.2°C for downy mildew lesion sporulation. The pathogen formed plenty of sporangia when disease cotyledons were wetted or in the environment with relative humidity = 100%. The downy mildew lesions produced only a few sporangia when placed in the environment with relative humidity = 90%. The inoculated cotyledons, which incubated for 5 days at about 20°C in a dry greenhouse, began to form sporangia 4 h after being wetted when incubated in darkness. The quantity of sporangia produced on the downy mildew lesions increased with extension of incubating period (within 12 h), and the relationship between produced sporangia and the incubation period at 15, 20, and 25°C can be described by three exponential models. The observed minimum wetness durations (MWD) required for sporangia to complete the infection process and cause downy mildew were 12, 4, 2.5, 1, 1, and 6 h for 5, 10, 15, 20, 25, and 30°C, respectively. The effect of temperature and wetness duration on infection by sporangia of P. cubensis can be described by the modified Weibull model. The shortest MWD was 0.45 h, about 27 min, estimated by model. The experimental data and models will be helpful in the development of forecasting models and effective control systems for cucumber downy mildew.


2020 ◽  
Vol 11 ◽  
pp. 108-121
Author(s):  
Chunyang Yao ◽  
Xiaodong Zhang ◽  
Hanping Mao ◽  
Hongyan Gao ◽  
Qinglin Li

Downy mildew, a kind of cucumber disease with a high spread rate and harmfulness that is more common in the world, has a great influence on the yield of cucumbers. The rapid identification of its symptoms and the rapid classification of the post-disease characters are of great significance to the rapid diagnosis of cucumber frost mold and the proper treatment of medicine after the disease. In order to quickly and accurately classify the occurrence and the degree of cucumber downy mildew, a rapid diagnosis and classification method of cucumber downy mildew based on visible light - high spectral imaging technology was proposed in this paper. In addition, the stepwise regression method and PCA were used to reduce and extract the feature information of sensitive bands. Two kinds of acquired feature information are used as the input of the model to construct the disease degree classification detection model of the SVM classification model. The model based on the stepwise regression method is used to classify and identify downy mildew and normal leaves. In this model, the accuracy of the Sigmoid kernel function classification test is the highest, reaching 95.00%, and the recognition rate of different degrees of cucumber downy mildew disease leaves as high as 93.88, which has a high classification detection accuracy. The results show that the rapid diagnosis and classification of cucumber downy mildew can be realized by using the visible light spectral imaging system combined with the automatic classification model of SVM, which provides a new method and reference for solving the problem of cucumber downy mildew in time.


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