Identification and characterization of Septoria steviae as the causal agent of Septoria leaf spot disease of stevia in North Carolina

Mycologia ◽  
2019 ◽  
Vol 111 (3) ◽  
pp. 456-465 ◽  
Author(s):  
Alyssa M. Koehler ◽  
Maximo T. Larkin ◽  
Layne W. Rogers ◽  
Ignazio Carbone ◽  
Marc A. Cubeta ◽  
...  
2018 ◽  
Vol 10 (3) ◽  
pp. 1015
Author(s):  
S. M. ZIA HASAN ◽  
MD. FIROSE HOSSAIN ◽  
ZANNATI FERDOUS ZAOTI ◽  
MD. SAROAR JAHAN ◽  
MD. FARUK HASAN ◽  
...  

2011 ◽  
Vol 40 (3) ◽  
pp. 246-259 ◽  
Author(s):  
Shan-Hai Lin ◽  
Si-Liang Huang ◽  
Qi-Qin Li ◽  
Chun-Jin Hu ◽  
Gang Fu ◽  
...  

2015 ◽  
Vol 164 (6) ◽  
pp. 372-377 ◽  
Author(s):  
Xinxin Ge ◽  
Rujun Zhou ◽  
Yue Yuan ◽  
Haijiao Xu ◽  
Junfan Fu ◽  
...  

2016 ◽  
Vol 10 (11) ◽  
pp. 238-245 ◽  
Author(s):  
Amos Chilagane Luseko ◽  
Nchimbi-Msolla Susan ◽  
Mbogo Kusolwa Paul ◽  
Gabriel Porch Timothy ◽  
Miryam Serrato Diaz Luz ◽  
...  

2021 ◽  
Vol 5 (1) ◽  
pp. 107-113
Author(s):  
Kahlil Muchtar ◽  
Chairuman ◽  
Yudha Nurdin ◽  
Afdhal Afdhal

much needed to meet the needs of both industry and households. However, tomato plants still require serious handling in increasing the yields. Data from the Central Bureau of Statistics shows that the number of tomatoes produced is not in accordance with a large number of market demands, resulting from the decrease of tomato yields. One of the obstacles in increasing tomato production is that the crops are attacked by septoria leaf spot disease due to the fungus or the fungus Septoria Lycopersici Speg. Most farmers have limited knowledge of the early symptoms, which are not obvious, and also facing difficulty in detecting this disease earlier. The problem has been causing disadvantages such as crop failure or plant death. Based on this problem, a study will be conducted with the aim of designing a tool that can be used to detect septoria leaf spot disease based on deep learning using the Convolutional Neural Network (ConvNets or CNN) model, where an algorithm that resembles human nerves is one of the supervised learning and widely used for solving linear and non-linear problems. In addition, the researcher used the Raspberry Pi as a microcontroller and used the Intel Movidius Neural Computing Stick (NCS) which functions to speed up the computing process so that the detection process is easier because of its portable, fast and accurate nature. The average accuracy rate is 95.89% with detection accuracy between 84.22% to 100%.  


Author(s):  
D. W. Minter

Abstract A description is provided for Lophomerum ponticum. Information is included on the disease caused by the organism, its transmission, geographical distribution, and hosts. HOSTS: Rhododendron ponticum. DISEASE: Leaf spot of rhododendron. In general Lophomerum ponticum appears to be saprophytic. Its ascocarps are usually not produced until the leaves have senesced, become detached and fallen to the litter. Occasionally, however, ascocarps can be found on browned regions of otherwise green leaves, and it seems possible, therefore, that the species is facultatively parasitic. It is important to distinguish this species from Lophodermium vagulum (CMI Descriptions 789) which is the causal agent of a leaf spot disease of chinese rhododendrons, but which does not occur on R. ponticum. GEOGRAPHICAL DISTRIBUTION: Europe (Great Britain), probably much more widespread. TRANSMISSION: By air-borne ascospores in wet or humid weather.


2009 ◽  
Vol 124 (4) ◽  
pp. 577-583 ◽  
Author(s):  
Barbara Meisel ◽  
Jeanne Korsman ◽  
Frederik J. Kloppers ◽  
Dave K. Berger

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