scholarly journals Expert system for corn plant disease diagnosis with the breadth-first search method

Author(s):  
A T Sumpala ◽  
R Rasyid
F1000Research ◽  
2018 ◽  
Vol 7 ◽  
pp. 1902
Author(s):  
Fahrul Agus ◽  
Muh. Ihsan ◽  
Dyna Marisa Khairina ◽  
Krishna Purnawan Candra

One of the factors causing rice production disturbance in Indonesia is the lack of knowledge of farmers on early symptoms of rice plant diseases. These diseases are increasingly rampant because of the lack of experts. This study aimed to overcome this problem by providing an Expert System that helps farmers to make early diagnosis of rice plant diseases. Data of rice plant pests and diseases in 2016 were taken from Samarinda, East Kalimantan, Indonesia using an in-depth survey, and rice experts from the Department of Food Crops and Horticulture of East Kalimantan Province were recruited for the project. The Expert System for Rice Plant Disease Diagnosis, ESforRPD2, was developed based on the pest and disease experiences of the rice experts, and uses a Waterfall Paradigm and Unified Modelling Language. This Expert System can detect 48 symptoms and 8 types of diseases of rice plants from 16 data tests with an accuracy of 87.5%. ESforRPD2 is available in Indonesian at: http://esforrpd2.blog.unmul.ac.id


F1000Research ◽  
2019 ◽  
Vol 7 ◽  
pp. 1902
Author(s):  
Fahrul Agus ◽  
Muh. Ihsan ◽  
Dyna Marisa Khairina ◽  
Krishna Purnawan Candra

One of the factors causing rice production disturbance in Indonesia is that farmers lack knowledge of early symptoms of rice plant diseases. These diseases are increasingly rampant because of the lack of experts. This study aimed to overcome this problem by providing an Expert System that helps farmers to make an early diagnosis of rice plant diseases. Data of rice plant pests and diseases in 2016 were taken from Samarinda, East Kalimantan, Indonesia using an in-depth survey, and rice experts from the Department of Food Crops and Horticulture of East Kalimantan Province were recruited for the project. The Expert System for Rice Plant Disease Diagnosis, ESforRPD2, was developed based on the pest and disease experiences of the rice experts and uses a Waterfall Paradigm and Unified Modeling Language. This Expert System can detect 48 symptoms and 8 types of diseases of rice plants from 16 data tests with a sensitivity of 87.5%. ESforRPD2 is available in Indonesian at http://esforrpd2.blog.unmul.ac.id


2010 ◽  
Vol 3 (4) ◽  
pp. 269-276 ◽  
Author(s):  
S.S. Abu-Naser ◽  
K.A. Kashkash ◽  
M. Fayyad

2008 ◽  
Vol 1 (2) ◽  
pp. 78-85 ◽  
Author(s):  
S.S. Abu-Naser ◽  
K.A. Kashkash ◽  
M. Fayyad

Author(s):  
Karen K. Baker ◽  
David L. Roberts

Plant disease diagnosis is most often accomplished by examination of symptoms and observation or isolation of causal organisms. Occasionally, diseases of unknown etiology occur and are difficult or impossible to accurately diagnose by the usual means. In 1980, such a disease was observed on Agrostis palustris Huds. c.v. Toronto (creeping bentgrass) putting greens at the Butler National Golf Course in Oak Brook, IL.The wilting symptoms of the disease and the irregular nature of its spread through affected areas suggested that an infectious agent was involved. However, normal isolation procedures did not yield any organism known to infect turf grass. TEM was employed in order to aid in the possible diagnosis of the disease.Crown, root and leaf tissue of both infected and symptomless plants were fixed in cold 5% glutaraldehyde in 0.1 M phosphate buffer, post-fixed in buffered 1% osmium tetroxide, dehydrated in ethanol and embedded in a 1:1 mixture of Spurrs and epon-araldite epoxy resins.


Nanoagronomy ◽  
2020 ◽  
pp. 101-123 ◽  
Author(s):  
Afifa Younas ◽  
Zubaida Yousaf ◽  
Madiha Rashid ◽  
Nadia Riaz ◽  
Sajid Fiaz ◽  
...  

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