Abstract: Worldwide, the monitoring of pests and diseases plays a fundamental role in the agricultural sustainability; making necessary the development of new tools for early pest detection. In this sense, we present a software application for detecting damage in tobacco (Nicotiana tabacum L.) leaves caused by the fungus of blue mold (Peronospora tabacina Adam). This software application processes tobacco leaves images using a pat-tern recognition technique known as Artificial Neural Network. For the training and testing stages, a total of 40 images of tobacco leaves were used. The experimentation carried out shows that the developed model has accuracy higher than 97% and there is no significant difference with a visual analysis carried out by experts in tobacco crop.

Himer Avila-George, Topacio Valdez-Morones, Humberto P´erez-Espinosa, Brenda Acevedo-Ju´arez and Wilson Castro. “Using Artificial Neural Networks for Detecting Damage on Tobacco Leaves Caused by Blue Mold”. International Journal of Advanced Computer Science and Applications (IJACSA) 9.8 (2018). http://dx.doi.org/10.14569/IJACSA.2018.090873

@article{Avila-George2018,
title = {Using Artificial Neural Networks for Detecting Damage on Tobacco Leaves Caused by Blue Mold},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090873},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090873},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {8},
author = {Himer Avila-George and Topacio Valdez-Morones and Humberto P´erez-Espinosa and Brenda Acevedo-Ju´arez and Wilson Castro}
}