Using Artificial Neural Networks for Detecting Damage on Tobacco Leaves Caused by Blue Mold

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.

@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},
  volume    = {9},
  number    = {8},
  year      = {2018},
  publisher = {The Science and Information Organization},
  author    = {Himer Avila-George and Topacio Valdez-Morones and Humberto P´erez-Espinosa and Brenda Acevedo-Ju´arez and Wilson Castro},
  doi       = {10.14569/IJACSA.2018.090873},
  url       = {https://doi.org/10.14569/IJACSA.2018.090873}
}