Bioinformatics and Image Processing—Detection of Plant Diseases

Optimization techniques on fuzzy inference systems to detect Xanthomonas campestris disease

“…Bearing in mind that "currently, disease transmission is easier and new ones might appear in places they have never been detected before," [1] great economic losses based on the belief that a crop looks is its most important quality sign [2] are common; furthermore, the accelerated increase of the population does not favours any slow down in the agronomical processes as farmers must keep an steady production rythm to satisfy the demand [3]. Therefore, to reduce the amount of poor looking and poor quality crops it is of great importance to detect diseases caused by bacteria, like the Xanthomonas campestris, in their early stages to avoid evident sequels [4] on the final product [5]. That need for constant monitoring can be reduced with the usage of digital image processing (DIP) [6] to identify the most relevant characteristics on the grown plant; Convolutional neural networks [7] are usually used in concordance with DIP due to its capacity to evaluate multiple depth layers and filters that show precise outcomes, however, if the conformation of the model is unknown its outcome loses significance.…”