Plant Disease Phenotype Identification and Classification via Deep Learning

Abstract

Humans face global food shortages in the upcoming years, and we must maximize the yield of common crops to feed the growing population. Plant diseases are a major threat to small and large farm owners alike. These diseases reduce the potential yield of the crops, and in some severe but frequent cases, up to 100%. The identification of these diseases remains a challenge despite government efforts to educate farmers. There is a need for identification of these diseases early on so that they can be treated quickly. The pervasiveness of smartphones among farmers around the world offers the potential of adopting recent technological developments in computer science to develop a solution that can help in plant disease phenotype identification. This rich ecosystem of diverse communities can be a great advantage to crop heath and consequently the human race. To utilize the potential of these technologies we use a dataset curated by PlantVillage that contains over 50,000 images of 14 different crops that can be utilized to perform disease identification using modern deep learning algorithms. The models can then be employed by smartphones to identify the diseases and recommend possible treatments