Supervised Training of a Simple Digital Assistant for a Free Crop Clinic

Abstract

Family farming represents a critical segment of Brazilian agriculture, involving more than 5 million properties and generating 74% of rural jobs in the country. Yield losses caused by crop diseases and pests can be devastating for small-scale producers. However, successful disease control requires correct identification, which challenges smallholders, who often lack technical assistance. The present work proposes a system that detects disease symptoms in images of plant leaves to assist phytopathology experts. The objective is to decrease the experts’ workload and enable consulting services for free or at nominal cost. In addition, the required digital communication channel will promote the formation of a caring community ready to offer unpaid advice for family farmers. The machine learning and refinement of the assistance system are described in detail. The developed classification system achieves a recall value of 95%.