An open access repository of images on plant health to enable the development of mobile disease diagnostics

TLDR

Human societies must boost food production by about 70 % by 2050, yet infectious diseases currently cut yields by an average of 40 %, and the widespread availability of smartphones offers a promising avenue for mobile disease diagnostics. The authors release more than 50 000 expertly curated images of healthy and infected crop leaves via the PlantVillage platform. The dataset and platform are described, providing a publicly accessible repository for machine‑learning and crowdsourcing applications. These images initiate an ongoing crowdsourcing effort to empower computer‑vision solutions that aim to reduce crop yield losses caused by plant diseases.

Abstract

Human society needs to increase food production by an estimated 70% by 2050 to feed an expected population size that is predicted to be over 9 billion people. Currently, infectious diseases reduce the potential yield by an average of 40% with many farmers in the developing world experiencing yield losses as high as 100%. The widespread distribution of smartphones among crop growers around the world with an expected 5 billion smartphones by 2020 offers the potential of turning the smartphone into a valuable tool for diverse communities growing food. One potential application is the development of mobile disease diagnostics through machine learning and crowdsourcing. Here we announce the release of over 50,000 expertly curated images on healthy and infected leaves of crops plants through the existing online platform PlantVillage. We describe both the data and the platform. These data are the beginning of an on-going, crowdsourcing effort to enable computer vision approaches to help solve the problem of yield losses in crop plants due to infectious diseases.