Evaluation the accuracy of a smartphone-based artificial intelligence system, PlantVillage Nuru, in identifying the viral diseases of cassava

Abstract

Premise of the studyNuru is an artificial intelligence system for diagnosis of plant diseases and pests developed as a public good by PlantVillage (Penn State University), FAO, IITA and CIMMYT. It provides a simple, inexpensive and robust means of conducting in-field diagnosis without requiring internet connection and provides real-time results and advice. The present work evaluates the effectiveness of Nuru as an in-field diagnostic tool by comparing the diagnosis capability of Nuru to that of cassava experts (researchers trained on cassava pests and diseases), agricultural extension agents and farmers. MethodsThe diagnosis capability of Nuru and that of the assessed individuals was determined by inspecting cassava plants in-field and by using the cassava symptom recognition assessment tool (CaSRAT) to score images of cassava leaves. ResultsNurus accuracy for symptom recognition when using six leaves (74 - 88%, depending on the condition) was similar to that of experts, 1.5-times higher than agricultural extension agents and two-times higher than farmers. DiscussionThese findings suggests that Nuru can be an effective tool for in-field diagnosis of cassava diseases and has a potential of being a quick and cost-effective means of disseminating knowledge from researchers to agricultural extension agents and farmers.