Her research project will build a multispectral drone that will enable early detection of infection in cassava plants in Côte d'Ivoire. Cassava is the second most important food crop in Côte d'Ivoire, but cassava production is limited by many bacterial diseases which are estimated to reduce production by as much as 80%. Early diagnosis of infection is necessary to prevent production loss. Existing techniques use a smartphone app requiring an image of a leaf from each plant in a given field; for a large area, this work is tedious, and usually left to women, who are in the majority in all links of the cassava value chain. This project will construct a drone that can map fields, capture multispectral images, and collect leaf diffuse reflectance spectra. Neural network-based analysis will predict infection only 24 hours after plant infection, leading to earlier diagnosis of cassava diseases and a lightened burden on farmers.