Pierluigi Bonello of Ohio State University in the U.S. will develop a surveillance system for crops using unmanned aerial vehicles (drones) to position sensors to help diagnose plant diseases in low-income countries. Plant diseases are usually identified first by the farmers or human scouts and then confirmed by laboratory testing. This process is inefficient and requires resources often unavailable in low-income countries, calling for alternative approaches. It is known that when a plant becomes infected, it produces specific chemicals. In addition, functional chemical groups in biological samples are known to vibrate in predictable ways after absorbing light. They will test whether this information can be exploited for the rapid and widespread detection of two plant diseases, rice blast and maize dwarf mosaic, by vibrational spectroscopy that could be positioned inside crop canopies by drones. Rice and maize grown in greenhouses and fields in the U.S. will be infected, and they will develop statistical methods to evaluate whether handheld spectrometers can distinguish between infected and uninfected plants. This technology could ultimately allow crop managers to control the spread of a disease even before plants show visual symptoms.
More information about Tools and Technologies for Broad-Scale Disease Surveillance of Crop Plants in Low-Income Countries (Round 21)