Julius Lucks of Northwestern University in the U.S. is developing a low-cost field test that can detect multiple plant pathogens and produce simple visual outputs for farmers in low-income countries to better monitor their crops. Current diagnostic field tests only detect one disease and are generally costly and difficult to use. In Phase I, they developed a sensitive, multiplexed assay that can detect multiple pathogens using biosensors and produce colorimetric outputs, and performed successful field-testing in several countries. In Phase II, they will generate a flexible diagnostic platform that uses computational models to rapidly optimize and formulate tests for a range of plant pathogens by combining nucleic acid sequence-based amplification with CRISPR Cas13 detection. They will also optimize cost, usability, and stability, and test performance in the laboratory and in the field in New Zealand, Kenya, and Uganda.
More information about Tools and Technologies for Broad-Scale Disease Surveillance of Crop Plants in Low-Income Countries (Round 21)