Foliar diseases take a toll on maize (corn) producers in the US and around the world, decreasing yields and provoking applications of costly, often hazardous fungicides. Our lab has studied several bacterial and fungal diseases, with a focus on northern leaf blight (NLB).

Our research has shown how different resistance loci affect different stages of pathogenesis, found pleiotropic loci for multiple disease resistance in several populations, and characterized a loss-of-function mutation that actually increases resistance to two diseases.

Current research in these areas seeks to identify the genes underlying quantitative trait loci (QTL) by fine mapping and association studies; to understand the roles of specific genes and alleles in resistance by analysis of maize mutants and transgenic lines; and to explore the transcriptional and physical changes during the transition from biotrophy to necrotrophy.


Certain ear rot pathogens of maize can produce mycotoxins, toxic compounds damaging to human and animal health. Even in small doses, these compounds can have grave effects: growth stunting, cancer, neural tube defects, increased mortality, and death. Mycotoxins may contribute substantially to the global burden of child stunting by harming the gut lining.

Our work focuses on two classes of mycotoxins: fumonisins (produced by Fusarium verticillioides) and aflatoxins (produced by Aspergillus flavus). The mechanisms of resistance to these ear rots are complex, and the visible severity of infection is often poorly correlated to mycotoxin levels.

To date, we have developed a rapid screening protocol for fungal biomass in infected grain, identified traits that reduce aflatoxin accumulation, and located a promising QTL for resistance to multiple ear rots. Ongoing research seeks to develop faster, cheaper screening methods and connect QTL back to the underlying chemical pathways of infection.


While severe mycotoxin contamination can kill dozens, there is growing evidence that constant low-level exposure to mycotoxins can cause severe health issues, issues that may go unnoticed and unchecked.

Our survey work first documented the dangerous levels of fumonisin in the food supply of eastern and western Kenya and confirmed that traditional visual sorting did not reduce aflatoxin to a safe level.

Current research is aimed both at characterizing the problem and finding effective interventions. The Tata-Cornell Initiative is funding PhD student Anthony Wenndt’s comprehensive surveys across rural India to understand the social, agronomic, and economic drivers of mycotoxin exposure. We recently received a Gates Foundation planning grant to develop intervention strategies to reduce mycotoxin exposure and mitigate child stunting in Tanzania.


For farmers, early detection of disease outbreaks can mean the difference between a successful harvest and a devastated field. For breeders and geneticists, high-throughput methods can evaluate many traits rapidly and reliably.

Together with the Gore Lab at Cornell and the Lipson Lab at Columbia University, we are harnessing artificial neural networks to detect, classify, and quantify plant diseases. These algorithms are trained by human experts.

This research is supported by NSF Award 1527232, “Deep Learning Unmanned Aircraft Systems for High-Throughput Agricultural Disease Phenotyping”