Cross and Drewry Publish Article on Remote Diagnosis of Wheat Stripe Rust Progression

Ohio State University Department of Food, Agricultural and Biological Engineering (FABE) Environmental Sciences Graduate Program (ESGP) student James Cross and advisor Darren Drewry recently published an article in the Frontiers in Plant Science journal last week. 

The article, titled "Non-invasive diagnosis of wheat stripe rust progression using hyperspectral reflectance," examines new technology used to diagnose a severe threat to wheat production. 

Wheat stripe rust (WSR) poses a significant threat to global wheat production, making the development of rust-resistant varieties essential. This study showcases the effectiveness of visible and shortwave infrared reflectance spectroscopy for high-throughput classification of WSR severity. 

Utilizing random forest models based on leaf-level and canopy-level hyperspectral data, researchers achieved classification accuracies of 45-52%, which improved to 79-96% with off-by-one scoring. The canopy-level model outperformed the leaf-level models, highlighting its potential for field-scale monitoring. 

Additionally, the study employed dimensionality reduction techniques to simplify model complexity while maintaining high classification skill, demonstrating that machine learning and selective waveband usage can enhance precision in monitoring and managing WSR, aiding in the breeding of resilient wheat varieties.

The Frontiers in Plant Science journal, the most cited plant science journal, advances the understanding of plant biology for sustainable food security, functional ecosystems and human health.