Boris X. Camiletti

This paper uses high-resolution satellite imagery and machine learning to map Red Crown Rot in soybean fields, achieving high accuracy in detecting affected canopies.

This paper develops and validates a high-resolution melting (HRM) assay for specific detection of Calonectria ilicicola in soybean, showing high specificity and sensitivity in both lab and field samples.

This paper develops and validates methods to assess red crown rot severity in soybean using root imaging and visual scales, improving accuracy and agreement across environments.

The paper quantifies yield losses from peanut smut in Argentina using field studies and finds consistent damage coefficients across incidence levels.