Weiqi Luo, PhD (he/him/his)
Principal Research Scholar
North Carolina State University
Fort Pierce, Florida, United States
Kendall Johnson
UPL
Wenatchee, Washington, United States
Clive H. Bock, PhD
Research Plant Pathologist
USDA ARS, U.S. Horticulture Research Laboratory
Ft. Pierce, Florida, United States
Phillip M. Brannen, PhD
Professor
University of Georgia
Athens, Georgia, United States
Ted Cottrell
USDA
Byron, Georgia, United States
Paul Severns, PhD
Assistant Professor of Plant Disease Epidemiology
Department of Plant Pathology, University of Georgia
Athens, Georgia, United States
Phony peach disease (PPD), caused by Xylella fastidiosa subsp. multiplex (Xfm) is a threat to peach orchards in Georgia and elsewhere in the Southeast (U.S.). Early and accurate detection allows effective disease management, and visual assessment is the primary detection method used. We evaluated the accuracy of visual PPD assessment and factors influencing rater performance, symptom detection reliability, and optimal survey deployment strategies. Using a random forest model, internode length was the most reliable symptom for PPD identification in two peach varieties, when compared to other physical traits such as canopy flatness and shape. For PPD surveys, simulation results suggested that deploying two experienced raters, as opposed to more or less, provided the best detection accuracy. Principal component analysis suggested that rater experience significantly improved agreement with qPCR. Lastly, PPD-infected trees, through PCR verification and visual identification, exhibited higher mortality rates than PPD-negative trees, reinforcing the need for early detection and removal to limit disease spread. These findings underscore the importance of strategic rater deployment and targeted symptom selection.