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ARS Home » Southeast Area » Byron, Georgia » Fruit and Tree Nut Research » Research » Publications at this Location » Publication #393158

Research Project: Healthy, Sustainable Pecan Nut Production

Location: Fruit and Tree Nut Research

Title: Evaluating the accuracy of visual estimation of the incidence of phony peach disease (caused by Xylella fastidiosa)

item JOHNSON, KENDALL - University Of Georgia
item Bock, Clive
item BRANNEN, PHILLIP - University Of Georgia

Submitted to: American Phytopathological Society Annual Meeting
Publication Type: Abstract Only
Publication Acceptance Date: 5/24/2022
Publication Date: 11/1/2022
Citation: Johnson, K.A., Bock, C.H., Brannen, P. 2022. Evaluating the accuracy of visual estimation of the incidence of phony peach disease (caused by Xylella fastidiosa). American Phytopathological Society Annual Meeting. Vol 112:S3.71.

Interpretive Summary:

Technical Abstract: Peach (Prunus persica) is an economically important fruit crop in Georgia. Phony peach disease (PPD) is a reemerging disease caused by Xylella fastidiosa (Xf) subsp. multiplex in central and southern Georgia. Early, accurate detection and rapid removal of symptomatic trees are crucial to effective disease management. Currently, producers rely solely on visual identification of symptoms to confirm PPD, which can be ambiguous if early in development, and may be confused with other causes. In this experiment, we compared visual assessment to qPCR for detecting Xf in an orchard of 263 peach trees in 2019 and 2020. Root samples were collected from each tree for detection by qPCR. With no prior knowledge of qPCR results, each tree was subject to visual assessment by a cohort of 5 experienced and 5 inexperienced raters. Experienced raters were familiar with symptoms of PPD, and inexperienced raters were provided with instruction. Accuracy of estimation for inexperienced raters ranged from 0.685 to 0.898 in 2019 and from 0.765 to 0.919 in 2020. For experienced raters, accuracy ranged from 0.846 to 0.910 in 2019 and from 0.878 to 0.929 in 2020. No significant difference was observed between years (p = 0.4) or between experienced and inexperienced rater groups in 2019 (p = 0.08), but there was a significant difference between rater groups in 2020 (p = 0.008). Visual identification of PPD has variable accuracy and in some cases may benefit from experience, but further research is needed to develop accurate methods of detection to aid management of PPD as both false positives and false negatives have a cost.