ORIGINAL RESEARCH article
Front. For. Glob. Change
Sec. Pests, Pathogens and Invasions
Volume 8 - 2025 | doi: 10.3389/ffgc.2025.1588428
Point-of-care diagnostics and resistance phenotyping to combat ash dieback
Provisionally accepted
- 1The Ohio State University, Columbus, Ohio, United States
- 2Forest Service, United States Department of Agriculture, Hamden, Connecticut, United States
- 3Southern Swedish Forest Research Centre, Faculty of Forest Sciences, Swedish University of Agricultural Sciences, Alnarp, Sweden
- 4Forestry Research Institute of Sweden, Uppsala, Uppsala, Sweden
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Non-destructive tree phenotyping for resistance screening and early, presymptomatic disease detection figure prominently among the most important practical limitations inherent in forest health management. The need for point-of-care tools is particularly acute for managing diseases caused by non-native pathogens, often resulting in difficult-to-control biological invasions. One such case is represented by ash dieback in Europe, caused by Hymenoscyphus fraxineus, which has led Sweden to red-list its main host, European ash (Fraxinus excelsior). We evaluated the use of near-infrared (NIR) spectroscopy and machine learning for detection of presymptomatic infections by H. fraxineus and identification of disease-resistance European ash accessions. Here, we show that presymptomatic infected trees can be distinguished from pathogen-free trees with a testing error rate of 0.161 in a controlled inoculation experiment. We also show that the same approach can be used to identify disease-resistant European ash accessions based on data from two independent, multiyear clonal trials, with a testing error rate of 0.155. These results confirm that NIR spectroscopy combined with machine learning is sensitive enough for early disease detection and resistance screening in this system. This is consistent with prior findings in other tree pathosystems and suggests that this approach could be developed into an operational tool to facilitate the management of biological invasions of forest environments by non-native pathogens, including habitat restoration with resistant germplasm.
Keywords: Ash dieback, Disease Resistance, Early detection, European ash, Non-destructive phenotyping
Received: 05 Mar 2025; Accepted: 28 May 2025.
Copyright: © 2025 Bonello, Conrad, Sadikovic, Liziniewicz and Cleary. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Pierluigi (Enrico) Bonello, The Ohio State University, Columbus, 43210, Ohio, United States
Michelle Cleary, Southern Swedish Forest Research Centre, Faculty of Forest Sciences, Swedish University of Agricultural Sciences, Alnarp, Sweden
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