4.6 Article

Previsual symptoms of Xylella fastidiosa infection revealed in spectral plant-trait alterations

Journal

NATURE PLANTS
Volume 4, Issue 7, Pages 432-439

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41477-018-0189-7

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Funding

  1. European Union's Horizon 2020 research and innovation programme through grant agreement POnTE [635646]
  2. European Union's Horizon 2020 research and innovation programme through grant agreement XF-ACTORS [727987]
  3. NERC [nceo020002] Funding Source: UKRI

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Plant pathogens cause significant losses to agricultural yields and increasingly threaten food security(1), ecosystem integrity and societies in general(2-5). Xylella fastidiosa is one of the most dangerous plant bacteria worldwide, causing several diseases with profound impacts on agriculture and the environment(6). Primarily occurring in the Americas, its recent discovery in Asia and Europe demonstrates that X. fastidiosa's geographic range has broadened considerably, positioning it as a reemerging global threat that has caused socioeconomic and cultural damage(7,8). X. fastidiosa can infect more than 350 plant species worldwide(9), and early detection is critical for its eradications(8). In this article, we show that changes in plant functional traits retrieved from airborne imaging spectroscopy and thermography can reveal X. fastidiosa infection in olive trees before symptoms are visible. We obtained accuracies of disease detection, confirmed by quantitative polymerase chain reaction, exceeding 80% when high-resolution fluorescence quantified by three-dimensional simulations and thermal stress indicators were coupled with photosynthetic traits sensitive to rapid pigment dynamics and degradation. Moreover, we found that the visually asymptomatic trees originally scored as affected by spectral plant-trait alterations, developed X. fastidiosa symptoms at almost double the rate of the asymptomatic trees classified as not affected by remote sensing. We demonstrate that spectral plant-trait alterations caused by X. fastidiosa infection are detectable previsually at the landscape scale, a critical requirement to help eradicate some of the most devastating plant diseases worldwide.

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