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Divergent abiotic spectral pathways unravel pathogen stress signals across species

Author

Listed:
  • P. J. Zarco-Tejada

    (University of Melbourne
    Instituto de Agricultura Sostenible (IAS), Consejo Superior de Investigaciones Científicas (CSIC))

  • T. Poblete

    (University of Melbourne)

  • C. Camino

    (European Commission, Joint Research Centre (JRC))

  • V. Gonzalez-Dugo

    (Instituto de Agricultura Sostenible (IAS), Consejo Superior de Investigaciones Científicas (CSIC))

  • R. Calderon

    (School of Integrative Plant Science, Cornell AgriTech, Cornell University)

  • A. Hornero

    (Instituto de Agricultura Sostenible (IAS), Consejo Superior de Investigaciones Científicas (CSIC)
    Swansea University)

  • R. Hernandez-Clemente

    (Swansea University)

  • M. Román-Écija

    (Instituto de Agricultura Sostenible (IAS), Consejo Superior de Investigaciones Científicas (CSIC))

  • M. P. Velasco-Amo

    (Instituto de Agricultura Sostenible (IAS), Consejo Superior de Investigaciones Científicas (CSIC))

  • B. B. Landa

    (Instituto de Agricultura Sostenible (IAS), Consejo Superior de Investigaciones Científicas (CSIC))

  • P. S. A. Beck

    (European Commission, Joint Research Centre (JRC))

  • M. Saponari

    (CNR, Istituto per la Protezione Sostenibile delle Piante)

  • D. Boscia

    (CNR, Istituto per la Protezione Sostenibile delle Piante)

  • J. A. Navas-Cortes

    (Instituto de Agricultura Sostenible (IAS), Consejo Superior de Investigaciones Científicas (CSIC))

Abstract

Plant pathogens pose increasing threats to global food security, causing yield losses that exceed 30% in food-deficit regions. Xylella fastidiosa (Xf) represents the major transboundary plant pest and one of the world’s most damaging pathogens in terms of socioeconomic impact. Spectral screening methods are critical to detect non-visual symptoms of early infection and prevent spread. However, the subtle pathogen-induced physiological alterations that are spectrally detectable are entangled with the dynamics of abiotic stresses. Here, using airborne spectroscopy and thermal scanning of areas covering more than one million trees of different species, infections and water stress levels, we reveal the existence of divergent pathogen- and host-specific spectral pathways that can disentangle biotic-induced symptoms. We demonstrate that uncoupling this biotic–abiotic spectral dynamics diminishes the uncertainty in the Xf detection to below 6% across different hosts. Assessing these deviating pathways against another harmful vascular pathogen that produces analogous symptoms, Verticillium dahliae, the divergent routes remained pathogen- and host-specific, revealing detection accuracies exceeding 92% across pathosystems. These urgently needed hyperspectral methods advance early detection of devastating pathogens to reduce the billions in crop losses worldwide.

Suggested Citation

  • P. J. Zarco-Tejada & T. Poblete & C. Camino & V. Gonzalez-Dugo & R. Calderon & A. Hornero & R. Hernandez-Clemente & M. Román-Écija & M. P. Velasco-Amo & B. B. Landa & P. S. A. Beck & M. Saponari & D. , 2021. "Divergent abiotic spectral pathways unravel pathogen stress signals across species," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
  • Handle: RePEc:nat:natcom:v:12:y:2021:i:1:d:10.1038_s41467-021-26335-3
    DOI: 10.1038/s41467-021-26335-3
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    References listed on IDEAS

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    1. Matthew C. Fisher & Daniel. A. Henk & Cheryl J. Briggs & John S. Brownstein & Lawrence C. Madoff & Sarah L. McCraw & Sarah J. Gurr, 2012. "Emerging fungal threats to animal, plant and ecosystem health," Nature, Nature, vol. 484(7393), pages 186-194, April.
    2. Kevin Schneider & Wopke van der Werf & Martina Cendoya & Monique Mourits & Juan A. Navas-Cortés & Antonio Vicent & Alfons Oude Lansink, 2020. "Impact of Xylella fastidiosa subspecies pauca in European olives," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 117(17), pages 9250-9259, April.
    3. Karatzoglou, Alexandros & Smola, Alexandros & Hornik, Kurt & Zeileis, Achim, 2004. "kernlab - An S4 Package for Kernel Methods in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 11(i09).
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    Cited by:

    1. Zarco-Tejada, Pablo, 2021. "Advanced monitoring techniques," 2021: Food and Nutrition Security - The Biosecurity, Trade, Health Nexus, 13-14 December 2021 320490, Crawford Fund.

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