Literature DB >> 29942047

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

P J Zarco-Tejada1, C Camino2, P S A Beck3, R Calderon2, A Hornero2,4, R Hernández-Clemente4, T Kattenborn5, M Montes-Borrego2, L Susca6, M Morelli7, V Gonzalez-Dugo2, P R J North4, B B Landa2, D Boscia7, M Saponari7, J A Navas-Cortes2.   

Abstract

Plant pathogens cause significant losses to agricultural yields and increasingly threaten food security1, ecosystem integrity and societies in general2-5. Xylella fastidiosa is one of the most dangerous plant bacteria worldwide, causing several diseases with profound impacts on agriculture and the environment6. 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 damage7,8. X. fastidiosa can infect more than 350 plant species worldwide9, and early detection is critical for its eradication8. 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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Year:  2018        PMID: 29942047     DOI: 10.1038/s41477-018-0189-7

Source DB:  PubMed          Journal:  Nat Plants        ISSN: 2055-0278            Impact factor:   15.793


  26 in total

1.  Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress.

Authors:  Gina H Mohammed; Roberto Colombo; Elizabeth M Middleton; Uwe Rascher; Christiaan van der Tol; Ladislav Nedbal; Yves Goulas; Oscar Pérez-Priego; Alexander Damm; Michele Meroni; Joanna Joiner; Sergio Cogliati; Wouter Verhoef; Zbyněk Malenovský; Jean-Philippe Gastellu-Etchegorry; John R Miller; Luis Guanter; Jose Moreno; Ismael Moya; Joseph A Berry; Christian Frankenberg; Pablo J Zarco-Tejada
Journal:  Remote Sens Environ       Date:  2019-07-13       Impact factor: 10.164

2.  Novel Vegetation Indices to Identify Broccoli Plants Infected With Xanthomonas campestris pv. campestris.

Authors:  Mónica Pineda; María Luisa Pérez-Bueno; Matilde Barón
Journal:  Front Plant Sci       Date:  2022-06-23       Impact factor: 6.627

Review 3.  Chlorophyll a fluorescence illuminates a path connecting plant molecular biology to Earth-system science.

Authors:  Albert Porcar-Castell; Zbyněk Malenovský; Troy Magney; Shari Van Wittenberghe; Beatriz Fernández-Marín; Fabienne Maignan; Yongguang Zhang; Kadmiel Maseyk; Jon Atherton; Loren P Albert; Thomas Matthew Robson; Feng Zhao; Jose-Ignacio Garcia-Plazaola; Ingo Ensminger; Paulina A Rajewicz; Steffen Grebe; Mikko Tikkanen; James R Kellner; Janne A Ihalainen; Uwe Rascher; Barry Logan
Journal:  Nat Plants       Date:  2021-08-09       Impact factor: 15.793

4.  Fast Detection of Olive Trees Affected by Xylella Fastidiosa from UAVs Using Multispectral Imaging.

Authors:  Attilio Di Nisio; Francesco Adamo; Giuseppe Acciani; Filippo Attivissimo
Journal:  Sensors (Basel)       Date:  2020-08-31       Impact factor: 3.576

5.  Spatial pattern of Bois noir: case study of a delicate balance between disease progression and recovery.

Authors:  Sergio Murolo; Matteo Garbarino; Valeria Mancini; Gianfranco Romanazzi
Journal:  Sci Rep       Date:  2020-06-17       Impact factor: 4.379

6.  Radiative transfer modelling reveals why canopy reflectance follows function.

Authors:  Teja Kattenborn; Sebastian Schmidtlein
Journal:  Sci Rep       Date:  2019-04-25       Impact factor: 4.379

Review 7.  Computer vision-based phenotyping for improvement of plant productivity: a machine learning perspective.

Authors:  Keiichi Mochida; Satoru Koda; Komaki Inoue; Takashi Hirayama; Shojiro Tanaka; Ryuei Nishii; Farid Melgani
Journal:  Gigascience       Date:  2019-01-01       Impact factor: 6.524

8.  Detection of Xylella fastidiosa in almond orchards by synergic use of an epidemic spread model and remotely sensed plant traits.

Authors:  C Camino; R Calderón; S Parnell; H Dierkes; Y Chemin; M Román-Écija; M Montes-Borrego; B B Landa; J A Navas-Cortes; P J Zarco-Tejada; P S A Beck
Journal:  Remote Sens Environ       Date:  2021-07       Impact factor: 10.164

9.  Detection and Imaging of the Plant Pathogen Response by Near-Infrared Fluorescent Polyphenol Sensors.

Authors:  Robert Nißler; Andrea T Müller; Frederike Dohrman; Larissa Kurth; Han Li; Eric G Cosio; Benjamin S Flavel; Juan Pablo Giraldo; Axel Mithöfer; Sebastian Kruss
Journal:  Angew Chem Int Ed Engl       Date:  2021-11-22       Impact factor: 16.823

10.  Advanced Imaging for Quantitative Evaluation of Aphanomyces Root Rot Resistance in Lentil.

Authors:  Afef Marzougui; Yu Ma; Chongyuan Zhang; Rebecca J McGee; Clarice J Coyne; Dorrie Main; Sindhuja Sankaran
Journal:  Front Plant Sci       Date:  2019-04-16       Impact factor: 5.753

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