Functional Hyperspectral Imaging by High-Related Vegetation Indices to Track the Wide-Spectrum Biocontrol Activity Against Soil-Borne Diseases of Baby-Leaf Vegetables.

Front Plant Sci

Consiglio per la ricerca in agricoltura e l'analisi dell'economia agraria, Centro di ricerca Orticoltura e Florovivaismo, Pontecagnano Faiano, Italy.

Published: February 2021

Research has been increasingly focusing on the selection of novel and effective biological control agents (BCAs) against soil-borne plant pathogens. The large-scale application of BCAs requires fast and robust screening methods for the evaluation of the efficacy of high numbers of candidates. In this context, the digital technologies can be applied not only for early disease detection but also for rapid performance analyses of BCAs. The present study investigates the ability of different spp. to contain the development of main baby-leaf vegetable pathogens and applies functional plant imaging to select the best performing antagonists against multiple pathosystems. Specifically, sixteen different spp. strains were characterized both and for their ability to contain and development. All spp. showed, significant radial growth inhibition of the target phytopathogens. Furthermore, biocontrol trials were performed on wild rocket, green and red baby lettuces infected, respectively, with and . The plant status was monitored by using hyperspectral imaging. Two strains, Tl35 and Ta56, belonging to and species, significantly reduced disease incidence and severity (DI and DSI) in the three pathosystems. Vegetation indices, calculated on the hyperspectral data extracted from the images of plant--pathogen interaction, proved to be suitable to refer about the plant health status. Four of them (OSAVI, SAVI, TSAVI and TVI) were found informative for all the pathosystems analyzed, resulting closely correlated to DSI according to significant changes in the spectral signatures among health, infected and bio-protected plants. Findings clearly indicate the possibility to promote sustainable disease management of crops by applying digital plant imaging as large-scale screening method of BCAs' effectiveness and precision biological control support.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7984460PMC
http://dx.doi.org/10.3389/fpls.2021.630059DOI Listing

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