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

Abstract

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 Trichoderma 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 Trichoderma spp. strains were characterized both in vivo and in vitro for their ability to contain R. solani, S. sclerotiorum and S. rolfsii development. All Trichoderma spp. showed, in vitro significant radial growth inhibition of the target phytopathogens. Furthermore, biocontrol trials were performed on wild rocket, green and red baby lettuces infected, respectively, with R. solani, S. sclerotiorum and S. rolfsii. The plant status was monitored by using hyperspectral imaging. Two strains, Tl35 and Ta56, belonging to T. longibrachiatum and T. atroviride 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-Trichoderma-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.

Biological Control of Fungal Diseases by Trichoderma aggressivum f. europaeum and Its Compatibility with Fungicides

“…, F. solani[76][77][78], B. cinerea[79][80][81][82][83][84][85], S. sclerotiorum[82,86], S. minor[87], Rhizoctonia solani[72,[88][89][90], Phytophthora capsici[91,92], Phytophthora parasitica[85], Chondrostereum purpureum[93], Macrophomina phaseolina[94], Podosphaera xanthii[95], Alternaria alternata,[96], Pythium aphanidermatum…”

Biotic and Abiotic Sources of Stress on Wild Rocket Classified by Leaf-Image Hyperspectral Data Mining with an Artificial Intelligence Model

“…Applying a linear regression analysis, Manganiello et al [70] recently found the interactive combination of hyperspectral vegetation indices TSAVI + SAVI and Triangular Vegetation Index able to predict baby-leaf infection levels of three different soil-borne pathogens, including R. solani on wild rocket, as modulated by treatments with biocontrol agents Trichoderma spp.…”

Early Detection of Wild Rocket Tracheofusariosis Using Hyperspectral Image-Based Machine Learning

“…Hyperspectral sensors capture the reflectance characteristics of an object by measuring a so-called hyperspectral fingerprint in the form of a data cube, which shows the spatial (x, y) and spectral (z) dimensions of the reflectance values per wavelength [38,39]. Many studies have shown that plant reflectance patterns are affected by abiotic stresses, pests, plant pathogens, and/or biological control agents, as well as any other treatments that affect plant physiology, emphasizing the value of hyperspectral imaging sensors in phenotyping, detection, and/or monitoring plant disease [30,[40][41][42][43][44][45]. These tools help to highlight spatial variability occurring in the canopy and have shown, in correspondence to previous research, an interesting ability in alert about generalized non-specific changes (symptoms) related to biotic stressors in the basal sap-flow system [46,47].…”

“…Total genomic DNA was extracted from 100 mg of processed sample by using the PureLink Plant Total DNA Purification Kit (Invitrogen™, ThermoFisher Scientific, Waltham, MA, USA) according to the manufacturer's protocol. PCR amplification of the FOR internal transcribed spacers (ITS1-4) and translation elongation factor 1α (TEF1) was performed in a Biorad C1000 Thermal Cycler (Bio-Rad, Hercules, CA, USA) following the PCR procedure reported by Manganiello et al [30]. Amplicons were purified by a PureLink™ PCR Purification Kit (InvitrogenTM, ThermoFisher Scientific, Waltham, MA, USA) quantified by NanoDrop™ (NanoDrop Technologies Inc., Wilmington, DE, USA) and sent to Sanger sequencing.…”