Phytopathogenic mollicutes

SCOPUS
  • Year: 2025
  • Volume: 15
  • Issue: 1

Pheno TruckAI: A mobile laboratory for hyperspectral and molecular detection of phytoplasma quarantine diseases like “flavescence dorée”

  • Author:
  • Wolfgang Jarausch1,*, Bonito Thielert2, Markus Michel3, Patrick Menz2, Miriam Runne1, Gesa Götte2, Sebastian Warnemünde2,4, Sylvia Wagner3
  • Total Page Count: 2
  • Published Online: Mar 5, 2025
  • Page Number: 21 to 22

1RLP AgroScience, Neustadt an der Weinstrasse, Germany

2Fraunhofer Institute for Factory Operation and Automation IFF, Magdeburg, Germany

3Fraunhofer Institute for Biomedical Engineering IBMT, Sulzbach, Germany

4Julius Kühn Institute (JKI) - Federal Research Centre for Cultivated Plants, Institute for Resistance Research and Stress Tolerance, Quedlinburg, Germany

Abstract

“Flavescence dorée” (FD) is an epidemic quarantine disease of grapevine in Europe efficiently spread by the leafhopper Scaphoideus titanus. Promptly uprooting infected stocks and insect control are mandatory. Systematic monitoring of FD has also to be conducted in FD-free areas. However, in these regions the non-quarantine disease “bois noir” (BN), which induces similar symptoms in grapevine as FD, is widespread. Therefore, fast and reliable detection methods for FD monitoring in the field had to be developed. The concept of the PhenoTruck® is based on three axes: large-scale screening of vineyards using remote sensing by drones (UAVs), hyperspectral screening of leaf samples for phytoplasma presence and molecular identification of FD phytoplasmas in a mobile laboratory. The latter is a special vehicle with 4-wheel drive which allows autonomous laboratory work direct at the field. Drone image data are automatically processed and sample strategies developed. One compartment of the mobile laboratory is equipped with a dual hyperspectral camera system (VNIR+SWIR, wavelength range from 400 - 2,500 nm). The spectra of leaf samples are automatically analyzed for phytoplasma presence. Using machine learning technologies, phytoplasma-infected and healthy leaves as well as phytoplasma symptoms and other biotic and abiotic stress factors could be distinguished. In addition, the spectral discrimination of FD- and BN-infected leaves was achieved. The molecular identification of FD-infections was done by improved LAMP assays. The concept of the mobile laboratory PhenoTruck® is open for any other plant disease detection.

Keywords

Grapevine, “Bois noir”, Palatinate grapevine yellows, Disease monitoring, LAMP, UAV machine learning