Workflow diagram with yellow sticky traps, planthoppers on the traps and a scanner

SBR-RISC

Habitat analysis, risk assessment and causality assessment of 'syndrome basses richesses' (SBR) at landscape level and automated evaluation of Pentastiridius leporinus on yellow traps
Habitat analysis, risk assessment and causality assessment of syndrome 'basses richesses' (SBR) at landscape level and automated evaluation of Pentastiridius leporinus on yellow traps

Laufzeit:

05/2024 – 04/2027

Projektteam:

Nathan Okole,

Dr. Stefan Paulus,

Prof. Dr. Anne-Katrin Mahlein

Abteilung:

Sensorik & Datenanalyse

Förderung:

Verein der Zuckerindustrie (VdZ)

Kooperation(en):

Verein der Zuckerindustrie, SBR Task-Force

This project focuses on understanding and managing the spread of the sugar beet disease complex known as 'syndrome basses richesses' (SBR), caused by two bacterial pathogens and transmitted by the planthopper Pentastiridius leporinus. The disease has been spreading rapidly across central Europe, significantly impacting sugar yield. To predict and mitigate the spread of the disease, the study aims to develop both correlative and mechanistic species distribution models (SDMs) to assess agronomic and ecological factors influencing P. leporinus populations. Additionally, the project seeks to improve vector identification and monitoring by developing an automated, image-based detection system using convolutional neural networks (CNNs), therefore reducing reliance on time-consuming PCR-based methods.

Workflow of the analysis, click in bottom right to see full image

Funding

wvz_logo.jpg