Browsing by Person "Fischer, Michael"

Now showing 1 - 2 of 2

Arthropods as vectors of grapevine trunk disease pathogens: Quantification of Phaeomoniella chlamydospora on arthropods and mycobiome analysis of earwig exoskeletons
(2024) Brandenburg, Elisa Maria; Vögele, Ralf; Fischer, Michael; Behrens, Falk Hubertus
Viticulture worldwide is challenged by grapevine trunk diseases (GTDs). Involvement of arthropods in the dissemination process of GTD pathogens, notably esca pathogens, is indicated after detection of associated pathogens on arthropod exoskeletons, and demonstration of transmission under artificial conditions. The present study is the first to quantify spore loads via qPCR of the esca-relevant pathogen Phaeomoniella chlamydospora on arthropods collected in German vineyards, i.e., European earwigs (Forficula auricularia), ants (Formicidae), and two species of jumping spiders (Marpissa muscosa and Synageles venator). Quantification of spore loads showed acquisition on exoskeletons, but most arthropods carried only low amounts. The mycobiome on earwig exoskeletons was described for the first time to reveal involvement of earwigs in the dispersal of GTDs in general. Metabarcoding data support the potential risk of earwigs as vectors for predominantly Pa. chlamydospora and possibly Eutypa lata (causative agent of Eutypa dieback), as respective operational taxonomical unit (OTU) assigned genera had relative abundances of 6.6% and 2.8% in total reads, even though with great variation between samples. Seven further GTD-related genera were present at a very low level. As various factors influence the successful transmission of GTD pathogens, we hypothesize that arthropods might irregularly act as direct vectors. Our results highlight the importance of minimizing and protecting pruning wounds in the field.
Evaluating the suitability of hyper- and multispectral imaging to detect foliar symptoms of the grapevine trunk disease Esca in vineyards
(2020) Bendel, Nele; Kicherer, Anna; Backhaus, Andreas; Klück, Hans-Christian; Seiffert, Udo; Fischer, Michael; Vögele, Ralf; Töpfer, Reinhard
Background: Grapevine trunk diseases (GTDs) such as Esca are among the most devastating threats to viticulture. Due to the lack of efficient preventive and curative treatments, Esca causes severe economic losses worldwide. Since symptoms do not develop consecutively, the true incidence of the disease in a vineyard is difficult to assess. There‑ fore, an annual monitoring is required. In this context, automatic detection of symptoms could be a great relief for winegrowers. Spectral sensors have proven to be successful in disease detection, allowing a non‑destructive, objec‑ tive, and fast data acquisition. The aim of this study is to evaluate the feasibility of the in‑field detection of foliar Esca symptoms over three consecutive years using ground‑based hyperspectral and airborne multispectral imaging. Results: Hyperspectral disease detection models have been successfully developed using either original field data or manually annotated data. In a next step, these models were applied on plant scale. While the model using annotated data performed better during development, the model using original data showed higher classification accura‑ cies when applied in practical work. Moreover, the transferability of disease detection models to unknown data was tested. Although the visible and near‑infrared (VNIR) range showed promising results, the transfer of such models is challenging. Initial results indicate that external symptoms could be detected pre‑symptomatically, but this needs further evaluation. Furthermore, an application specific multispectral approach was simulated by identifying the most important wavelengths for the differentiation tasks, which was then compared to real multispectral data. Even though the ground‑based multispectral disease detection was successful, airborne detection remains difficult. Conclusions: In this study, ground‑based hyperspectral and airborne multispectral approaches for the detection of foliar Esca symptoms are presented. Both sensor systems seem to be suitable for the in‑field detection of the disease, even though airborne data acquisition has to be further optimized. Our disease detection approaches could facilitate monitoring plant phenotypes in a vineyard.