
SmartGrape: early detection of cicada-borne vine diseases using field spectroscopy and detection of volatile plant scents
Abstract
Bois noir (BN) is a cicada-transmitted grapevine disease that today causes up to 50% yield and vine loss in vineyards. It is caused by the phytoplasma Candidatus Phytoplasma solani (16SrXII-A). The cicada Hyalesthes obsoletus Signoret (Hemiptera: Cixiidae) transmits the phytoplasma from host plants in the undergrowth of vineyards to grapevines (Vitis vinifera). Infected plants cannot be cured and temperature anomalies associated with climate change have been seen to increase the risk of infection. In Switzerland, BN is a ‘regulated non-quarantine organism’, a classification for ‘particularly dangerous plant pathogens and pests that are already widespread’. Since there are no possibilities for direct control of BN, practical methods for systematic and early detection are urgently needed to support its management and prevention. Such methods will also be useful for preventing other invasive cicada-transmitted vine diseases, such as the quarantine disease flavescence dorée (FD). The aim of the study is to develop a package of innovative monitoring and early detection methods. Spectral imaging will enable efficient mapping of BN and support experts in calculating the proportion of infected vineyard area. Analyses of plant volatiles and the leaf metabolome of symptomatic vines will be used to determine whether they contain biomarkers for BN that can contribute to early detection. The data will be integrated to train machine learning models that categorize diseased vines and highlight distinguishing features. This package will be developed in a transdisciplinary, co-creative, step-wise process involving winegrowers, wine industry representatives and experts from the Swiss Plant Protection Service. Initial spectral, volatile and metabolomic results will be presented for a Zweigelt and Pinot Noir vineyards in Stäfa, Switzerland.
Issue: GiESCO 2025
Type: Poster
Authors
1 Agroscope, Schlossgass 8, 8820 Wädenswil
2 Weinbauzentrum Wädenswil, Schlossgass 8, 8820 Wädenswil
3 Universität Zürich, Rämistrasse 71, 8006 Zürich
4 Agroscope, Rue de Duillier 60, 1260 Nyon
5 Eidgenössische Technische Hochschule Zürich, Rämistrasse 101, 8092 Zürich
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Keywords
bois noir, flavescence dorée, plant volatiles, machine learning