Automated visual assessment of grapevine leafroll symptoms using artificial intelligence

by | Jan 30, 2023 | South Africa Wine Scan

Researcher: Prof Lizel Mostert, Department of Plant Pathology, Stellenbosch University

Aim and industry relevance:

This study would aim to develop a system whereby photos taken with a smartphone could be used for the recognition of GLRaV-3 infected red and white wine cultivars. An automated identification system will aid vineyard managers and workers in easily identifying symptomatic vines without looking through all the possibilities available online or in a physical manual.  

Grapevine leafroll is an economically important disease for grapevine production in South Africa. The identification of diseased vines infected with mainly grapevine leafroll-associated virus type 3 (GLRaV-3) is essential to ensure clean propagation material and for roguing of infected vines especially in newly planted vineyards. This practice is critical in mother block vineyards, but also important for growers.

The identification of leafroll amongst other diseases and nutritional disorders can be difficult. Leaf symptoms that can be confused with leafroll are for example, ‘black leaf’ symptoms of potassium deficiency seen in late summer, Shiraz disease, and Aster yellows.

Currently, no disease identification app can identify leafroll of grapevines. The outcomes of this project will aid growers in the identification of leafroll infected vines. This can help in the management of leafroll in vineyards and nurseries.

Image credit: Shutterstock


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