Abstract
Flavescence dorée (FD) is a grapevine disease caused by phytoplasmas and transmitted by leafhoppers that has been spreading in European vineyards despite significant efforts to control it. In this study, we aim to develop a model for the automatic detection of FD-like symptoms (which encompass other grapevine yellows symptoms). The concept is to detect likely FD-affected grapevines so that samples can be removed for FD laboratory identification, followed by uprooting if they test positive, all to be conducted quickly and without omission, thus avoiding further contamination in the fields. Developing FD-like symptoms detection models is not simple, as it requires dealing with the complexity of field conditions and FD symptoms’ expression. To address these challenges, we use deep learning, which has already been proven effective in similar contexts. More specifically, we train a Convolutional Neural Network on image patches, and convert it into a Fully Convolutional Network to perform inference. As a result, we obtain a coarse segmentation of the likely FD-affected areas while having only trained a classifier, which is less demanding in terms of annotations. We evaluate the performance of our model trained on a white grape variety, Chardonnay, across five other grape varieties with varying FD symptoms expressions. Of the two largest test datasets, the true positive rate for Chardonnay reaches 98.48% whereas for Ugni-Blanc it drops to 8.3%, underlining the need for a multi-varietal training dataset to capture the diversity of FD symptoms. To obtain more transparent results and to better understand the model’s sensitivity, we investigate its behavior using two visualization techniques, Guided Gradient-weighted Class Activation Mapping and the Uniform Manifold Approximation and Projection. Such techniques lead to a more comprehensive analysis with greater reliability, which is essential for in-field applications, and more broadly, for all applications impacting humans and the environment.
Highlights
Flavescence dorée (FD) is a grapevine disease raising serious concern in Europe
Symptoms expressed by an FD-infected plant are the same as those expressed by Bois noir, another disease caused by phytoplasmas
The objective of this study is to achieve the automatic preidentification of FD symptoms in several white grape varieties from images taken in the field
Summary
Flavescence dorée (FD) is a grapevine disease raising serious concern in Europe This disease is caused by several phytoplasmas classified according to their ribosomal DNA (16SrV subgroup C and D) (Filippin et al, 2009) and grouped under the temporary name of Candidatus Phytoplasma vitis (Firrao et al, 2004). The transmission of those phytoplasmas is mediated by infected leafhopper Scaphoideus titanus which transmit the disease when feeding on vine leaves. Symptoms expressed by an FD-infected plant are the same as those expressed by Bois noir, another disease caused by phytoplasmas. In some at-risk areas in France, Italy and Switzerland, insecticide treatments are mandatory to limit the number of leafhoppers (Chuche and Thiery, 2014)
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