Dataset Information

Evaluating the suitability of hyper- and multispectral imaging to detect foliar symptoms of the grapevine trunk disease Esca in vineyards.

ABSTRACT:

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. Therefore, 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, objective, 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 accuracies 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.

SUBMITTER: Bendel N

PROVIDER: S-EPMC7579826 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Publications

Evaluating the suitability of hyper- and multispectral imaging to detect foliar symptoms of the grapevine trunk disease Esca in vineyards.

Bendel Nele N Kicherer Anna A Backhaus Andreas A Klück Hans-Christian HC Seiffert Udo U Fischer Michael M Voegele Ralf T RT Töpfer Reinhard R

Plant methods 20201021

<h4>Background</h4>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. Therefore, an annual monitoring is required. In this context, automatic detection of symptoms could be a great relief for winegrowers. Spectral sensors h ...[more]

PMID: 33101451

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Project description:Esca is a Grapevine Trunk Disease (GTD) caused by a broad range of taxonomically unrelated fungal pathogens. These attack grapevine wood tissues inducing necroses even in the conductive vascular tissues, thus affecting the vine physiology and potentially leading to plant death. However, the influence of Esca on leaf and whole-plant water transport disruption remains poorly understood. In this paper, a detailed analysis of xylem-related physiological parameters in grapevines that expressed Esca-foliar symptoms was carried out. The experiments were conducted in a vineyard in the Bordeaux region (France) on cv. Cabernet-Sauvignon (Vitis vinifera L.) grapevines, which were monitored for Esca-foliar symptoms over a two-year period. Heat dissipation sap-flow sensors were installed during the summer on grapevines having expressed or not Esca-foliar symptoms. Leaf water potential, stomatal conductance and leaf transpiration were also measured. Physiological monitoring showed that sap flow density and whole-plant transpiration of Esca-infected grapevines decreased significantly a week before the first foliar symptoms appeared. When atmospheric water demand (Vapour Pressure Deficit, VPD) was the highest, both parameters tended to be about twice as low in symptomatic grapevines as in asymptomatic ones. Sap flow density data at the maximum transpiration-time, was systematically 29-30% lower in Esca-infected grapevines compared to control plants before or after the appearance of Esca-foliar symptoms. This trend was observed whatever the temperatures and VPD values measured. In Esca-diseased plants, larger amounts of necrotic wood, mainly white rot, were found in the trunk and cordon of symptomatic grapevines compared to healthy ones, suggesting necroses have an influence in reducing the whole-plant hydraulic capacity. This study reveals that the use of physiological monitoring methods, together with the visual monitoring of foliar symptoms, could prove useful in providing accurate measurements of Esca disease severity.

Project description:Leaf samples were obtained from Vitis vinifera 'Malvasia Fina' plants with well-characterized esca complex disease symptoms (n = 18) and from healthy uninfected plants (n = 6). Leaves from diseased plants were divided into three groups: asymptomatic (ASY), chlorotic (SY1), and scorched leaves (SY2). The metabolic profile of these leaves was then examined using an ultrahigh performance liquid chromatography system coupled to a Q-Exactive Hybrid Quadrupole-Orbitrap high resolution/accurate mass spectrometer interfaced with a heated electrospray ionization source. The number of small molecules measured in a sample was increased by varying the reconstitution solvent, chromatographic column, and ionization source. Data on accurate masses, peak areas, and relative levels of several metabolites were documented for each leaf sample, using the abovementioned approach. In this paper, data on 235 metabolites of known structural identity are reported, along with the biochemical pathways to which the metabolites belong. The remaining data related to lipid species and with a different focus of the research question are reported elsewhere. The broad coverage of metabolites reported here resulted in a greater coverage of the biochemical pathways involved in grapevine metabolism, which could provide a better understanding of the biochemical changes occurring during the onset and progression of foliar symptoms after invasion of woods by esca-associated pathogens. To determine which metabolites varied according to the study design, the detected ion features were processed using different statistical methods, including mean and median values, fold changes, Welch's two-sample t-test, false discovery rate, and quartiles represented by box and whisker plots. The goal of this statistical evaluation was to assess the responses of healthy, asymptomatic, and symptomatic leaf groups using a pairwise comparison, thus providing an opportunity for detecting statistically significant compounds and uncovering the dynamic metabolic models underlying disease latency and symptom expression.

Dataset Information

Evaluating the suitability of hyper- and multispectral imaging to detect foliar symptoms of the grapevine trunk disease Esca in vineyards.

Background

Results

Conclusions

Publications

Evaluating the suitability of hyper- and multispectral imaging to detect foliar symptoms of the grapevine trunk disease Esca in vineyards.

Similar Datasets

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