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Addressing Dieback in Grapevines: Causes and Effects

Study reveals insights on grapevine dieback issues and their impact on vineyards.

― 6 min read


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Table of Contents

Perennial plant dieback is when certain plants start to die off too early, losing their healthy growth and eventually dying. This problem can be caused by various issues, primarily environmental factors like drought, as well as diseases caused by pathogens. Dieback is a common issue in forests around the world and affects many regions. Despite its prominence, research on dieback in grapevines, which are a significant crop, has not been sufficiently explored.

Causes of Dieback in Grapevines

Grapevines can suffer from dieback due to both environmental and biological factors. Several trunk diseases, such as Esca, Eutypa dieback, and Botryosphaeria dieback, are particularly harmful and are found in vineyards across the globe. These diseases can damage the grapevines and lead to a decline in their yield. However, sometimes the estimation of losses in certain areas may be too high.

The rise in trunk diseases in Europe has been noted since the early 1990s. Particularly, from the early 2000s until about 2008, there was a noticeable increase in cases of esca, a specific trunk disease. This trend is especially concerning for grape growers, especially since effective treatments for these diseases have been limited due to regulations.

Factors Affecting Incidence of Trunk Diseases

Many factors can influence how often trunk diseases occur in grapevines. Different Grape Varieties have shown varied responses to these diseases, with some being more resistant than others. Research conducted in various regions of Europe has shown that this variation can be linked to the grape type.

The age of the vines also plays a role in their response to diseases. As vines age, they may become more susceptible to stress from environmental conditions and pathogens. However, the relationship between vine age and the occurrence of trunk diseases is not straightforward. Some studies suggest that older vines may show more symptoms, while others find little connection between age and disease incidence.

To better understand dieback and disease prevalence, it is critical to gather long-term data across different vineyards. This data will help researchers analyze the patterns and improve pest management strategies in vineyards.

Need for Monitoring and Surveillance

Large-scale and long-term monitoring of grapevines is necessary to effectively manage the emergence of diseases like dieback. Collecting information about plant health can help in recognizing disease patterns, facilitating better control measures.

In France, a national survey was conducted between 2003 and 2008 to monitor trunk diseases across several regions. This survey included a diverse range of grape varieties and numerous vineyard plots. Yet, recent data collection is essential to assess how trunk disease levels have changed over the years.

To address this, a study was carried out to consolidate data from various regions of France over 20 years, focusing on two major diseases affecting grapevines: esca and Eutypa dieback. This newly created database includes many vineyard plots and grape varieties, allowing for a detailed analysis of how these diseases have developed over the years.

Project Overview

The database contains thousands of observations regarding leaf symptoms of esca and Eutypa dieback across many French wine regions. This data helps in understanding the occurrence and impact of these diseases over the 20 years, as well as the effect of different grape varieties and vineyard ages.

During the study, leaf symptoms were recorded in various municipalities across multiple regions. Each observation involved assessing numerous plants to determine the presence of symptoms. It is vital to analyze this data for effective vineyard management and disease control strategies.

Observations of Esca Leaf Symptoms

Through the data collected, it's evident that many vineyards have experienced significant rates of esca, with the percentage of plots showing symptoms fluctuating from year to year. On average, around 74% of monitored plots had at least one plant exhibiting symptoms. Some regions had even higher prevalence rates.

When considering the overall incidence of esca, the average rate was about 3.1%, though it varied from year to year. Specific grape varieties demonstrated considerable differences in their rates of incidence, with certain types being more affected than others. For example, Trousseau had the highest incidence, while Meunier, Pinot Noir, and Syrah showed lower incidence rates.

Monitoring Eutypa Dieback

Similarly, Eutypa dieback was observed in numerous plots. The incidence of this disease has decreased over the years, with various cultivars showing different rates of susceptibility. The data indicates that most vineyards monitored had at least some vines with Eutypa dieback symptoms, but a significant number were free of the disease.

Overall, specific wine regions reported differing rates of Eutpa dieback, with some areas showing much higher prevalence than others.

Factors Influencing Disease Dynamics

The study analyzed the interplay of cultivar, year, and vineyard age on the prevalence and incidence of esca leaf symptoms. Several key points emerged from this analysis, shedding light on how these variables impact disease occurrence.

Impact of Cultivar

Different grape varieties seem to react differently to esca disease. Some cultivars consistently show a higher prevalence of symptoms while others remain less affected. The estimated probabilities of disease presence varied, indicating that certain grape varieties, like Gewurztraminer, tend to experience more severe symptoms compared to cultivars like Chardonnay.

Yearly Variation

Yearly conditions also played an essential role in influencing disease rates. Some years saw significantly higher incidences of esca symptoms than others. For example, certain favorable weather conditions led to increased risks of symptom development. Additionally, higher rates were seen after 2012, indicating changing patterns of disease progression over time.

Age of Vines

The age of the grapevines significantly affected their susceptibility to esca. Younger vines, especially those under ten years, generally experienced lower incidence rates. As vines mature, they often become more susceptible, with incidence peaking around intermediate ages. However, some older vines showed reduced incidence rates, suggesting that the most resilient plants may survive better over time.

Statistical Modeling of Data

This study employed statistical modeling techniques to analyze the collected data. A Bayesian framework was used to gain deeper insights into how cultivar, year, and vineyard age affect the dynamics of esca and Eutpa dieback.

Through this modeling process, researchers were able to identify the significant influences that different factors have on the prevalence and incidence of esca symptoms. The analysis highlighted how well the model fit the observed data by correlating the predictions with actual conditions in the vineyards.

Conclusion

The comprehensive nature of this study provides valuable insights into how trunk diseases like esca and Eutpa dieback affect grapevines across France. Despite variability in symptoms among different cultivars and years, trends have emerged that could help grape growers manage these diseases better.

The data collected highlights the need for ongoing monitoring of vineyards, as future weather patterns may continue to impact the health of grapevines. Understanding these dynamics will play a crucial role in developing effective management strategies to ensure the sustainability of grape production in the face of both biotic and abiotic stressors.

In summary, the study's findings underline the importance of continued research and monitoring in the field of plant health, especially concerning perennial crops like grapevines. The patterns observed through this extensive data collection serve as a foundation for further investigations into disease resistance and vineyard management practices.

Original Source

Title: Exploring the role of cultivar, year and plot age in the incidence of esca and Eutypa dieback: insights from 20 years of regional surveys in France

Abstract: Grapevine trunk diseases cause yield losses and vine mortality in vineyards worldwide. However, there have been few quantitative studies evaluating grapevine dieback on a large spatial and temporal scale. Here, we consolidated and standardized databases from the 13 main wine regions of France, compiling records of leaf symptoms associated with esca and Eutypa dieback from 2082 plots and 36 cultivars over a 20-year period. This large dataset was used (a) for quantitative analysis of the prevalence (number of plots with at least one symptomatic plant) and incidence (percentage of symptomatic plants) of esca and Eutypa dieback; and (b) to decipher the effects of cultivar, year and plot age on both the prevalence and incidence of esca leaf symptoms by temporal Bayesian modelling. Esca was present on a mean of 74 {+/-} 2% plots annually, with an incidence of 3.1 {+/-} 0.1%. Eutypa dieback occurred in 41 {+/-} 3% of the plots, with an incidence of 1.4 {+/-} 0.1%. Our modelling approach revealed that the cultivar had a significant impact on the prevalence of esca, but not on its incidence when prevalence is greater than zero. Esca prevalence remained stable, whereas esca incidence was higher than the mean value in six of the years after 2012. We also found a significant non-linear effect of plot age, with 10- to 30-year-old plots significantly more susceptible, depending on the cultivar. This study clearly illustrates the importance of considering extensive and continuous monitoring to improve our understanding of the impact and evolution of crop diseases.

Authors: Chloe E.L. Delmas, L. Etienne, F. Fabre, D. Martinetti, E. Frank, L. Michel, V. Bonnardot, L. Guerin Dubrana

Last Update: 2024-07-29 00:00:00

Language: English

Source URL: https://www.biorxiv.org/content/10.1101/2024.03.19.585220

Source PDF: https://www.biorxiv.org/content/10.1101/2024.03.19.585220.full.pdf

Licence: https://creativecommons.org/licenses/by-nc/4.0/

Changes: This summary was created with assistance from AI and may have inaccuracies. For accurate information, please refer to the original source documents linked here.

Thank you to biorxiv for use of its open access interoperability.

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