AI & IoT in Vineyards: Boosting Wine Quality & Climate Resilience in France & Italy

European vineyards are increasingly turning to advanced technology to safeguard their harvests and enhance wine quality in the face of growing climate challenges. A project called AgriDataValue, funded by the European Union’s Horizon Europe program, is at the forefront of this digital transformation, integrating data collection and analysis into viticulture practices across multiple countries.

Harnessing Data for a Changing Climate

The Rise of Smart Vineyards

The AgriDataValue initiative is rolling out 23 pilot projects in nine European nations, focusing on various crops and production systems. Within viticulture, pilot programs in France and Italy are specifically designed to incorporate vineyards into advanced “smart agriculture” and agroclimatic monitoring systems. This involves deploying Internet of Things (IoT) technology – specifically sensors – to gather real-time data on environmental factors like temperature, soil moisture, and relative humidity.

Did You Know? The AgriDataValue project is part of a broader effort to create an Agro-Environmental Data Space, driving digitalization across the agricultural sector.

This data is then transmitted directly to producers, enabling them to make informed adjustments to irrigation, fertilization, and disease prevention strategies. The goal is to increase efficiency while simultaneously minimizing environmental impact.

AI-Powered Risk Management

The project utilizes systems like SynField, developed by Synelixis, to continuously monitor key field parameters. These systems provide a precise and up-to-date view of vineyard conditions, supporting more effective management and optimized product quality. Furthermore, AgriDataValue incorporates machine learning models to anticipate potential risks to plant health.

These models analyze historical data and climate patterns to identify periods of heightened risk from diseases like powdery mildew (oídio) and downy mildew (mildiu), allowing for targeted interventions and reduced crop losses. A central focus is also on mitigating climate risks, particularly the threat of spring frosts to European vineyards.

Regional Implementation: France and Italy

In France, the pilot project is underway in Saint-Émilion, a region renowned for its wine production and stringent traceability requirements. SynField X5 devices and SynOdos peripheral nodes are collecting data on ambient temperature, relative humidity, wind speed and direction, precipitation, soil moisture and temperature, leaf wetness, and solar radiation in Merlot vineyards.

In Italy, a seven-hectare vineyard in Tebano (Emilia-Romaña) is participating in the project. This vineyard, planted with Sangiovese and Trebbiano varieties using the Guyot system since 2021, features a SynField X3 main node, a weather station, and soil sensors constantly gathering environmental data. The terrain is flat and the soil is a mix of clay and silt.

Expert Insight: The integration of satellite data with on-site sensor readings represents a significant step towards more accurate extreme weather prediction, potentially offering a crucial buffer against climate-related crop damage.

All collected data is integrated into the AgriDataValue platform, facilitating advanced analysis and the use of artificial intelligence tools to support decision-making at the farm level. Secure data sharing between producers is also a key component, promoting transparency and efficiency.

Looking Ahead

The deployment of this technology is designed to give producers a deeper understanding of their vineyards, enabling them to manage climate risks, optimize yields, and reduce their environmental footprint. It also enhances traceability throughout the production chain, bolstering consumer confidence. It is possible that this approach could serve as a model for other agro-food sectors seeking more sustainable and efficient production methods.

Frequently Asked Questions

What types of data are being collected in these vineyards?

Sensors are collecting data on temperature, humidity (soil and air), precipitation, wind speed and direction, soil moisture and temperature, leaf wetness, and solar radiation.

Which countries are involved in the AgriDataValue project?

The project includes 23 pilot projects across nine European countries, though the specific countries are not detailed in the provided information.

What diseases are the AI models designed to predict?

The models are designed to predict risks associated with powdery mildew (oídio) and downy mildew (mildiu).

As vineyards increasingly embrace digital technologies, how might this shift impact the future of wine production and the consumer experience?