Artificial intelligence is present in the bubbles of Moët Hennessy. Thanks to the Hiphen company, the champagne house, which is part of the luxury group LVMH (owner of “Echos”), employs advanced deep learning techniques to detect diseases, particularly botrytis, in grape harvests arriving on its pressing lines.
“Our algorithms optimize sorting by providing quality indicators for each box of fruit, ensuring homogeneous vintages,” explains Alexis Comar, the founding president of this Avignon-based specialist in robotics and image processing established ten years ago. The analysis is performed under polarized light and takes just 0.3 seconds, which is also enough time to assess the maturity level of the clusters.
It can measure the phenotype of plants
Grapes are not the only focus: through data analysis, Hiphen can measure the phenotype of plants, meaning all their observable characteristics, for various agricultural needs, including optimizing varietal selections for crop monitoring.
“We measure plants using sensors embedded on satellites or drones, on tractors, or directly installed in the fields. Our job is to transform these signals into agronomic information that our clients use to select future varieties or create decision-making tools,” the CEO elaborates.
Among the parameters studied are water stress, nitrogen stress, weed quantities, and the presence or absence of diseases, among others.
A range of tools
To facilitate data acquisition, Hiphen has developed a range of often customized tools. For the Mohammed VI Polytechnic University in Morocco, a crane equipped with sensors moves over lines of experimental crops in open fields to gain insights into the mechanisms of water stress on African seeds.
For the University of Arizona, it employs a gantry on rails fitted with cameras operating at different wavelengths, spectrometers, and 3D scanners to study the tolerance and resilience of sorghum and lettuce crops on extensive plots under desert conditions. At the National Research Institute for Agriculture, Food, and the Environment (INRAE) in Avignon, similar tools are currently being used to further understand the drought resistance of certain tree species.
“Mobility is our best asset for data acquisition,” insists Alexis Comar. To collect information as close to the field as possible, a new portable high-resolution imaging instrument is being launched, featuring sensors at the end of a pole that allow measurement of vegetation density in selected plots on foot.
Around sixty customers
Sampling is therefore more precise and enables yield predictions for specific watersheds or evaluation of treatment effectiveness across different plots.
Through evangelization at around thirty specialized trade fairs each year, he aims to triple his business within five years to reach a turnover of 10 million euros.
Artificial Intelligence Revolutionizing Moët Hennessy’s Champagne Production
The luxury champagne house Moët Hennessy, a part of the LVMH group, is making waves in the world of agriculture with the use of artificial intelligence. By collaborating with the innovative Hiphen company, they are leveraging advanced deep learning techniques to monitor grape health and quality during harvest, significantly enhancing the champagne production process.
Advanced Disease Detection in Grapes
Hiphen has pioneered algorithms that expedite the sorting of grapes based on quality indicators. According to Alexis Comar, the founding president of Hiphen, “Our algorithms optimize sorting by providing quality indicators for each box of fruit, thus ensuring homogeneous vintages.” Using polarized light, their analysis takes a mere 0.3 seconds, adequately assessing the degree of maturity of grape clusters, ensuring only the best grapes make it to the pressing line.
From Grapes to Plant Phenotyping
While grapes are a primary focus, Hiphen’s capabilities extend to plant phenotyping, which encompasses all observable traits of plants. This includes various agricultural applications such as:
- Optimizing varietal selections
- Crop monitoring for health and yield
“We measure plants using sensors embedded in satellites, drones, tractors, or directly in the fields,” Comar explains. “Our job is to transform these signals into agronomic information, enabling our clients to select varieties for future cultivation or to develop decision-making tools.” Factors analyzed through this process include water stress, nitrogen levels, weed quantities, and the presence of diseases, all vital for modern agricultural practices.
A Suite of Custom Tools
To enhance data acquisition capabilities, Hiphen has developed a comprehensive range of tailor-made tools. Examples include:
- Crane-mounted sensors: Deployed at the Mohammed VI Polytechnic University in Morocco to study water stress mechanisms in crops.
- Gantry on rails: Equipped with cameras, spectrometers, and 3D scanners at the University of Arizona, it studies crops like sorghum and lettuce under extreme desert conditions.
- Portable imaging instruments: New tools are being developed for on-foot data collection, measuring the vegetation density directly in the field.
These advancements allow for precise sampling, yield predictions for specific watersheds, and the evaluation of treatment effectiveness across different plots.
Mobility in Data Acquisition
“Mobility is our key to data acquisition,” insists Comar, emphasizing the importance of collecting information close to where it matters most. The innovative tools being introduced not only streamline data collection but also significantly enhance the quality of insights gathered from the field.
Building Client Relationships and Market Position
Hiphen currently serves around sixty loyal customers, a testament to its niche market presence with high value-added services. Despite facing challenges in a conservative agricultural environment resistant to change, Comar is optimistic about the future. “We come up against a market that often sees digital solutions as a fixed cost,” he acknowledges. The long-term benefits of AI and data analytics in agriculture, however, are becoming increasingly evident.
Evangelizing for Innovation
Through participation in approximately thirty specialized trade fairs every year, Hiphen aims to stimulate interest and understanding in advanced agricultural technologies. Their goal is ambitious: to triple their activity within five years and reach a turnover of 10 million euros.
The Benefits of Artificial Intelligence in Agriculture
Integrating AI into agricultural practices, particularly in luxury sectors like champagne production, offers numerous advantages:
- Enhanced Quality Control: AI ensures stringent quality checks of grape harvests, leading to superior final products.
- Informed Decision-Making: The ability to analyze large sets of data helps in making informed decisions regarding crop health and management.
- Yield Prediction: Accurate predictions of yield based on real-time data empower producers to optimize their production schedules.
- Resource Optimization: Better insights into water and nutrient needs allow for efficient resource allocation, reducing waste and costs.
Case Studies Highlighting AI Applications
| Application | Technology Used | Outcome |
|---|---|---|
| Cranes in Morocco | Sensor Technology | Understanding water stress in African seeds |
| University of Arizona Study | Gantry System | Researching crop resilience in desert conditions |
| INRAE Research | Cameras and Spectrometers | Analyzing trees’ drought resistance |
Transforming Future Agriculture
The application of artificial intelligence in grape and general agricultural management signifies a pivotal moment in how producers can leverage technology to enhance both productivity and quality. As companies like Hiphen continue to innovate and advocate for the integration of AI, the farming landscape may see a transformative shift marked by efficiency, sustainability, and improved outcomes in crop production.
Practical Tips for Farmers
Farmers looking to embrace AI technologies can consider the following steps:
- Research available tools: Investigate AI-based tools that align with your specific agricultural needs.
- Attend trade shows: Participate in agricultural fairs to learn about the latest technological innovations.
- Experiment with small implementations: Start with pilot projects to test AI tools before full-scale implementation.
- Networking: Connect with other farmers who have adopted AI technologies to learn from their experiences.
By staying informed and open to these advancements, farmers can significantly enhance their operations and contribute to a more sustainable agricultural future.