How Tenso AI, Asahi and Microsoft Are Transforming Hop Farming Through the forHops Project

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Climate change is rapidly reshaping the world’s agricultural landscape — and hop farming is no exception. Facing unpredictable weather, declining soil health, and rising water scarcity, hop growers around the world are being forced to rethink how they operate.

To confront these challenges, Asahi Group Holdings, Microsoft, and Tenso AI united to launch forHops, an ambitious initiative designed to make hop cultivation more resilient, sustainable, and profitable. By combining industry expertise with cutting-edge AI and precision agriculture, the project is proving that technology can redefine the future of hops.

Farmer in a hop yard using AI

Why the forHops Project Matters:

Hop farming is under increasing pressure due to several critical issues:

• Climate Change: Extreme weather events, temperature fluctuations, and shifting rainfall patterns reduce yields and crop stability.

  
  

• Water Scarcity: Hops are water-intensive, and many growing regions face shrinking water supplies.

  
  

• Soil Degradation: Declining soil quality impacts plant health, productivity, and long-term farm viability.

  
  

Traditional agricultural practices alone can no longer keep up. Limited access to real-time data also makes it difficult for farmers to make timely, informed decisions.

This is where Tenso AI’s precision agriculture approach becomes essential.

Side-by-side comparison of healthy vs. drought-stressed hop plants

The Role of Tenso AI: Bringing Intelligence to the Field

Tenso AI contributed core technological capabilities to the forHops project, including:

An agronomist placing sensors in the field

1. Predictive Models

AI models capable of forecasting yield, water requirements, and plant stress based on historical climate data, soil metrics, and crop performance.

2. Advanced Data Analysis

Large datasets were analyzed to uncover hidden patterns, helping farmers understand how weather, soil moisture, and irrigation affect yields.

3. Precision Agriculture Tools

Technologies such as drip irrigation optimization, environmental sensing, and digital twins allowed farms to reduce water waste while improving output.

How the Project Was Implemented:

Six trial farms were equipped with:

• 2Grow sapflow sensors to track plant hydration dynamics

  
  

• Weather stations measuring temperature, humidity, rainfall, and light

  
  

• Soil moisture sensors to monitor irrigation needs in real time

  
  

Using this data, Tenso AI built an ML-powered digital twin — a virtual model of each farm — enabling simulations of irrigation patterns, climate impacts, and crop response before decisions were applied in the field.

2Grow sapflow sensors installed on a hop bine

Quantifiable Results: Sustainability Meets Productivity

The results from the forHops project are remarkable:

📈 40% Increase in Hop Yields

Optimized irrigation and data-driven crop management dramatically boosted productivity.

💧 Up to 30% Reduction in Water Consumption

AI-based scheduling ensured water was used only when needed, reducing waste.

🌱 Up to 10,000 Tons of Carbon Sequestered Per Year

Improved practices and reduced resource use contributed to measurable environmental benefits.

Overall, the project succeeded in creating a hop supply chain that is more resilient, more efficient, and significantly more sustainable.

Market overview showing Tenso AI's obtainable, available, and total addressable opportunities across high-value specialty crops

Lessons Learned:

While the project demonstrated strong results, several key insights emerged:

• Data Quality Matters: Accurate predictions rely on consistent, high-quality data from sensors and field operations.

  
  

• Every Farm Is Unique: Local soil conditions, infrastructure, and farming methods require customized AI models.

  
  

• Sustainability Must Be Central: Long-term success depends on prioritizing soil health, water conservation, and eco-friendly farming methods.

AI Digital maps and satellite imagery of farmland

Broader Impacts on the Industry:

For the Hop Industry

• Greater competitiveness through higher yields and lower costs

• Improved reputation through sustainable practices

• New opportunities in eco-conscious markets

For the Environment

• Reduced carbon footprint

• Conservation of water resources

• Protection of biodiversity through regenerative practices

For Farmers

• More reliable yields

• Actionable insights instead of guesswork

• Better long-term profitability

Sustainable hop growth in action

What Comes Next for forHops and Tenso AI:

The success of the project opens the door to many future developments:

• Scaling the solution across larger farms and additional regions

  
  

• Collaborations with breweries and food producers, creating more sustainable supply chains

  
  

• Continuous R&D to improve AI accuracy and expand capabilities

  
  

• Integration of new sensors (remote imagery, soil analytics, drone monitoring, etc.)

The forHops project shows that the combination of AI, sensor technology, and industry collaboration can create a more sustainable agricultural future — one where data-driven farming becomes the new standard. The collaboration between Asahi Group Holdings, Microsoft, and Tenso AI proves that innovation can turn uncertainty into opportunity. By combining precision sensors, advanced AI models, and real-time field intelligence, hop growers can now make decisions that are not only smarter — but more sustainable and more profitable.

As the industry moves forward, the success of forHops signals a clear shift: the future of agriculture will be data-driven, resilient, and environmentally responsible. Tenso AI remains committed to pushing that future even further — helping farmers worldwide adapt, optimize, and thrive in a changing climate.

🌱 The transformation has begun. The question now is how far we can go when intelligence meets the fields that feed us.

Tenso AI is proving that when intelligence meets agriculture, the future stops being uncertain — it becomes scalable.