Satellite-guided fertilizer system tested in Sweden's Skåne region

New technology using artificial intelligence promises to revolutionize farming practices in Sweden and beyond

Breakthrough in Agricultural Technology

Researchers at Lund University of Technology (LTH) have developed an AI-driven system that optimizes fertilizer, water, and pesticide use in real time with meter-level precision. The technology, integrated into farming machinery, will undergo field tests on farms across southern Sweden this year.

Key Benefits:

✅ Higher Efficiency: Optimized resource use (fuel, fertilizers) increases crop yields and profitability

✅ Environmental Protection: Prevents over-fertilization, reducing groundwater contamination

✅ Climate Adaptation: AI models compensate for unpredictable weather patterns caused by climate change

✅ Early Yield Predictions: Can forecast harvests as early as March/April by analyzing weather forecasts, historical patterns, and soil data

How It Works:

The system uses machine learning to process:

Satellite imagery

Historical harvest data

Soil samples

Weather patterns

It generates AI-modeled "control files" – essentially smart field maps that identify:

🔵 High-yield zones (receiving more resources)

🔴 Low-yield areas (receiving minimal inputs)

"This helps farmers allocate resources precisely where needed," explains Alexandros Sopasakis, LTH researcher.

Global Potential with Local Adaptation

While developed for Swedish conditions (where agricultural data is openly available), the technology can be adapted worldwide by training models on local datasets.

"In many countries, agri-data is privatized, hindering open research," notes PhD student Oskar Åström.

Climate Change Necessity

As historical weather patterns become less reliable, AI's ability to process real-time data becomes crucial:

"Statistical models are now essential to support farmers facing unpredictable conditions," Åström emphasizes.

Next Steps:

Field testing begins this year, with potential for rapid implementation given Sweden's advanced agricultural data infrastructure.