Doctoral defence: Muhammad Uzair "Soft decision making for agri-food 4.0“

On 15 October at 10:15, Muhammad Uzair will defend his thesis "Soft decision making for agri-food 4.0“ to obtain the Doctor of Philosophy (in Computer Science).

Supervisors:
Visiting Professor Stefania Tomasiello, University of Tartu
Associate Professor Radwa Mohamed El Emam El Shawi, University of Tartu
Associate Professor Evelin Loit-Harro, Estonian University of Life Sciences

Opponents:
Professor Ferdinando Di Martino, University of Naples Federico II (Italy)
Professor Çagatay Çatal, Qatar University (Qatar)

Summary
Agriculture is essential for human civilization, providing vital food and resources. However, the growing population and climate change present significant challenges requiring innovative solutions. 

Effective water management is a major issue. A significant portion of agricultural water is lost through evapotranspiration, which includes both soil evaporation and plant transpiration. Accurately predicting water loss is crucial for developing efficient irrigation strategies. 

Soil health is another critical concern. Soil Organic Carbon (SOC) is fundamental in maintaining soil fertility, structure, and its ability to store carbon dioxide, helping mitigate climate change. Monitoring and predicting SOC levels can help farmers and policymakers implement practices like crop rotation, cover cropping, and organic amendments, which improve soil health. 

Sustainable agriculture aims to balance current food production with the preservation of resources for future generations. Sustainable practices include precision farming, integrated pest management, and the use of renewable energy sources. These practices reduce farming's ecological footprint and promote long-term productivity. 

Detection and management of crop disease are also pressing issues. Wheat strip rust, a severe disease affecting wheat crops globally, can cause significant yield loss, surpassing damage from other wheat diseases. 

Several approaches were discussed to address these issues, including fuzzy logic, classical machine learning algorithms, and a combination of Automated Machine Learning and context-aware automatic feature engineering. 

In conclusion, effective water management, maintaining soil health, promoting sustainable agriculture, and managing crop diseases are key issues that need to be addressed. By focusing on these areas, we can develop strategies that enhance