Non-invasive optical techniques in the region of the Terahertz for monitoring the water content of plants and fruits

This thesis explores non-invasive techniques for analyzing plants and fruits using Terahertz (THz) radiation to address agricultural challenges posed by climate change. It focuses on detecting water stress and ozone damage in plants, as well as quality control of dry fruits. The study compares Near Infrared and THz techniques, concluding that THz is more suitable for our goal. A portable sub-THz setup was developed and validated for hazelnut quality assessment, achieving high classification accuracy, and for detecting ozone damage in plant leaves. Additionally, a high-resolution THz system was designed using a quantum cascade laser, significantly improving imaging accuracy. The new system provided detailed leaf imaging, resolving features such as veins and leaf structure. These results confirm THz technology’s potential for precise, non-invasive agricultural diagnostics. Further advancements include improving system portability, automation, and integrating AI for data analysis, reinforcing its applicability in sustainable agriculture.