description
- Two of the most severe global problems are climate change and food security. Both can be linked to agriculture since it is a large producer of greenhouse gasses, while a reduced yield can negatively impact food security. The modern trend is to merge agriculture and technology by implementing "smart farming" techniques; not only increasing yield, but also making the process more efficient. Rust diseases pose significant risks to crops since total losses can be encountered in bad pandemic years. Current preventive measures include pesticides and genetically modified crops. The former is environmentally detrimental if used in large quantities while the latter could pose long-term health risks. Early rust detection followed by localized pesticide application provides a way to only use as little pesticides as possible. Current early detection methods rely on using spore traps alongside specialized laboratories; making the process slow and complex. This project aims to develop and build a bespoke microscopy system that can be deployed in the field to detect wheat rusts optically. The imaging system would be based on lensless digital holographic microscopy (DHM). This technique can provide image features that are not possible with conventional imaging techniques; features such as quantitative phase imaging. Holographic imaging works by recording the interference between the light that interacts with the object and a reference beam. By using the theory of light propagation, the complex field at the object plane can be digitally reconstructed, without the use of lenses. Lensless DHM has received significant attention in recent years since modern image sensors feature small pixel sizes at ever-decreasing prices. Most advancements in lensless DHM have been for transmitted light imaging, with features such as sub-micron resolution and multispectral imaging being demonstrated. The novelty of this project would come from adapting these advancements to lensless DHM operating in reflection mode.