How to improve measurement of major wheat diseases using artificial intelligence?

Fungal diseases of wheat cause significant yield losses and threaten food security. Especially damaging are the five diseases that affect wheat leaves: septoria tritici blotch (STB), yellow rust (YR), brown rust (BR), powdery mildew (PM), and tan spot (TS). In the UK, fungicides and cultivar resistance are the primary ways to control them. Yet, both measures often fail because of the evolutionary adaptation of pathogen populations. Pesticides may negatively affect the environment and human health. Consequently, growers need to reduce fungicide use in favour of integrated pest management (IPM) that emphasizes cultural/genetic control. To achieve this, cropping systems need local adjustments, which requires comprehensive disease monitoring. However, current national monitoring [e.g. UK Department for Environment, Food and Rural Affairs (DEFRA) surveys conducted by ADAS uses visual scoring, which limits the number of fields sampled at a given budget, and has restricted accuracy/reproducibility. These factors limit the utility of the data.

The student will develop a novel method to measure the five diseases using digital imaging (DI) and artificial intelligence (AI). The method will exceed existing methods in accuracy and speed. When used in disease monitoring, the method will enable increased sample sizes and improved data quality. This will lead to a more informative disease monitoring, allowing policy-makers to learn more about IPM uptake, its effects, and boost its adoption.

Objective A. Develop a new method to detect the presence of each disease on wheat leaves using DI and AI techniques.

Objective B. Develop a new method to quantify the amount of each disease within wheat leaves using DI and AI techniques.

Objective C. Develop a portable platform to acquire high-quality images of wheat leaves in the field.

Objective D. Test the new method in subsets of DEFRA/ADAS's surveys.

Detection of disease presence is an image classification problem, while...