Prediction of Plant Disease Using Artificial Intelligence

Plant diseases are a persistent threat to global food security due to their ability to damage crops. They account for 20–40% of loss of global food trade every year. The exploding global food trade, coupled with climate change, has led to the sustainability of native plant pests in the new environment, worsening the condition. Additionally, new plant pests and diseases continue to threaten staple crops. This sheds light on the need for the implementation of novel techniques to diagnose plant diseases to tackle the global food crises. Implementation of artificial intelligence (AI)-based methods such as machine learning (ML), deep learning (DL), and artificial neural networks can aid in overcoming such challenges by conducting early diagnosis of plant pests and diseases. In recent years, many research investigations conducted on plant disease detection using AI have offered valuable insights for agriculturists, botanical researchers, practitioners, and industrial professionals. The applications DL and ML methods for plant disease detection are growing rapidly. This chapter will shed light on recent cutting-edge research in this field, including the latest advancements involving AI-based plant disease detection. It will also address the trials and limitations related to the usage of AI-based methods for plant disease diagnosis.