  The agricultural sector plays an essential role in the economic growth of a
country. Specifically, in an Indian context, it is the critical source of
livelihood for millions of people living in rural areas. Plant Disease is one
of the significant factors affecting the agricultural sector. Plants get
infected with diseases for various reasons, including synthetic fertilizers,
archaic practices, environmental conditions, etc., which impact the farm yield
and subsequently hinder the economy. To address this issue, researchers have
explored many applications based on AI and Machine Learning techniques to
detect plant diseases. This research survey provides a comprehensive
understanding of common plant leaf diseases, evaluates traditional and deep
learning techniques for disease detection, and summarizes available datasets.
It also explores Explainable AI (XAI) to enhance the interpretability of deep
learning models' decisions for end-users. By consolidating this knowledge, the
survey offers valuable insights to researchers, practitioners, and stakeholders
in the agricultural sector, fostering the development of efficient and
transparent solutions for combating plant diseases and promoting sustainable
agricultural practices.
