Examination on Advanced Machine Learning Techniques for Plant Leaf Disease Detection from Leaf Imagery

Abstract

Agriculture is the backbone of countries as it feeds people across the globe. With respect to agriculture in India, the total geographical area for agriculture in India is 328 million hectares. The new area sown is 142 million hectares. 190.8 million hectares is the gross cropped area. It reveals the significance of agriculture and its related research. With technological innovations emerged, now it is the era where there is scope of increasing the research towards precision agriculture (PA). PA is the agriculture where technology-driven procedures are followed to do right things at right time. This will increase productivity and saves time, money and effort. Agricultural plat leaf disease detection is an important research area in agriculture that is related to PA. In this context, image processing and machine learning techniques assume significance to capture live leave imagery from fields and detect diseases. Automatic detection of disease based on agricultural plant leaves has its utility in real world agricultural applications. This is the motivation behind taking up this research. This paper throws light on different kinds of plant diseases, various advanced machine learning and image processing methods to detect plant diseases. The innovations in technologies lead to automatic detection of diseases even from remote places and take necessary steps to ensure that the agricultural crops are healthy and yield desired harvest. This survey also provides important research gaps that will help in further research towards realizing PA.