Automatic identification of diseases in grains crops through computational approaches: A review

Abstract

Agricultural productivity significantly contributes to every country's economy. The grain plants such as wheat, rice, corn (maize), barley, oats, rye, millet, and sorghum are commonly grown across the world. The pest and various diseases in the grain plants severely affect major production and cause heavy losses in the global economy. Monitoring of health and early diagnosing of diseases in grains plants is a critical task for sustainable agriculture. The information on early diagnosis of several diseases can facilitate the control of diseases through proper selection of pest control techniques to improve the grains productivity. The manual identification of the disorders in grains plants can lead to inaccurate measurements of pesticides. While several papers on grain diseases identification through intelligent techniques have been published in recent years, there has been no clear attempt to study these papers systematically to describe various phases of diagnosis system such as image preprocessing, segmentation, feature extraction, features selection, and classification methods. In this context, a total of 109 peer-reviewed articles reporting to identify the diseases at the early stage to increase the production of the five most-produced grains in the world such as maize, rice, wheat, soybean, and barley are reviewed, ranging in publication date from 2001 to 2020. The article also presents a detailed taxonomy of grain plant leaf diseases. The study found that there are still many issues that’s need to be addressed in each phase of the automated disease detection system. The pros and cons of reviewed computational method is explored and future directions are highlighted. The survey outcomes reveal that the existing automated detection and classification methods for grain plants diseases is still infancy. Hence novel fully automated tools are necessary for the process of detection and classification diseases in grain plants.