A Systematic Review on Crop Leaf Disease Identification Using Machine Learning and Deep Learning Techniques

World Population is increasing drastically and is expected to be around 12.3 billion in 2100. With the increase in population, it becomes important to foster the basic needs of mankind suitably. To withstand larger food requirements, getting higher crop yields is important. However, challenges like crop diseases, environmental factors like soil type, soil moisture, nutrient contents in soil, climate change, etc., affect various crop yields severely. The modern technologies can help in minimizing the adverse effects of these factors on crop yields. The advent of advanced automation techniques in Artificial Intelligence (AI) & Machine Learning (ML) can help in automated detection of crop diseases more accurately. However, use of such automated techniques face several challenges. Current study attempts to present a systematic literature review (SLR) of the existing body of knowledge in crop disease recognition & classification using automated techniques. The review followed PRISMA guidelines & searched four major databases with a comprehensive search query. 60 relevant research studies were identified after filtering through systematic inclusion & exclusion criteria for further analysis. Each research article is examined for the crop species used, the dataset used, & the methodology used. In each of the studied research papers, we looked at the performance measures utilized to assess the overall acquired findings for crop disease diagnosis & classification. It is observed that such systems have great potential to improve food security & agricultural productivity. However, more research is needed to overcome the challenges & limitations of the current methods and to ensure their validity & reliability in different settings and platforms. The readers of this study could acquire challenges faced by researchers in automated crop disease identification systems & their potential solutions to improve the performance of advanced algorithms.