Plant Disease Prediction using Image Processing and Soft Computing Algorithms: A Review

Abstract

Plant production, a crucial factor in accelerating agricultural growth, is majorly impeded by presence of plant diseases. Thus, identification of plant diseases using suitable technique is of enormous importance. The current technological advancement has paved the way for diverse approaches for determining the nature, severity, and stage of plant diseases, where imaging processes showed a great promise. In this regard, this work reviews such image processing techniques where modern technology, with increased precision and accuracy, is used to compare the cases where the human perception approach is utilized. Such findings demonstrate the usefulness and significance of utilizing the image processing and soft computing algorithms in the investigation of plant diseases. Despite the limitations of cost and emergence of new strains of plant diseases, the current approaches remain effective in identification of disease in plant and can be improved to enhance the accuracy of the results.