Empirical Study of Crop-disease Detection and Crop-yield Analysis Systems: A Statistical View

In crop-imagery different algorithms have been proposed over the years which determine crop-growth, crop-diseases, crop-yield etc., using a series of image processing steps. As large number of architectures are available in the area of crop imaging, selection of particular algorithm is a very much crucial task for getting optimum results from the set off application. A lot of research is required for this, which increases the delay in the system design, to reduce this delay this paper reviews the best algorithm set in terms of their statistical parameter. The error rate and accuracy of different algorithms is compared in order to understand performance of different algorithms. This will facilitate the investigator to search out the most effective practices in connection with crop disease detection and crop yield prediction.