International Journal of Chemical Studies
  • Printed Journal
  • Indexed Journal
  • Refereed Journal
  • Peer Reviewed Journal
P-ISSN: 2349-8528, E-ISSN: 2321-4902   |   Impact Factor: GIF: 0.565

Vol. 11, Issue 4 (2023)

A novel study of leveraging machine learning for detecting plant diseases


Author(s): Premakumari P and Dr. Srikanth GA

Abstract: The diagnosis of various plant diseases represents just one of the major farming aspects where digitization in agriculture has made tremendous strides. To achieve precision and accuracy also meet the steadily rising need for food, the focus of virtually every country has shifted towards mechanising agriculture. Plant disease identification is one of the major challenges in agriculture and has a considerable impact on crop production. Plant disease affects the nutritional value of vegetables, organic goods, vegetables, and grains. Since heavy loss is already underway and consequently financial losses are being monitored, timely and effective monitoring and evaluation processes are vital. Providing an extensive overview of the machine learning models that can be used to enhance the phase of identifying plant diseases in its infancy to strengthen grain security and the practicability in an agro-biological system.

Pages: 15-22  |  253 Views  78 Downloads

download (12511KB)

International Journal of Chemical Studies International Journal of Chemical Studies
How to cite this article:
Premakumari P, Dr. Srikanth GA. A novel study of leveraging machine learning for detecting plant diseases. Int J Chem Stud 2023;11(4):15-22.
 

Call for book chapter
International Journal of Chemical Studies