Modeling plant disease occurrence predicting plant dise | 105069
An International Journal

Agricultural and Biological Research

ISSN - 0970-1907
RNI # 24/103/2012-R1


Modeling plant disease occurrence predicting plant diseases based on conditions

K. Jyothi* and G. Shankar Lingam

Global food security is seriously threatened by plant diseases, which annually result in large agricultural yield losses. Predicting and managing plant diseases are critical for sustainable agriculture. Soil conditions, including physical and chemical properties, play a vital role in plant health and disease development. This research paper presents an effective model for predicting plant diseases based on comprehensive soil condition data. We demonstrate how soil properties, such as moisture content, pH levels, nutrient content, and microbial composition, can be integrated into a predictive model to anticipate disease outbreaks and enable proactive disease management strategies. Our findings highlight the importance of considering soil conditions as a key factor in disease prediction and provide insights into the development of precision agriculture practices.

Journal Hilights
  • Abstracting and indexing in renowned databases
  • Expert editorial team
  • High quality articles
  • High visibility
  • International readership
  • Language editing
  • Membership
  • Online manuscript submission and tracking system
  • Rapid peer review process
  • Reprints of published articles
Journal is Indexed in:
  • BIOSIS Previews and Zoological Record which are part of the life sciences in Web of Science (WOS)
  • Euro Pub
  • Google Scholar
  • MIAR
  • Publons
Journal Flyer
Google Scholar Citation Report
Citation image
Peer Review Process Check
Publon image