DEVELOPMENT OF MACHINE LEARNING BASED APPLICATION FOR CROP DISEASE IDENTIFIED RECTIFICATION AND FERTILIZER RECOMMENDATION
SANJITH K
, SANJAY S , ASRATH J
Machine learning , Disease identification, dataset, Decision tree-based algorithm,fertilizer recommendation.
The agricultural industry is facing major challenges due to the increasing global population and climate change. One of the most significant challenges is crop disease, which reduces yield and quality. Therefore, there is a pressing need to develop innovative solutions for early detection, Disease identification, and rectification of crop diseases. Machine learning (ML) techniques have shown great potential in agriculture for predicting crop yield, identifying pests, and classifying crop diseases, and recommending suitable chemicals for rectification In this project, we propose a machine learning-based application for crop disease identification and rectification, as well as fertilizer recommendation. The application will be trained using a large dataset of crop images, and will use image recognition techniques to identify diseases. The identified diseases will be rectified using a Decision tree-based algorithm, and the optimal fertilizer recommendations will be provided based on the type of crop and soil conditions. The proposed application has the potential to revolutionize the agricultural industry by providing accurate and efficient crop disease management and fertilizer recommendations, which can increase crop yield and improve the quality of agricultural products.
"DEVELOPMENT OF MACHINE LEARNING BASED APPLICATION FOR CROP DISEASE IDENTIFIED RECTIFICATION AND FERTILIZER RECOMMENDATION", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.b497-b514, March-2023, Available :https://ijnrd.org/papers/IJNRD2303160.pdf
Volume 8
Issue 3,
March-2023
Pages : b497-b514
Paper Reg. ID: IJNRD_188579
Published Paper Id: IJNRD2303160
Downloads: 000118827
Research Area: Engineering
Country: Erode, Tamil Nadu, India
ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.76 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator
Publisher: IJNRD (IJ Publication) Janvi Wave
