Crop and Fertilizer Recommendation System
N.V.S.S.POORNIMA
, Dr. P.HIMA KEERTHI , K.TEJA SRI SAI , P.AKHILA , P.S.L.N.SAI SIREESHA
Crop recommendation, Fertilizer recommendation, Machine Learning, Python, Pillow, Flask
Crop recommendation and fertilizer recommendation are key components of modern agriculture that are crucial for
improving crop yield, soil fertility, and sustainability. In this study, we reviewed the existing strategies for crop and fertilizer recommendations, as well as the challenges faced in implementing these recommendations. We also examined recent advances in crop and fertilizer management techniques, including precision agriculture, integrated pest management, and soil health management. Precision agriculture involves the use of technology to optimize crop production, such as sensors and mapping tools that help farmers identify areas of the field that need more or less fertilizer or irrigation. Integrated pest management involves using multiple approaches, such as crop rotation and biological controls, to manage pests and minimize the use of pesticides. Soil health management focuses on improving soil quality through practices such as cover cropping and reduced tillage, which can lead to better crop yields and soil health over the long term. But now-a-days, food production and prediction is getting depleted due to unnatural climatic changes, which will adversely affect the economy of farmers by getting a poor yield and also help the farmers to
remain less familiar in forecasting the future crops for this project we use 5 different algorithms they are XG Boost, Decision Tree, AdaBoost, Support vector machine and Random Forest Apart from these algorithms Decision Tree algorithms gives better accuracy compared to remaining algorithms.
"Crop and Fertilizer Recommendation System", IJNRD - INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT (www.IJNRD.org), ISSN:2456-4184, Vol.8, Issue 3, page no.c627-c632, March-2023, Available :https://ijnrd.org/papers/IJNRD2303270.pdf
Volume 8
Issue 3,
March-2023
Pages : c627-c632
Paper Reg. ID: IJNRD_189197
Published Paper Id: IJNRD2303270
Downloads: 000118869
Research Area: Computer Science & Technology
Country: Visakhapatnam, Andhra Pradesh, 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
