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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM33419
Volume:
8 |
5 |
May 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Agriculture is one of the most important components of our society. Soil is a critical factor for a successful agriculture. The composition of soil differs from soil to soil. The Growth of Crops is affected by these chemical features of soil. Choosing the right type of crops for that particular type of soil is also important. Machine Learning techniques can be used to classify the soil series data. The results of such classification can further be combined with crop dataset to predict the crops that are suitable for the soil series of a particular region and its climatic conditions. Soil dataset and crop dataset are used. The datasets comprise of chemical attributes and geographical attributes of soil and crops. Algorithms like SVM and Ensembling technique can be used to classify the soil series data and predict the suitable crops.
KEYWORDS
Publication Date
12/31/45419
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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