Agricultural Data Mining for Crop Recommendation and Yield Prediction

  • Vijaya Prakash B Department of Agriculture Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore- 641062, Tamil Nadu, India.
  • Tajuddin A Department of Agriculture Engineering, Sri Shakthi Institute of Engineering and Technology, Coimbatore- 641062, Tamil Nadu, India.
Keywords: Data Mining, Crop Recommendation, Potassium, Nitrogen, Phosphorous, Crop Rotation

Abstract

This structure is considered to predict the best harvest suitable for the agronomists' area. It also suggests farming strategies for crops such as diverse farming, spacing, irrigation, sow processing, etc. along with fertilizer and pesticide proposals.  This is done on the basis of historical soil standards of the area and estimating crop and weather costs. Further, cost prediction is done based on Linear Regression to aid in ranking the crops recommended. India is defined as an agricultural country, where recommendations are given in traditional ways. In a Present-day, recommendations are based on farmers communicate between farmers, experts and various experts have a variety of recommendations. Recommendation can be provided to farmers who use past agricultural activities data. The application provides recommendations to farmers to determine the appropriate fertilizer and crop. This application can be used to increase crop yield and also recommend suitable crop.

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References

[1] A Model for Prediction of Crop Yield, "International Journal of Computational Intelligence and Informatics, Vol. 6: No. 4, March 2017.
[2] Satish Babu (2013), ‘A Software Model for Precision Agriculture for Small and Marginal Farmers’, at the International Centre for Free and Open Source Software (ICFOSS) Trivandrum, India.
[3] Rakesh Kumar, M.P. Singh, Prabhat Kumar and J.P. Singh (2015), ’Crop Selection Method to Maximize Crop Yield Rate using Machine Learning Technique’, International Conference on Smart Technologies and Management for Computing, Communication, Controls, Energy and Materials (ICSTM).
[4] (Soil Test Information | Recommended Fertilizers) Agri. Dept, "Soil Health Card ", February, 2015.
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[6] Tapas Ranjan Baitharua, Subhendu Kumar Panib (2016), ‘Analysis of Data Mining Techniques for Healthcare Decision Support
[7] Satish Babu (2013), ‘A Software Model for Precision Agriculture for Small and Marginal Farmers’, at the International Centre for Free and Open Source Software (ICFOSS) Trivandrum, India.
Published
2020-10-30
How to Cite
(1)
B, V. P.; A, T. Agricultural Data Mining for Crop Recommendation and Yield Prediction. ijceae 2020, 2, 93-97.
Section
Articles



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