A Survey of using Data Mining Techniques for Soil Fertility

  • Authors

    • Madhuri Kommineni
    • Someswari Perla
    • Divya Bharathi Yedla
    2018-03-18
    https://doi.org/10.14419/ijet.v7i2.7.11096
  • Data Mining, K-Means, Soil Fertility, Soil Nutrient, SVM,
  • Abstract

    Data Mining is a technique which focuses on large data sets to extract information for prediction and discovery of hidden patterns.  Data Mining is applicable on various areas like healthcare, insurance, marketing, retail, communication, agriculture. Agriculture is the backbone of country’s economy. It is the important source of livelihood. Agriculture mainly depends on climate, topography, soil, biology. Agricultural Mining is a technology which can bring knowledge to agriculture development. Data Mining in agriculture plays a role in weather forecasting, yield prediction, soil fertility, fertilizers usage, fruit grading, plant disease and weed detection. The current study presents the different data mining techniques and their role in context of soil fertility, nutrient analysis.

     


  • References

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  • How to Cite

    Kommineni, M., Perla, S., & Bharathi Yedla, D. (2018). A Survey of using Data Mining Techniques for Soil Fertility. International Journal of Engineering & Technology, 7(2.7), 917-918. https://doi.org/10.14419/ijet.v7i2.7.11096

    Received date: 2018-04-05

    Accepted date: 2018-04-05

    Published date: 2018-03-18