Data Mining in Soil & Plant Nutrient Management, Recent Advances and Future Challenges in Organic Crops
S. Jeya Laksshmi1, V. Rama2, G. Suseendran3
1S. Jeya Laksshmi, Assistant Professor, Department of Computing Sciences, Vels Institute of Science, Technology & Advanced Studies VISTAS, Chennai (Tamil Nadu), India.
2V. Rama, Research Scholar, Department of Computing Sciences, VISTAS, Chennai (Tamil Nadu), India.
3Dr. G. Suseendran, Assistant Professor, Department of Computing Sciences, Vels Institute of Science, Technology & Advanced Studies VISTAS, Chennai (Tamil Nadu), India.
Manuscript received on 10 October 2019 | Revised Manuscript received on 19 October 2019 | Manuscript Published on 02 November 2019 | PP: 213-216 | Volume-8 Issue-2S11 September 2019 | Retrieval Number: B10350982S1119/2019©BEIESP | DOI: 10.35940/ijrte.B1035.0982S1119
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Data mining procedures are colossally regarded in the examination field of cultivating. The cultivating factors atmosphere, deluge, soil, pesticides, and fertilizers are the basic careful perspective to raise the age of yields. The key piece of agribusiness is Soil for yield creating. Examination of soil is a basic bit of soil asset the administrators in development. The earth examination is especially significant for cultivators to observe which sort of harvests to be made in a specific soil condition. The rule focal point of this work is to look at soil supplements utilizing data mining gathering techniques. A broad enlightening record of soil supplements status database was accumulated from the Department of Agriculture, Cooperation and Farmers Welfare. The database contains the estimation of soil supplements for each and every different state. This work takes some district of Tamil Nadu in India to look at the soil supplements. Specific sort’s earth has a different variety of improvements. This paper picks Nitrogen, Phosphorus, Potassium, Calcium, Magnesium, Sulfur, Iron, Zinc, and so on, supplements for investigating the earth upgrades utilizing Hybrid procedure of Neural framework. The execution of the portrayal computations is taken a gander at subject to the going with two factors: accuracy and execution time.
Keywords: Data Mining, Agriculture, Soil Nutrients, Classification, Hybrid Neural Network.
Scope of the Article: Data Mining