Data Mining in Soil & Plant Nutrient Management, Recent Advances and Future Challenges in Organic Crops

Jeyalaksshmi, S. and Raman, V. and Suseendran, G. (2019) Data Mining in Soil & Plant Nutrient Management, Recent Advances and Future Challenges in Organic Crops. International Journal of Recent Technology and Engineering, 8 (2S11). pp. 213-216. ISSN 2277-3878

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Abstract

Data Mining in Soil & Plant Nutrient Management, Recent Advances and Future Challenges in Organic Crops

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
11 2 2019 213 216 B10350982S1119 10.35940/ijrte.B1035.0982S1119 https://www.ijrte.org/wp-content/uploads/papers/v8i2S11/B10350982S1119.pdf https://www.ijrte.org/wp-content/uploads/papers/v8i2S11/B10350982S1119.pdf

Item Type: Article
Subjects: Computer Science Engineering > Data Science
Divisions: Computer Science
Depositing User: Mr IR Admin
Date Deposited: 10 Oct 2024 10:03
Last Modified: 10 Oct 2024 10:03
URI: https://ir.vistas.ac.in/id/eprint/9694

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