Soil Testing and Crop-Suggestion Using Data Mining

Soil Testing and Crop-Suggestion Using Data Mining

Authors

  • Sruthimol Kurian ktu
  • Priya Thomas

DOI:

https://doi.org/10.5281/zenodo.6180525

Keywords:

Data mining, Soid data set, Classification Techniques, Agriculture

Abstract

Agriculture is the most essential component of
Indian economic system. To increase yield production, many
factors are responsible. Data mining plays an important role in
agriculture sector. Data mining is the process of mining
important information from a collection of huge data set and
transform this into an understandable form for future use. There
for the aim of this work is to predict soil type by using data
mining classification techniques.
In this study, soil dataset containing soil test outcomes has
been used to apply various classification strategies in data
mining. Soil type deals with the categorization of soil into specific
soil classes as “very low”, “low”, “medium”, “high”, and “very
high” on the idea of % of nutrient determined within the soil and
on the basis of these lessons crops are recommended for a soil
portion.

Published

2023-02-23

How to Cite

Sruthimol Kurian, & Priya Thomas. (2023). Soil Testing and Crop-Suggestion Using Data Mining. National Conference on Emerging Computer Applications, 4(1), 31–33. https://doi.org/10.5281/zenodo.6180525
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