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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:10.55041/IJSREM36890

ECO-FERTILIZATION USING ML TECHNIQUE

Stream/Area:

-

Subject:

-

Paper ID:

10.55041/IJSREM36890

Volume:

8 |

8 |

Aug 2024

Pages:

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM36890

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

RS

RAPELLI SRIKANTH

A

A.SHRAVANI

Y

Y.BALRAJ

AG

ALURI GOPI

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Abstract

Farmers often have limited control over their use of fertilizers, but they can achieve higher yields and reduce fertilizer loss with expert guidance on the best practices for fertilizer use. Rainfall volume and timing are also crucial factors in nutrient loss, with moderate rainfall at the right moment aiding nutrient penetration and dissolution, while excessive rain can increase runoff and the risk of losing important nutrients like nitrogen, phosphorus, and potassium. To address these issues, this paper proposed a nutrient recommendation system that employs an updated version of the random forest algorithm, which is based on time-series data to predict the optimal quantity of nutrients needed for various crops based on rainfall patterns and crop fertility. By leveraging this method, farmers can improve soil fertility and reduce the potential for leaching and runoff, providing the optimum conditions for crop growth.

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Cite This Article

RAPELLI SRIKANTH, A.SHRAVANI, Y.BALRAJ, ALURI GOPI, "ECO-FERTILIZATION USING ML TECHNIQUE," International Journal of Scientific Research in Engineering and Management, vol. 8, no. 8, Aug 2024. https://doi.org/10.55041/IJSREM36890

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1/7/2024

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