Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

@article{157476,
        author = {Mehreen Choudhary and Dr. Simmi Dutta and Dr. Jyoti Kumar Mahajan},
        title = {Fuzzy Inference system for soil fertility crop prediction},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {9},
        number = {7},
        pages = {257-260},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=157476},
        abstract = {Economic growth of different countries depends upon agriculture. One of such country is India. Agriculture is inspired by correctly identifying soil for harvesting crops. The technology to this end plays critical role. This paper proposed a fuzzy based mechanism for detecting the fertility of soli. For this purpose, dataset corresponding to soil is extracted from Kaggle. The dataset attributes include levels of Nitrogen, phosphorous, potassium and pH levels. Nutrients levels of these attributes fed into the fuzzy system. Three predictors including Ph levels, Nitrogen and phosphorus are major constituents of soil fertility as detected from correlation analysis. This study concludes that fuzzy based system is effective enough in predicting the fertility of cultivating crops including banana, maize, rice, grapes coconut etc.. This means Fuzzy based inference system (FIS) can be used for effective decision-making regarding soil fertility. },
        keywords = {Fuzzy system, Soil fertility, Inference system},
        month = {},
        }