• Gadhiraju HemaVallika
• M Naga Keerthi

India is an agricultural country; its economy predominantly depends on agriculture yield growth and agro-industry products. But crop yield depends on the environmental and soil related attributes, hence traditional methods of agriculture are used to decide on the type of crop to grow based on rain fall & weather conditions. These traditional methods to grow same crop each year sometimes fails to produce high yield. In this paper a Machine learning algorithm is implemented to suggest a crop based on the various attributes like location, and PH value (alkalinity of the soil). Apart from these, the values of nutrients like nitrogen (n), phosphorous (p), and potassium (k). This dataset is used to train the machine learning algorithm for building a prediction model. The system comes with a model to be precise and accurate in predicting crops and delivering the end user with proper recommendations about the required crop and fertilizer based on atmospheric and soil parameters of the land.

Soil attributes, Crop recommendation, Fertilizer, Python, Random Forrest algorithm.

"Crop Recommendation And Fertilizer Suggestion Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 7, page no.d328-d336, July-2024, Available :http://www.jetir.org/papers/JETIR2407332.pdf

"Crop Recommendation And Fertilizer Suggestion Using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 7, page no. ppd328-d336, July-2024, Available at : http://www.jetir.org/papers/JETIR2407332.pdf