• Reshma Mandal
• Sandhya Tawri
• Sanskriti Sahu
• Darshana Sahu
• Ranjeeta Krishan

India is the second largest country in agriculture production and majority of people in India opt the field of agriculture as their profession. Farmers just keep growing the same crops over and over as they don’t know much about soil condition so they use random number of fertilisers to grow crops. This will eventually increase the acidification of soil, destroy the nourishment of the soil and damages the upper layer of soil. So, to overcome these scenarios we have, designed a Machine Learning model for farmers. Our model helps the farmer by suggesting the best crop to be grown according to the weather and soil conditions. Hence by using our model farmers can know about different type of crops they have to grow so that they can increase their production which leads to increase their profit and minimise the soil pollution. The main objective is to obtain a better variety of crops that can be grown over the season. Crop prediction attributes are defined by multiple factors such as genotype, climate and the interactions between the user who are basically the farmers and the system .

Machine learning, Agriculture, Modern Farming

"A CROP RECOMMENDATION MODEL USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 4, page no.l571-l581, April-2024, Available :http://www.jetir.org/papers/JETIR2404B76.pdf

"A CROP RECOMMENDATION MODEL USING MACHINE LEARNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 4, page no. ppl571-l581, April-2024, Available at : http://www.jetir.org/papers/JETIR2404B76.pdf