• Shubham Pathrikar
• Pranjali Gurav
• Kshitij Agrawal
• Govind Pole

The agricultural sector in India has gone through many changes, such as the green revolution which helped in revolutionizing the yield per hectare and many more such plans implemented by the government. Even though such developments have taken place there is a strong need to increase the production of crops to satisfy and sustain the Indian population. To increase the yield per hectare we propose making use of Machine Learning and Data Science to develop a system which would recommend proper crop taking into account various factors. The factors which will be taken into account will be soil pH, soil texture, soil NPK levels, soil’s electrical conductivity and many more. A lot of data is being generated due to the progress of IOT in agriculture, all that data can be used to develop machine learning models. These machine learning models will then help us to recommend proper crop suited for particular soil factors.

Machine Learning, Agriculture, Recommender Systems

"Crop Recommendation System using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.157-161, June-2019, Available :http://www.jetir.org/papers/JETIR1906A27.pdf

"Crop Recommendation System using Machine Learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp157-161, June-2019, Available at : http://www.jetir.org/papers/JETIR1906A27.pdf