• Shruti Rajendra Kudagi
• Prof. Dr.S. H.Patil
• Prof. Dr.Mrs. Sunita Dhotre

The Indian economy is mostly based on agricultural occupation. So the environmental factors like temperature, climate, moisture content, irrigation, soil fertility, minerals, sunlight, and variety of crop can affect the agriculture practices. Due to this the crop yield can be less. Farmer uses conventional methods so that they can judge the crop yield. But due to certain climatic changes farmers need to face huge loss. Climates are certain and specific but the weather is unpredictable sometimes this lead to loss in agriculture. Each type of crops need different environmental conditions this is threat to farmer. Machine learning is mainly used for predictive modeling based on existing dataset. In this paper tried to focus on survey on different papers which uses machine learning techniques to predict crop yield. Which helps us to select proper algorithms so that the model can predict crop yield with accuracy and better result.attributes , irrigation all matters deeply. The contribution of survey done tends to give machine learning approach so that model can be built to predict the sugarcane yield for plot with accuracy.

"Survey on prediction of crop yield by using different techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.457-460, June 2019, Available :http://www.jetir.org/papers/JETIR1907U92.pdf

"Survey on prediction of crop yield by using different techniques", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp457-460, June 2019, Available at : http://www.jetir.org/papers/JETIR1907U92.pdf