• Swathi B S
• Vidya N L
• Swathi B S
• Sushmitha v Patel

Yield prediction is very popular among farmers these days, which particularly contributes to the proper selection of crops for sowing. This makes the problem of predicting the yielding of crops an interesting challenge. The kind of crops predictions is the toughest task for agriculture domain. Agriculture crops growth depends on different parameters, namely weather, soil characteristics, soil moisture and surface temperature. In our project, agriculture crop grow data are collected from different sensors from surface of farmland and lot of explorative data analysis is done. Further various regression models like linear, multi linear, support vector regression are tested for the effective kind of crops predictions. This work gives a better prediction for the farmers to plant which kind of crops to their farm field based on above mention parameters to improve the productivity. In our proposed model, we use machine learning techniques to fetch the crop prediction by analyzing the location using GPS module and fetch the data based on it. A system is been proposed which will gather information about all the crops that are cultivated from different places so that the farmers can use the system to know about the on growing crop details and to predict the best crop that allows him to get more profit.

Crop Analysis; Crop Yield; Data mining; Machine Learning; Prediction.

"Loctation based crop prediction using data mining and machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 5, page no.788-791, May 2020, Available :http://www.jetir.org/papers/JETIR2005423.pdf

"Loctation based crop prediction using data mining and machine learning", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 5, page no. pp788-791, May 2020, Available at : http://www.jetir.org/papers/JETIR2005423.pdf