Crop Selection and it’s Yield Prediction
Aksheya Suresh1, K. Monisha, R. Pavithra, B. Marish Hariswamy2
1Aksheya Suresh, B.Tech., M.E., Assistant Professor in Rajalakshmi Engineering College. K. Monisha, Student, Rajalakshmi Engineering College, Computer Science and Engineering, Chennai, India.
2R. Pavithra Student, Rajalakshmi Engineering College, Computer Science and Engineering, Chennai, India.
3Marish Hariswamy.B, Student, Rajalakshmi Engineering College,Computer Science and Engineering, Chennai, India.
Manuscript received on March 15, 2020. | Revised Manuscript received on March 24, 2020. | Manuscript published on March 30, 2020. | PP: 4126-4128 | Volume-8 Issue-6, March 2020. | Retrieval Number: F9191038620/2020©BEIESP | DOI: 10.35940/ijrte.F9191.038620
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The field of Agriculture plays a major role in the Indian economy. This sector helps to meet the basic needs of human and their civilization. Hence agriculture would be the enterprise in the globe. Considering the parameters of the agriculture, selection of crops plays a very vital role in farming. The proposed model for Crop selection and it’s yield prediction mainly focusses on the season and location to display the desired crop for cultivation . This requirement is implemented with Machine Learning algorithms like Decision tree for classification and Linear regression for yield prediction to maximize the crop yield. This model helps the farmers to know about the correct crop to be cultivated in a particular location . And also gives a approximate percentage of yield based on the data available in the dataset. Thus selecting crop for cultivation becomes a easier task for farmers because selection of correct crop for their location is precisely implemented using this project.
Keywords: Decision tree, Linear Regression, Crop selection , Yield Prediction.
Scope of the Article: Regression and Prediction.