Crop Recommendation using Machine Learning Techniques
S. Mamatha Jajur1, Soumya N. G.2, G. T. Raju3
1S Mamatha Jajur, Department of CSE, RNS Institute of Technology, VTU, Bengaluru (Karnataka), India.
2Soumya N. G., Department of CSE, RNS Institute of Technology, VTU, Bengaluru (Karnataka), India.
3G. T. Raju, Department of CSE, RNS Institute of Technology, VTU, Bengaluru (Karnataka), India.
Manuscript received on 08 December 2019 | Revised Manuscript received on 16 December 2019 | Manuscript Published on 31 December 2019 | PP: 658-661 | Volume-9 Issue-2S December 2019 | Retrieval Number: B11061292S19/2019©BEIESP | DOI: 10.35940/ijitee.B1106.1292S19
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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: Precision agriculture (PA) allows precise utilization of inputs like seed, water, pesticides, and fertilizers at the right time to the crop for maximizing productivity, quality and yields. By deploying sensors and mapping fields, farmers can understand their field in a better way conserve the resources being used and reduce adverse affects on the environment. Most of the Indian farmers practice traditional farming patterns to decide crop to be cultivated in a field. However, the farmers do not perceive crop yield is interdependent on soil characteristics and climatic condition. Thus this paper proposes a crop recommendation system which helps farmers to decide the right crop to sow in their field. Machine learning techniques provide efficient framework for data-driven decision making. This paper provides a review on set of machine learning techniques to support the farmers in making decision about right crop to grow depending on their field’s prominent attributes.
Keywords: Precision Agriculture, Smart Framing, Crop Prediction, Crop Recommendation.
Scope of the Article: Machine Learning