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Fusion: Practice and Applications

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Online: 2692-4048 Print: 2770-0070
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Fusion: Practice and Applications
Full Length Article

Volume 6 • Issue 2 • PP: 57-63 • 2021

Crop Recommendation Using Machine Learning

Akshita Waldia 1*
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,
Pragati Garg 1
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,
Priyanka Garg 1
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,
Rachna Tewani 2
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,
Arun Kumar Dubey 1
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,
Anurag Agrawal 1
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1Bharati Vidyapeeth’s College of Engineering, New Delhi, India
2Data Scientist ,Great Learning, India
* Corresponding Author.
DOI https://doi.org/10.54216/FPA.060203
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Received February 02, 2021 Accepted August 30, 2021
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Abstract

The population of India is over one billion. Nearly 65 percent of the population of India lives in villages with the main occupation being agriculture. The diverse climatic conditions in the country result in the production of a large number of agricultural items. Many surveys have proved that the suicide rate of farmers is proliferating over years due to the selection of the wrong crop resulting in less yield. In some areas, farmers lack information about the composition of soil and weather conditions and may choose the wrong crop to sow which results in lesser yield. Production of crops depends on geographical parameters like humidity, rainfall, and properties of soil such as pH, and NPK content. Integration of technology with agriculture helps the farmer to improve his production. The main goal of agricultural planning is to achieve the maximum yield rate of crops by using a limited number of land resources. This paper mainly focuses on recommending the appropriate crop using ML Algorithms ( Decision Tree, Naive Bayes, Random Forest ) based on soil composition and weather conditions to maximize the yield of the farm and increase the economic condition of India’s farmers.

Keywords

Machine Learning Crop prediction Decision tree Naive Bayes Random Forest crop recommendation

References

[1] Van Klompenburg, Thomas, Ayalew Kassahun, and Cagatay Catal. "Crop yield prediction using machine learning: A systematic literature review." Computers and Electronics in Agriculture 177 (2020): 105709.

[2] Chougule, Archana, Vijay Kumar Jha, and Debajyoti Mukhopadhyay. "Crop suitability and fertilizers recommendation using data mining techniques." In Progress in Advanced Computing and Intelligent Engineering, pp. 205-213. Springer, Singapore, 2019.

[3] Pudumalar, S., E. Ramanujam, R. Harine Rajashree, C. Kavya, T. Kiruthika, and J. Nisha. "Crop recommendation system for precision agriculture." In 2016 Eighth International Conference on Advanced Computing (ICoAC), pp. 32-36. IEEE, 2017.

[4] Kalimuthu, M., P. Vaishnavi, and M. Kishore. "Crop prediction using machine learning." In 2020 Third International Conference on Smart Systems and Inventive Technology (ICSSIT), pp. 926-932. IEEE, 2020.

[5] Osman, Tousif, Shahreen Shahjahan Psyche, MD Rafik Kamal, Fouzia Tamanna, Farzana Haque, and Rashedur M. Rahman. "Predicting Early Crop Production by Analysing Prior Environment Factors." In International Conference on Advances in Information and Communication Technology, pp. 470-479. Springer, Cham, 2016.

[6] Shah, Ayush, Akash Dubey, Vishesh Hemnani, Divye Gala, and D. R. Kalbande. "Smart farming system: Crop yield prediction using regression techniques." In Proceedings of International Conference on Wireless Communication, pp. 49-56. Springer, Singapore, 2018.

[7] A. Sharma, A. Jain, P. Gupta and V. Chowdary, "Machine Learning Applications for Precision Agriculture: A Comprehensive Review," in IEEE Access, vol. 9, pp. 4843-4873, 2021, doi: 10.1109/ACCESS.2020.3048415.

[8] Kamatchi, S. Bangaru, and R. Parvathi. "Improvement of Crop Production Using Recommender System by Weather Forecasts." Procedia Computer Science 165 (2019): 724-732.

 

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Waldia, Akshita, Garg, Pragati, Garg, Priyanka, Tewani, Rachna, Dubey, Arun Kumar, Agrawal, Anurag. "Crop Recommendation Using Machine Learning." Fusion: Practice and Applications, vol. Volume 6, no. Issue 2, 2021, pp. 57-63. DOI: https://doi.org/10.54216/FPA.060203
Waldia, A., Garg, P., Garg, P., Tewani, R., Dubey, A., Agrawal, A. (2021). Crop Recommendation Using Machine Learning. Fusion: Practice and Applications, Volume 6(Issue 2), 57-63. DOI: https://doi.org/10.54216/FPA.060203
Waldia, Akshita, Garg, Pragati, Garg, Priyanka, Tewani, Rachna, Dubey, Arun Kumar, Agrawal, Anurag. "Crop Recommendation Using Machine Learning." Fusion: Practice and Applications Volume 6, no. Issue 2 (2021): 57-63. DOI: https://doi.org/10.54216/FPA.060203
Waldia, A., Garg, P., Garg, P., Tewani, R., Dubey, A., Agrawal, A. (2021) 'Crop Recommendation Using Machine Learning', Fusion: Practice and Applications, Volume 6(Issue 2), pp. 57-63. DOI: https://doi.org/10.54216/FPA.060203
Waldia A, Garg P, Garg P, Tewani R, Dubey A, Agrawal A. Crop Recommendation Using Machine Learning. Fusion: Practice and Applications. 2021;Volume 6(Issue 2):57-63. DOI: https://doi.org/10.54216/FPA.060203
A. Waldia, P. Garg, P. Garg, R. Tewani, A. Dubey, A. Agrawal, "Crop Recommendation Using Machine Learning," Fusion: Practice and Applications, vol. Volume 6, no. Issue 2, pp. 57-63, 2021. DOI: https://doi.org/10.54216/FPA.060203
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