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Application of Machine Learning Algorithms in Agriculture: An Analysis

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Emerging Trends in Data Driven Computing and Communications

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Abstract

Machine learning is being rapidly adopted in various industries: According to Research and Markets, the machine learning market is projected to grow to $8.81 billion by 2022, at a compound annual growth rate of 44.1%. One of the main reasons for its increasing use is that companies are collecting big data from which they need to obtain valuable information. Machine learning is an efficient way to make sense of that data. In the current situation, we are talking about the emerging concept of smart farming that makes farming more efficient and effective with the help of high-precision algorithms. The mechanism that drives it is machine learning, the scientific field that gives machines the ability to learn without being strictly scheduled. It has emerged alongside big data technologies and high-performance computing to create new opportunities to unravel, quantify, and understand data-intensive processes in agricultural operational environments. This paper reviews the exiting techniques and methods of machine learning applicable in the agriculture sector.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, College of Technology & Engineering, MPUAT, Udaipur, India

    Kalpana Jain & Naveen Choudhary

Authors
  1. Kalpana Jain
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  2. Naveen Choudhary
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Editor information

Editors and Affiliations

  1. Department of Electronics and Communication Engineering, Geetanjali Institute of Technical Studies, Udaipur, India

    Rajeev Mathur

  2. Department of Computer Science and Engineering, Rajasthan Technical University, Kota, India

    C. P. Gupta

  3. Department of Electronics and Communication Engineering, Indian Institute of Science Bangalore, Bengaluru, India

    Vaibhav Katewa

  4. Department of Computer Science, Namibia University of Science and Technology, Windhoek, Namibia

    Dharm Singh Jat

  5. Department of Mathematics, National Institute of Technology, Hamirpur, Himachal Pradesh, India

    Neha Yadav

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Jain, K., Choudhary, N. (2021). Application of Machine Learning Algorithms in Agriculture: An Analysis. In: Mathur, R., Gupta, C.P., Katewa, V., Jat, D.S., Yadav, N. (eds) Emerging Trends in Data Driven Computing and Communications. Studies in Autonomic, Data-driven and Industrial Computing. Springer, Singapore. https://doi.org/10.1007/978-981-16-3915-9_12

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  • DOI: https://doi.org/10.1007/978-981-16-3915-9_12

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-3914-2

  • Online ISBN: 978-981-16-3915-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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