Acta Scientific Agriculture (ASAG)(ISSN: 2581-365X)

Review Article Volume 5 Issue 9

Emerging Trends of Artificial Intelligence in Agriculture

S Madhuri Paradesi*

Associate Professor, Department of Law, Sri Padmavathi MahilaViswaVidyalayam, Tirupati, Andhra Pradesh, India

*Corresponding Author: S Madhuri Paradesi, Associate Professor, Department of Law, Sri Padmavathi MahilaViswaVidyalayam, Tirupati, Andhra Pradesh, India.

Received: July 19, 2021; Published: August 24, 2021


  This article outlines and examines the meaning, benefits of Artificial intelligence (AI) in predicting its benefits in Agriculture through machine learning. While Artificial intelligence is the capacity of the system to grasp, comprehend, analyze and predict data, Machine learning Creates models through natural language programming (NLP) and facilitates the prediction. This process requires big data base. Data is the fundamental basis of AI. Instead of manually cultivating, AI through algorithm facilitates automatic search agricultural processes are feed to the system through machine learning model. The easy methods of farming will be ascertained and used for agriculture.

  In many countries AI is being used to predict data and to decide whether This is facilitated by AI through predictions referring to the data to understand a particular agricultural process is suitable for a land, what type of farming , labor are required are analysis . Therefore, it can be said that AI does the work of a human being though training in the form of program. The author is interested to bring to light the use of AI in Agriculture, its benefits to the farmers with relevant examples and its disadvantages with conclusion and suggestions for effective use of AI in this regard.

Keywords: Artificial Intelligence; Machine Learning; Algorithm; Supervised Learning; Unsupervised Learning


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Citation: S Madhuri Paradesi. “Emerging Trends of Artificial Intelligence in Agriculture". Acta Scientific Agriculture 5.9 (2021): 38-43


Copyright: © 2021 S Madhuri Paradesi. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.


Acceptance rate32%
Acceptance to publication20-30 days
Impact Factor1.014

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