Vol. 8, Issue 11, Part K (2024)

Artificial intelligence and machine learning in soil analysis innovations for sustainable agriculture: A review

Author(s):

Kuldeep Kumar, Avimanyu Palit, Simran Sindhu, Divya D, Yogita, Rajeeb Lochan Moharana, Smriti Hansda and Anil Kumar

Abstract:

Soil analysis is one important tool in sustainable agriculture since they represent information in terms of soil health and fertility to farmers; hence, there is an optimum resource management. Conventional methods of soil analysis though effective are normally time-consuming, expensive, and often labor-intensive. With the appearance of Artificial Intelligence (AI) and Machine Learning (ML), it has been no more than a transformative innovation in the field of soil analysis. This paper addresses some recent innovations of AI and ML application for soil analysis, focusing on techniques such as remote sensing, spectral analysis, predictive modeling, and precision agriculture, all of which help sustain farming practices.

Pages: 869-878  |  4198 Views  3695 Downloads

How to cite this article:
Kuldeep Kumar, Avimanyu Palit, Simran Sindhu, Divya D, Yogita, Rajeeb Lochan Moharana, Smriti Hansda and Anil Kumar. Artificial intelligence and machine learning in soil analysis innovations for sustainable agriculture: A review. Int. J. Adv. Biochem. Res. 2024;8(11):869-878. DOI: 10.33545/26174693.2024.v8.i11k.2973