A Perspective on the Application of Artificial Intelligence in Sustainable Agriculture with Special Reference to Precision Agriculture

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  • Research Associate, Institute of Rural Management Anand – 388001, Gujarat ,IN
  • Post-doctoral fellow and visiting scholar at IRMA, Pernambuco Federal University (UFPE-Brazil) ,BR




Agroecology, Agrometeorology, Artificial Intelligence, Efficiency, Sustainability


Agriculture has undergone rapid technological changes in the search for greater productivity. At the same time, environmental changes, agricultural crises from the possible repercussions of climate change and the different uses of land and technology make tools that look to minimise the negative aspects of the environment and human beings increasingly necessary. In this context, the concern with sustainability is imperative. Different agricultural systems have been trying to connect with this issue, making the term sustainable a field of conceptual, political, ideological, and power dispute. On this note, Artificial Intelligence (AI) can be used to enhance sustainable agriculture's growth prospects. Therefore, this paper analyses how AI could aid sustainable agriculture, keeping in mind the accessibility challenges for small and marginal farmers. The paper will also explore the prospects of agrometeorology and precision agriculture as a concept and how it would play a significant role in smart harvesting. Finally, the documents will also look to oversee the influence of AI in agroecology. The article will also explore the common grounds between Indian and Brazilian agriculture, especially the small and medium farmers scenario, their challenges in accessing this technology, and how the government could aid the use of these technologies through inclusive policy interventions.


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How to Cite

Raj, V. H. A., & de Carvalho, C. X. (2023). A Perspective on the Application of Artificial Intelligence in Sustainable Agriculture with Special Reference to Precision Agriculture. SDMIMD Journal of Management, 14(Special Issue), 1–13. https://doi.org/10.18311/sdmimd/2023/33006






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