Artificial Intelligence in Agriculture: Innovations, Challenges, and Future Prospects

This review explores the application of AI technology in agriculture to address challenges such as declining manual labor, limited arable land, and the growing disparity between food production and the increasing global population. AI is presented as a promising solution, with advancements driven by scientists worldwide. Artificial Intelligence (AI) plays a crucial role in optimizing farming practices by analysing data from sensors, satellites, and drones. Applications include monitoring soil health, crop growth, and weather patterns to enhance yields while minimizing resource utilization. AI-powered tools, such as advanced irrigation systems and fertilizer management, ensure efficient use of inputs. The use of robots in agriculture has significantly improved productivity, making farming more efficient and widely adopted. AI techniques offer real-time data, reducing human error and enhancing decision-making. The research highlights that modern AI technology and methods outperform traditional farming methods with minimal human intervention and in a shorter time frame. The review also delves into the development of agricultural robots, highlighting various examples of robots designed for specific tasks within the agricultural industry. The review discusses the challenges faced in applying agricultural robots, particularly the unpredictability of real-world environments. Despite these challenges, it underscores significant advancements in this field and the promising prospects for the future of agricultural robotics.

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Publication Details

Journal
Journal of Scientific Research and Reports
Published
2025-03-22
DOI
https://doi.org/10.9734/jsrr/2025/v31i32900
Citations
2
Primary Topic
Smart Agriculture and AI
Type
article
Field-Weighted Citation Impact
3.50
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article

Artificial Intelligence in Agriculture: Innovations, Challenges, and Future Prospects

Pravin Sukhadeo Gaikar, V. N. Anap, R. M. Jadhav, S. H. Lohale
2 citations
Journal of Scientific Research and Reports
Smart Agriculture and AI
3.50
article

Artificial Intelligence in Agriculture: Innovations, Challenges, and Future Prospects

Pravin Sukhadeo Gaikar, V. N. Anap, R. M. Jadhav, S. H. Lohale
article en
2 citations

Abstract

This review explores the application of AI technology in agriculture to address challenges such as declining manual labor, limited arable land, and the growing disparity between food production and the increasing global population. AI is presented as a promising solution, with advancements driven by scientists worldwide. Artificial Intelligence (AI) plays a crucial role in optimizing farming practices by analysing data from sensors, satellites, and drones. Applications include monitoring soil health, crop growth, and weather patterns to enhance yields while minimizing resource utilization. AI-powered tools, such as advanced irrigation systems and fertilizer management, ensure efficient use of inputs. The use of robots in agriculture has significantly improved productivity, making farming more efficient and widely adopted. AI techniques offer real-time data, reducing human error and enhancing decision-making. The research highlights that modern AI technology and methods outperform traditional farming methods with minimal human intervention and in a shorter time frame. The review also delves into the development of agricultural robots, highlighting various examples of robots designed for specific tasks within the agricultural industry. The review discusses the challenges faced in applying agricultural robots, particularly the unpredictability of real-world environments. Despite these challenges, it underscores significant advancements in this field and the promising prospects for the future of agricultural robotics.

Journal of Scientific Research and ReportsVol. 31(3)
Department of Biotechnology (IN), Montfort Social Institute (IN)
Zero hunger
Openalex Percentile: Top 9%
Smart Agriculture and AI
3.50
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Artificial Intelligence in Agriculture: Innovations, Challenges, and Future Prospects — Pravin Sukhadeo Gaikar, V. N. Anap, et al. · Journal of Scientific Research and Reports (2025) | TGRS Research Map | TGRS