Comprehensive Study and Review of Thirty Key Research Contributions on Artificial Intelligence in the Field of Agricultural

Abstract

Artificial Intelligence (AI) is revolutionizing the agricultural sector by enhancing efficiency, productivity, and sustainability. This review paper analyzes 30 research studies that explore AI applications in agriculture, including precision farming, crop disease detection, smart irrigation, agricultural robotics, and supply chain optimization. The studies highlight the role of AI-driven technologies such as machine learning, deep learning, computer vision, and Internet of Things (IoT) in improving decision-making and resource management. Key findings suggest that AI enhances crop yield predictions, automates pest and disease detection, and optimizes water usage, contributing to sustainable farming practices. However, challenges such as high implementation costs, data privacy concerns, and limited access to AI technology in developing regions remain significant barriers. This paper provides insights into current advancements, challenges, and future research directions to bridge the gap between AI innovation and practical agricultural applications.

Introduction

Agriculture is crucial to global food security but faces challenges like unpredictable weather, pests, inefficient resource use, and labor shortages. Artificial Intelligence (AI) is emerging as a transformative solution in modern farming, enhancing precision agriculture, smart irrigation, disease detection, and automation through technologies like machine learning, IoT, and computer vision.

A review of 30 research studies shows how AI improves agricultural efficiency, productivity, and sustainability. Applications include real-time monitoring, predictive analytics, and the use of drones, robotics, and climate forecasting. However, challenges remain—high costs, data privacy concerns, and limited rural access.

Key Literature Insights:

1. Di Vaio et al. (2022):
   Explores AI in sustainable agri-food systems. Highlights AI’s role in precision farming, waste reduction, and supply chain transparency, aligning with UN SDGs (Zero Hunger & Responsible Consumption). Emphasizes policy and stakeholder collaboration.

2. Yu et al. (2021):
   Focuses on AI’s impact on food security via improved productivity, resource use, and distribution. Highlights use of remote sensing and big data. Points out challenges like data scarcity and ethical concerns, and calls for policy support.

3. Kamal et al. (2023):
   Reviews AI in precision agriculture, including real-time monitoring, automated decision-making, and robotics. Discusses the importance of user-friendly tools, technical training, and collaboration for wider adoption.

4. Lewis et al. (2022):
   Examines AI-powered agricultural robotics for tasks like planting, harvesting, and crop monitoring. Highlights benefits like reduced labor and enhanced accuracy, but also addresses technical and cost-related barriers.

Overall Contribution:

The paper offers a comprehensive review of AI’s role in agriculture, highlighting both its transformative potential and adoption challenges, and provides guidance for future research, policy, and practical implementation toward sustainable, tech-driven farming.

Conclusion

The comparison of the five papers underscores the transformative potential of Artificial Intelligence (AI) in revolutionizing agriculture across diverse domains, including precision farming, smart irrigation, supply chain management, and disease detection. Each study highlights AI’s ability to enhance productivity, optimize resource use, and promote sustainability by providing data-driven insights and enabling real-time decision-making. While the applications vary, the common outcomes emphasize improved efficiency, reduced waste, and better alignment with global sustainability goals, such as the United Nations Sustainable Development Goals (SDGs). However, challenges like high implementation costs, data privacy concerns, and the need for technical expertise remain significant barriers to widespread adoption. To fully realize AI’s potential, future efforts must focus on policy support, interdisciplinary collaboration, farmer training, and the development of scalable, user-friendly solutions. By addressing these challenges and fostering innovation, AI can play a pivotal role in building a more sustainable, resilient, and efficient agri-food system for the future.

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Copyright

Copyright © 2025 Dr. Goldi Soni, Paras Kukreja, A Yash Govind. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.