Advancing Agronomy: Robotics and AI in Crop Management and Sustainability

Agronomy is now embracing advanced technologies to enhance the production and management of crops for food, fibre, and energy. Robotics and AI in agronomy are not just about mechanising tasks; they represent a paradigm shift towards precision agriculture, where every aspect of farming, from soil health to plant growth, can be monitored and managed with unprecedented accuracy and efficiency. This approach dovetails with the agronomic emphasis on understanding and manipulating the complex interplay of biotic and abiotic factors in ecosystems. However, integrating such technologies also brings challenges in terms of adaptability, cost, and the need for specialised skills. Furthermore, it raises crucial questions about the future training of agronomists and the role of these technologies in sustainable and equitable food production, especially in the face of global challenges like climate change. This field of study is crucial for propelling agronomy forward, expanding the limits of sustainable, efficient, and responsible crop production.

The primary goal is to address the critical problem of integrating robotics, automation, and artificial intelligence (AI) into agronomy to enhance crop production efficiency, sustainability, and resilience. This integration is crucial in the context of increasing global food demands, climate change challenges, and the necessity for sustainable farming practices. Recent advances in robotics have brought forward autonomous tractors, drones for precision crop monitoring, and robotic harvesters, significantly reducing labour requirements and optimising resource use. AI and machine learning have made strides in predictive analytics, offering insights into crop health, yield prediction, pest and disease management, and soil health monitoring, enabling more informed agronomic decisions.

To gather further insights into the integration of robotics, automation, and AI into agronomy, we welcome articles addressing, but not limited to, the following themes:
- Advances in robotic systems for planting, harvesting, and crop management.
- Utilisation of AI and machine learning in predictive analytics for crop health and yield optimisation.
- The role of automation in precision agriculture and resource management.
- Socio-economic and ethical considerations in the adoption of these technologies in agriculture.
- Case studies on implementing robotics and AI in diverse agricultural settings.
- Future directions and challenges in integrating these technologies into agronomy.
- Comparative analysis between autonomous systems and conventional farm machinery.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Systematic Review
• Technology and Code

Keywords: AgBots, Agricultural Robots, Automated Agriculture, AI Powered Agronomy, Autonomous Agricultural Vehicles

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.