About this Research Topic
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, the integration of such technologies also brings forth challenges in terms of adaptability, cost, and the need for specialised skills. Furthermore, it raises important 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 area of research is essential for advancing the frontiers of agronomy, pushing the boundaries of what is possible in sustainable, efficient, and responsible crop production.
The primary goal is to address the critical problem of integrating robotics, automation, and artificial intelligence (AI) into the multifaceted field of 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, which significantly reduce labour requirements and optimise 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, thereby enabling more informed agronomic decisions.
To achieve a harmonious integration of these technologies, the research must focus on developing cost-effective, user-friendly, and adaptable solutions that can be applied across diverse agricultural settings, including small-scale farms. It also involves training the next generation of agronomists in these technologies, ensuring they are equipped to implement and manage them effectively. Addressing the challenges of technology adoption, particularly in developing countries, and understanding the socio-economic impacts of this technological shift in agronomy are also vital. The goal is to pave the way for a new era of agronomy, where technology enhances the principles of sustainable, efficient, and eco-friendly agriculture, aligning with the broader objectives of global food security and environmental stewardship.
The journal invites contributions that delve into the intersection of advanced technologies with agronomic practices. We are particularly interested in manuscripts that explore the application and impact of robotics, automation, and AI in enhancing crop production, sustainability, and efficiency. Specific themes include but are not limited to:
1. Advances in robotic systems for planting, harvesting, and crop management.
2. Utilisation of AI and machine learning in predictive analytics for crop health and yield optimisation.
3. The role of automation in precision agriculture and resource management.
4. Socio-economic and ethical considerations in the adoption of these technologies in agriculture.
5. Case studies on the implementation of robotics and AI in diverse agricultural settings.
6. Future directions and challenges in integrating these technologies into agronomy.
7. Comparative analysis between autonomous systems and conventional farm machinery.
The primary goal is to address the critical problem of integrating robotics, automation, and artificial intelligence (AI) into the multifaceted field of 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, which significantly reduce labour requirements and optimise 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, thereby enabling more informed agronomic decisions.
To achieve a harmonious integration of these technologies, the research must focus on developing cost-effective, user-friendly, and adaptable solutions that can be applied across diverse agricultural settings, including small-scale farms. It also involves training the next generation of agronomists in these technologies, ensuring they are equipped to implement and manage them effectively. Addressing the challenges of technology adoption, particularly in developing countries, and understanding the socio-economic impacts of this technological shift in agronomy are also vital. The goal is to pave the way for a new era of agronomy, where technology enhances the principles of sustainable, efficient, and eco-friendly agriculture, aligning with the broader objectives of global food security and environmental stewardship.
The journal invites contributions that delve into the intersection of advanced technologies with agronomic practices. We are particularly interested in manuscripts that explore the application and impact of robotics, automation, and AI in enhancing crop production, sustainability, and efficiency. Specific themes include but are not limited to:
1. Advances in robotic systems for planting, harvesting, and crop management.
2. Utilisation of AI and machine learning in predictive analytics for crop health and yield optimisation.
3. The role of automation in precision agriculture and resource management.
4. Socio-economic and ethical considerations in the adoption of these technologies in agriculture.
5. Case studies on the implementation of robotics and AI in diverse agricultural settings.
6. Future directions and challenges in integrating these technologies into agronomy.
7. Comparative analysis between autonomous systems and conventional farm machinery.
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.
