Irrigation plays a central role in irrigated agricultural systems, intersecting with various crop management practices. Recent advancements in sensor, telemetry, and artificial intelligence (AI) technologies have revolutionized the way we monitor and manage irrigation, enabling more detailed insights and integrated analytics to support day-to-day decision-making. This Research Topic aims to present a comprehensive overview of the most recent advancements in precision irrigation, exploring cutting-edge hardware and software solutions, AI-driven irrigation management, and real-world cases of technology adoption and its barriers. Additionally, it will investigate the integration of irrigation management with other crop management practices, such as nutrition and disease management. By addressing these key aspects, this Research Topic seeks to provide a holistic understanding of precision irrigation's potential to optimize resource use, enhance crop yields, and contribute to sustainable agriculture in the face of increasing water scarcity and climate variability.
This Research Topic aims to explore the latest advancements in precision irrigation, focusing on innovative technologies, AI-driven solutions, modelling, and strategies to promote widespread adoption. The collected articles will showcase cutting-edge research and practical applications that can significantly improve water use efficiency, optimize resource management, and enhance crop productivity.
The collection will cover themes such as AI-driven precision irrigation scheduling and management, innovative precision irrigation technologies, quantitative modelling for irrigation management, practical case studies of successful precision irrigation adoption as well as strategies for overcoming barriers to widespread adoption, and the integration of precision irrigation with other precision agriculture practices.
By addressing these themes, this Research Topic seeks to provide a comprehensive overview of the state-of-the-art in precision irrigation, highlighting the potential of innovative technologies, modelling, and AI-driven solutions to revolutionize water management in agriculture. The ultimate goal is to identify effective strategies for promoting the widespread adoption of these technologies, thereby contributing to the sustainable intensification of agricultural production in the face of increasing water scarcity and climate variability.
Original research, reviews, or opinion pieces that related to the following topics will be collected:
1. AI-driven precision irrigation scheduling and management: Investigating the use of AI algorithms, machine learning techniques, deep learning, and neural networks to optimize irrigation decision-making for improved water use efficiency. Exploring how AI could help predict upcoming water stresses with changing climate conditions. Developing real-time decision support systems for irrigation management. Integrating Internet of Things (IoT) technologies for comprehensive data collection and analysis
2. Innovative precision irrigation technologies: Presenting novel sensors, controllers, and delivery systems that enable high-resolution monitoring of plant water stress and precise application of water. Exploring remote sensing technologies (e.g., drones, satellite imagery) for large-scale irrigation management.
3. Quantitative modeling for irrigation management: Developing and applying crop models, hydrological models, and other relevant quantitative approaches. Implementing multi-scale modeling techniques from field to regional scales under various climatic conditions. Utilizing data assimilation techniques to improve model accuracy and reliability. Exploring soil-plant-atmosphere processes and responses to different irrigation regimes.
4. Practical case studies of successful precision irrigation adoption: Demonstrating the real-world impact and feasibility of implementing advanced precision irrigation technologies in various agricultural contexts. Strategies for overcoming barriers to widespread adoption: Examining the socio-economic, cultural, and policy factors that influence the uptake of precision irrigation technologies and proposing solutions to address these challenges.
5. Integration of precision irrigation with other precision agriculture practices: Exploring the synergies between precision irrigation and other crop management aspects, such as nutrition management, disease management, etc., to optimize overall farm management.
Keywords:
AI-driven irrigation innovations, Precision irrigation, Crop water stress monitoring, Widespread adoption strategies, Barriers to adoption, Water scarcity, Climate variability
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.
Irrigation plays a central role in irrigated agricultural systems, intersecting with various crop management practices. Recent advancements in sensor, telemetry, and artificial intelligence (AI) technologies have revolutionized the way we monitor and manage irrigation, enabling more detailed insights and integrated analytics to support day-to-day decision-making. This Research Topic aims to present a comprehensive overview of the most recent advancements in precision irrigation, exploring cutting-edge hardware and software solutions, AI-driven irrigation management, and real-world cases of technology adoption and its barriers. Additionally, it will investigate the integration of irrigation management with other crop management practices, such as nutrition and disease management. By addressing these key aspects, this Research Topic seeks to provide a holistic understanding of precision irrigation's potential to optimize resource use, enhance crop yields, and contribute to sustainable agriculture in the face of increasing water scarcity and climate variability.
This Research Topic aims to explore the latest advancements in precision irrigation, focusing on innovative technologies, AI-driven solutions, modelling, and strategies to promote widespread adoption. The collected articles will showcase cutting-edge research and practical applications that can significantly improve water use efficiency, optimize resource management, and enhance crop productivity.
The collection will cover themes such as AI-driven precision irrigation scheduling and management, innovative precision irrigation technologies, quantitative modelling for irrigation management, practical case studies of successful precision irrigation adoption as well as strategies for overcoming barriers to widespread adoption, and the integration of precision irrigation with other precision agriculture practices.
By addressing these themes, this Research Topic seeks to provide a comprehensive overview of the state-of-the-art in precision irrigation, highlighting the potential of innovative technologies, modelling, and AI-driven solutions to revolutionize water management in agriculture. The ultimate goal is to identify effective strategies for promoting the widespread adoption of these technologies, thereby contributing to the sustainable intensification of agricultural production in the face of increasing water scarcity and climate variability.
Original research, reviews, or opinion pieces that related to the following topics will be collected:
1. AI-driven precision irrigation scheduling and management: Investigating the use of AI algorithms, machine learning techniques, deep learning, and neural networks to optimize irrigation decision-making for improved water use efficiency. Exploring how AI could help predict upcoming water stresses with changing climate conditions. Developing real-time decision support systems for irrigation management. Integrating Internet of Things (IoT) technologies for comprehensive data collection and analysis
2. Innovative precision irrigation technologies: Presenting novel sensors, controllers, and delivery systems that enable high-resolution monitoring of plant water stress and precise application of water. Exploring remote sensing technologies (e.g., drones, satellite imagery) for large-scale irrigation management.
3. Quantitative modeling for irrigation management: Developing and applying crop models, hydrological models, and other relevant quantitative approaches. Implementing multi-scale modeling techniques from field to regional scales under various climatic conditions. Utilizing data assimilation techniques to improve model accuracy and reliability. Exploring soil-plant-atmosphere processes and responses to different irrigation regimes.
4. Practical case studies of successful precision irrigation adoption: Demonstrating the real-world impact and feasibility of implementing advanced precision irrigation technologies in various agricultural contexts. Strategies for overcoming barriers to widespread adoption: Examining the socio-economic, cultural, and policy factors that influence the uptake of precision irrigation technologies and proposing solutions to address these challenges.
5. Integration of precision irrigation with other precision agriculture practices: Exploring the synergies between precision irrigation and other crop management aspects, such as nutrition management, disease management, etc., to optimize overall farm management.
Keywords:
AI-driven irrigation innovations, Precision irrigation, Crop water stress monitoring, Widespread adoption strategies, Barriers to adoption, Water scarcity, Climate variability
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.