Proper nutrient management is essential for optimizing plant growth and productivity while minimizing environmental impact. Traditional nutrient management practices often rely on fixed application rates, as determined from soil test analyses and other non-plant based factors, without considering the dynamic nutrient requirements of plants. Adaptive nutrient management systems aim to address this issue by integrating precision agriculture, data-driven approaches, and advanced technologies to optimize nutrient application strategies. These systems take into account factors such as in-season soil and crop conditions, as well as other environmental variables to tailor nutrient inputs for increased plant productivity, reduced nutrient losses, and maximum economic profitability.
The main purpose of this Research Topic is to explore the challenges, goals, and potential of adaptive nutrient management systems for plant nutrition. The goals are to investigate the optimization strategies, economic feasibility, and ecological implications of such systems. Key problems to be addressed include:
• Developing models and algorithms for adaptive nutrient management based on plant and soil data.
• Evaluating the profitability and economic benefits of precision nutrient management strategies.
• Assessing the environmental impacts and nutrient use efficiency of adaptive nutrient management systems.
• Exploring the interactions between nutrient management practices and ecosystem services.
• Identifying barriers and opportunities for the adoption of adaptive nutrient management technologies.
• Understanding the role of digital agriculture and data analytics in optimizing nutrient management.
In this collection, we welcome Original Research, Reviews, Perspective, and Methods on the following sub-themes but not limited to:
• Remote sensing and precision agriculture techniques for assessing plant nutrient status.
• Sensor-based technologies for real-time monitoring and feedback in nutrient application.
• Modeling approaches for predicting crop nutrient requirements and optimizing fertilizer application.
• Integration of climate data and predictive tools for adaptive nutrient management.
• Assessment of adaptive nutrient management practices in diverse cropping systems and agroecosystems.
• Economic analyses and cost-benefit assessments of adaptive nutrient management strategies.
• Environmental impacts and sustainability assessment of advanced nutrient management approaches.
• Adoption barriers, knowledge gaps, and extension strategies for implementing adaptive nutrient management.
• Synergies between adaptive nutrient management systems and other sustainable agricultural practices.
Proper nutrient management is essential for optimizing plant growth and productivity while minimizing environmental impact. Traditional nutrient management practices often rely on fixed application rates, as determined from soil test analyses and other non-plant based factors, without considering the dynamic nutrient requirements of plants. Adaptive nutrient management systems aim to address this issue by integrating precision agriculture, data-driven approaches, and advanced technologies to optimize nutrient application strategies. These systems take into account factors such as in-season soil and crop conditions, as well as other environmental variables to tailor nutrient inputs for increased plant productivity, reduced nutrient losses, and maximum economic profitability.
The main purpose of this Research Topic is to explore the challenges, goals, and potential of adaptive nutrient management systems for plant nutrition. The goals are to investigate the optimization strategies, economic feasibility, and ecological implications of such systems. Key problems to be addressed include:
• Developing models and algorithms for adaptive nutrient management based on plant and soil data.
• Evaluating the profitability and economic benefits of precision nutrient management strategies.
• Assessing the environmental impacts and nutrient use efficiency of adaptive nutrient management systems.
• Exploring the interactions between nutrient management practices and ecosystem services.
• Identifying barriers and opportunities for the adoption of adaptive nutrient management technologies.
• Understanding the role of digital agriculture and data analytics in optimizing nutrient management.
In this collection, we welcome Original Research, Reviews, Perspective, and Methods on the following sub-themes but not limited to:
• Remote sensing and precision agriculture techniques for assessing plant nutrient status.
• Sensor-based technologies for real-time monitoring and feedback in nutrient application.
• Modeling approaches for predicting crop nutrient requirements and optimizing fertilizer application.
• Integration of climate data and predictive tools for adaptive nutrient management.
• Assessment of adaptive nutrient management practices in diverse cropping systems and agroecosystems.
• Economic analyses and cost-benefit assessments of adaptive nutrient management strategies.
• Environmental impacts and sustainability assessment of advanced nutrient management approaches.
• Adoption barriers, knowledge gaps, and extension strategies for implementing adaptive nutrient management.
• Synergies between adaptive nutrient management systems and other sustainable agricultural practices.
