About this Research Topic
This Research Topic is part of the article collection series - AI, Sensors and Robotics in Plant Phenotyping and Precision Agriculture.
Plant production needs to be improved in a sustainable manner to accommodate a rising global population and anticipated climate change. Plant phenotyping plays an essential role in optimizing the genetic potential, plant breeding, and resource deployment in plant production. Recent and comprehensive plant phenotyping emerges from the dynamic and local interaction of phenotypes with the spatially and temporally dynamic environment above and below ground, while assessing complex plant traits such as growth, development, tolerance, resistance, physiology, ecology, yield, and basic quantitative parameters. The integration of smart sensors, big data, artificial intelligence, non-invasive technologies, and information technologies is pivotal in deriving accurate plant-physiological parameters at high throughput for precision agriculture. Notably, the advancement of wearable plant sensors, which are environmentally friendly for long-term use, marks a significant stride toward smart, data-driven agriculture. This technology provides novel solutions to complex challenges in agricultural production and environmental monitoring.
This Research Topic will welcome papers involved in research on plant phenotyping and precision agriculture. The selection of papers for publication will depend on the quality and the rigor of research. Specific topics include, but are not limited to advanced methods for imaging technologies, sensor setups, and data processing in plant phenotyping and precision agriculture:
• Panchromatic, multispectral, and hyperspectral approaches;
• AI algorithms for agriculture;
• Wearable plant sensors;
• High-throughput sensor platforms;
• Robotics for plant phenotyping;
• Field phenotyping and yield estimation;
• Disease and stress detection;
• Data analysis in plant phenotyping;
• Sensors and sensing techniques for phenotyping;
• Aerial plant phenotyping.
Plant production needs to be improved in a sustainable manner to accommodate a rising global population and anticipated climate change. Plant phenotyping plays an essential role in optimizing the genetic potential, plant breeding, and resource deployment in plant production. Recent and comprehensive plant phenotyping emerges from the dynamic and local interaction of phenotypes with the spatially and temporally dynamic environment above and below ground, while assessing complex plant traits such as growth, development, tolerance, resistance, physiology, ecology, yield, and basic quantitative parameters. The integration of smart sensors, big data, artificial intelligence, non-invasive technologies, and information technologies is pivotal in deriving accurate plant-physiological parameters at high throughput for precision agriculture. Notably, the advancement of wearable plant sensors, which are environmentally friendly for long-term use, marks a significant stride toward smart, data-driven agriculture. This technology provides novel solutions to complex challenges in agricultural production and environmental monitoring.
This Research Topic will welcome papers involved in research on plant phenotyping and precision agriculture. The selection of papers for publication will depend on the quality and the rigor of research. Specific topics include, but are not limited to advanced methods for imaging technologies, sensor setups, and data processing in plant phenotyping and precision agriculture:
• Panchromatic, multispectral, and hyperspectral approaches;
• AI algorithms for agriculture;
• Wearable plant sensors;
• High-throughput sensor platforms;
• Robotics for plant phenotyping;
• Field phenotyping and yield estimation;
• Disease and stress detection;
• Data analysis in plant phenotyping;
• Sensors and sensing techniques for phenotyping;
• Aerial plant phenotyping.
Keywords: #CollectionSeries, Wearable plant sensors, Agricultural Large Models, Plant Phenotyping, Precision Agriculture, Intelligent Perception
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.
