AI, Sensors and Robotics in Plant Phenotyping and Precision Agriculture

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Editorial

23 November 2022

Editorial: AI, sensors and robotics in plant phenotyping and precision agriculture

Yongliang Qiao

,

João Valente

,

Daobilige Su

,

Zhao Zhang

and

Dongjian He

5,852 views

19 citations

Editors

5

University of Adelaide

Centre for Automation and Robotics, Spanish National Research Council (CSIC)

China Agricultural University

College of Engineering, China Agricultural University

Northwest A&F University

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Plant production needs to be improved in a sustainable manner to accommodate a rising global population and anticipated climate change. To reduce the impact of agriculture on the environment, a sustainable intensification of agriculture is required by adopting modern techniques for plant breeding, cultivation and management of crops. 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. In recent years, smart sensors, big data and machine learning, non-invasive technologies and information technologies are combined to derive reliable plant-physiological parameters at an increasing throughput for precision agriculture.

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;
• 3D sensors adapted to plants;
• 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. To reduce the impact of agriculture on the environment, a sustainable intensification of agriculture is required by adopting modern techniques for plant breeding, cultivation and management of crops. 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. In recent years, smart sensors, big data and machine learning, non-invasive technologies and information technologies are combined to derive reliable plant-physiological parameters at an increasing throughput for precision agriculture.

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;
• 3D sensors adapted to plants;
• 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

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Editors

University of Adelaide

Centre for Automation and Robotics, Spanish National Research Council (CSIC)

China Agricultural University

College of Engineering, China Agricultural University

Northwest A&F University

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89,339 Article views

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5,491 Topic views

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Frontiers in Plant Science

Sustainable and Intelligent Phytoprotection

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