作物表型多源多尺度智能感知技术与装备研究进展

    Research progress in multi-source and multi-scale intelligent sensing technologies and equipment for crop phenotyping

    • 摘要: 作物表型是作物育种、精准栽培和智慧农业的重要信息基础,近年来正向多源融合、多尺度协同方向演进。本文分析了面向不同应用场景的室内外表型获取平台,以及RGB、多光谱、高光谱、热成像、荧光成像、激光雷达和核磁共振等不同感知方式,归纳了其在作物形态结构、生理状态和生化组分获取中的应用特点。分析了在植物细胞、组织器官、植株、群体小区和田块等不同尺度的表型获取方法与智能解析技术,探讨了高通量表型技术与作物基因功能协同解析的研究进展,为后续表型研究提供参考。

       

      Abstract: Crop phenotyping serves as a fundamental basis for crop breeding, precision cultivation, and smart agriculture. In recent years, it has evolved toward multimodal integration and multiscale coordination. This paper analysed indoor and outdoor phenotyping platforms across diverse application scenarios and reviewed sensing technologies, including RGB imaging, multispectral imaging, hyperspectral imaging, thermal imaging, fluorescence imaging, LiDAR, and nuclear magnetic resonance (NMR). The applications of these technologies were summarized in capturing crop morphological traits, physiological status, and biochemical components. The phenotyping acquisition methods and intelligent analytical techniques were also analyzed at different scales such as plant cells, tissues and organs, individual plants, population plot and field. Additionally, the advancements were explored in high-throughput phenotyping technologies and their integration with crop gene function analysis, providing a reference for future phenotyping research.

       

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