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Smart Agriculture ›› 2024, Vol. 6 ›› Issue (1): 63-75.doi: 10.12133/j.smartag.SA202311018

• 专题--智能农业传感器技术 • 上一篇    下一篇

融合三维结构光和叶绿素荧光的植株光合表型成像系统

束宏伟1,2(), 王玉伟2,3, 饶元1,2(), 朱浩杰2,3, 侯文慧2,3, 王坦1,2   

  1. 1. 安徽农业大学 信息与人工智能学院,安徽 合肥 230036,中国
    2. 农业农村部农业传感器重点实验室,安徽 合肥 230036,中国
    3. 安徽农业大学 工学院,安徽 合肥 230036,中国
  • 收稿日期:2023-11-10 出版日期:2024-01-30
  • 作者简介:
    束宏伟,研究方向为农业传感器技术。E-mail:
  • 通信作者:
    饶 元,博士,教授,研究方向为农业信息化。E-mail:

Imaging System for Plant Photosynthetic Phenotypes Incorporating Three-dimensional Structured Light and Chlorophyll Fluorescence

SHU Hongwei1,2(), WANG Yuwei2,3, RAO Yuan1,2(), ZHU Haojie2,3, HOU Wenhui2,3, WANG Tan1,2   

  1. 1. College of Information and Artificial Intelligence, Anhui Agricultural University, Hefei 230036, China
    2. Key Laboratory of Agricultural Sensors, Ministry of Agriculture and Rural Affairs, Hefei 230036, China
    3. College of Engineering, Anhui Agricultural University, Hefei 230036, China
  • Received:2023-11-10 Online:2024-01-30
  • Foundation items:National Natural Science Foundation of China(32371993); Key Research and Development Plan Project of Anhui Province(2023n06020057); Major Natural Science Research Projects in Anhui Province Universities(2022AH040125)
  • About author:

    SHU Hongwei, E-mail:

  • Corresponding author:
    RAO Yuan, E-mail:

摘要:

目的/意义 植株光合表型研究在把握植株生理特性和解析植株形态结构上起着至关重要的作用,通过传统叶绿素荧光成像方法难以对植株光合作用三维空间异质性进行分析。为提高植株表型检测效率,满足高通量植株光合表型分析需求,本研究构建了一套经济实用、融合三维结构光和叶绿素荧光的植株光合表型成像系统。 方法 提出了一种自动化植株图像采集并建立植株可视化模型的方法,并进行图像分析获取植株光合效率信息。通过搭建结合叶绿素荧光激发的结构光条纹投影装置,先用LED(Light-Emitting Diode)白光与蓝光分别照射植株样本,再用投影仪对植株样本投射相移条纹,电动滤光轮配合相机同步采集不同光照条件下特定波段的植株图像;通过数字图像处理获取植株三维图像和对应的叶绿素荧光图像,并分析植株的三维形态结构及光合效率,将植株叶绿素荧光图像逐像素渲染到其三维结构上,便可推测出植株光合在三维空间中分布情况。 结果和讨论 该方法及系统能够高效多样化采集植株图像,快速重构出植株三维形态,其整体重建准确率可达到96.69%,整体误差仅为3.31%,重构时间仅需1.11 s,同时能够满足植株光合效率评估需求。 结论 该研究可为植株高通量光合表型异质性分析提供技术支持。

关键词: 结构光条纹投影, 叶绿素荧光, 植株表型, 三维重构, 光合效率, 异质性分析

Abstract:

Objective The investigation of plant photosynthetic phenotypes is essential for unlocking insights into plant physiological characteristics and dissecting morphological traits. However, traditional two-dimensional chlorophyll fluorescence imaging methods struggle to capture the complex three-dimensional spatial variations inherent in plant photosynthetic processes. To boost the efficacy of plant phenotyping and meet the increasingly demand for high-throughput analysis of photosynthetic phenotypes, the development and validation of a novel plant photosynthetic phenotype imaging system was explored, which uniquely combines three-dimensional structured light techniques with chlorophyll fluorescence technology. Methods The plant photosynthetic phenotype imaging system was composed of three primary parts: A tailored light source and projector, a camera, and a motorized filter wheel fitted with filters of various bandwidths, in addition to a terminal unit equipped with a development board and a touchscreen interface. The system was based on the principles and unique characteristics of chlorophyll fluorescence and structured light phase-shifted streak 3D reconstruction techniques. It utilized the custom-designed light source and projector, together with the camera's capability to choose specific wavelength bands, to its full potential. The system employed low-intensity white light within the 400–700 nm spectrum to elicit stable fluorescence, with blue light in the 440–450 nm range optimally triggering the fluorescence response. A projector was used to project dual-frequency, twelve-step phase-shifted stripes onto the plant, enabling the capture of both planar and stripe images, which were essential for the reconstruction of the plant's three-dimensional structure. An motorized filter wheel containing filters for red, green, blue, and near-infrared light, augmented by a filter less wheel for camera collaboration, facilitated the collection of images of plants at different wavelengths under varying lighting conditions. When illuminated with white light, filters corresponding to the red, green, and blue bands were applied to capture multiband images, resulting in color photographs that provides a comprehensive documentation of the plant's visual features. Upon exposure to blue light, the near-infrared filter was employed to capture near-infrared images, yielding data on chlorophyll fluorescence intensity. During the structured light streak projection, no filter was applied to obtain both planar and streak images of the plant, which were then employed in the 3D morphological reconstruction of the plant. The terminal, incorporating a development board and a touch screen, served as the control hub for the data acquisition and subsequent image processing within the plant photosynthetic phenotypic imaging system. It enabled the switching of light sources and the selection of camera bands through a combination of command and serial port control circuits. Following image acquisition, the data were transmitted back to the development board for analysis, processing, storage, and presentation. To validate the accuracy of 3D reconstruction and the reliability of photosynthetic efficiency assessments by the system, a prototype of the plant photosynthetic phenotypic imaging system was developed using 3D structured light and chlorophyll fluorescence technology, in accordance with the aforementioned methods, serving as an experimental validation platform. The accuracy of 3D reconstruction and the effectiveness of photosynthetic analysis capabilities of this imaging system were further confirmed through the analysis and processing of the experimental results, with comparative evaluations conducted against conventional 3D reconstruction methods and traditional chlorophyll fluorescence-based photosynthetic efficiency analyses. Results and Discussions The imaging system utilized for plant photosynthetic phenotypes incorporates a dual-frequency phase-shift algorithm to facilitate the reconstruction of three-dimensional (3D) plant phenotypes. Simultaneously, plant chlorophyll fluorescence images were employed to evaluate the plant's photosynthetic efficiency. This method enabled the analysis of the distribution of photosynthetic efficiency within a 3D space, offering a significant advancement over traditional plant photosynthetic imaging techniques. The 3D phenotype reconstructed using this method exhibits high precision, with an overall reconstruction accuracy of 96.69%. The total error was merely 3.31%, and the time required for 3D reconstruction was only 1.11 s. A comprehensive comparison of the 3D reconstruction approach presented with conventional methods had validated the accuracy of this technique, laying a robust foundation for the precise estimation of a plant's 3D photosynthetic efficiency. In the realm of photosynthetic efficiency analysis, the correlation coefficient between the photosynthetic efficiency values inferred from the chlorophyll fluorescence image analysis and those determined by conventional analysis exceeded 0.9. The experimental findings suggest a significant correlation between the photosynthetic efficiency values obtained using the proposed method and those from traditional methods, which could be characterized by a linear relationship, thereby providing a basis for more precise predictions of plant photosynthetic efficiency. Conclusions The method melds the 3D phenotype of plants with an analysis of photosynthetic efficiency, allowing for a more holistic assessment of the spatial heterogeneity in photosynthetic efficiency among plants by examining the pseudo-color images of chlorophyll fluorescence's spatial distribution. This approach elucidates the discrepancies in photosynthetic efficiency across various regions. The plant photosynthetic phenotype imaging system affords an intuitive and comprehensive view of the photosynthetic efficiency in plants under diverse stress conditions. Additionally, It provides technical support for the analysis of the spatial heterogeneity of high-throughput photosynthetic efficiency in plants.

Key words: structured light streak projection, chlorophyll fluorescence, plant phenotype, three-dimensional reconstruction, photosynthetic efficiency, heterogeneity analysis