4.7 Article

High-Throughput Phenotyping Analysis of Potted Soybean Plants Using Colorized Depth Images Based on A Proximal Platform

Journal

REMOTE SENSING
Volume 11, Issue 9, Pages -

Publisher

MDPI
DOI: 10.3390/rs11091085

Keywords

soybean; plant height; canopy breadth; color indices; high-throughput; Kinect sensor

Funding

  1. National Natural Science Foundation of China [31601220]
  2. Natural Science Foundation of Heilongjiang Province [QC2016031]
  3. China Postdoctoral Science Foundation [2016M601464]
  4. Support Program for Natural Science Talent of Heilongjiang Bayi Agricultural University [ZRCQC201806]

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Canopy color and structure can strongly reflect plant functions. Color characteristics and plant height as well as canopy breadth are important aspects of the canopy phenotype of soybean plants. High-throughput phenotyping systems with imaging capabilities providing color and depth information can rapidly acquire data of soybean plants, making it possible to quantify and monitor soybean canopy development. The goal of this study was to develop a 3D imaging approach to quantitatively analyze soybean canopy development under natural light conditions. Thus, a Kinect sensor-based high-throughput phenotyping (HTP) platform was developed for soybean plant phenotyping. To calculate color traits accurately, the distortion phenomenon of color images was first registered in accordance with the principle of three primary colors and color constancy. Then, the registered color images were applied to depth images for the reconstruction of the colorized three-dimensional canopy structure. Furthermore, the 3D point cloud of soybean canopies was extracted from the background according to adjusted threshold, and each area of individual potted soybean plants in the depth images was segmented for the calculation of phenotypic traits. Finally, color indices, plant height and canopy breadth were assessed based on 3D point cloud of soybean canopies. The results showed that the maximum error of registration for the R, G, and B bands in the dataset was 1.26%, 1.09%, and 0.75%, respectively. Correlation analysis between the sensors and manual measurements yielded R-2 values of 0.99, 0.89, and 0.89 for plant height, canopy breadth in the west-east (W-E) direction, and canopy breadth in the north-south (N-S) direction, and R-2 values of 0.82, 0.79, and 0.80 for color indices h, s, and i, respectively. Given these results, the proposed approaches provide new opportunities for the identification of the quantitative traits that control canopy structure in genetic/genomic studies or for soybean yield prediction in breeding programs.

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