Novel 3D Imaging Systems for High-Throughput Phenotyping of Plants
The use of 3D plant models for high-throughput phenotyping is increasingly becoming a preferred method for many plant science researchers. Numerous camera-based imaging systems and reconstruction algorithms have been developed for the 3D reconstruction of plants. However, it is still challenging to...
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| Format: | Article |
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MDPI AG
2021-05-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/13/11/2113 |
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| author | Tian Gao Feiyu Zhu Puneet Paul Jaspreet Sandhu Henry Akrofi Doku Jianxin Sun Yu Pan Paul Staswick Harkamal Walia Hongfeng Yu |
| author_facet | Tian Gao Feiyu Zhu Puneet Paul Jaspreet Sandhu Henry Akrofi Doku Jianxin Sun Yu Pan Paul Staswick Harkamal Walia Hongfeng Yu |
| author_sort | Tian Gao |
| collection | DOAJ |
| description | The use of 3D plant models for high-throughput phenotyping is increasingly becoming a preferred method for many plant science researchers. Numerous camera-based imaging systems and reconstruction algorithms have been developed for the 3D reconstruction of plants. However, it is still challenging to build an imaging system with high-quality results at a low cost. Useful comparative information for existing imaging systems and their improvements is also limited, making it challenging for researchers to make data-based selections. The objective of this study is to explore the possible solutions to address these issues. We introduce two novel systems for plants of various sizes, as well as a pipeline to generate high-quality 3D point clouds and meshes. The higher accuracy and efficiency of the proposed systems make it a potentially valuable tool for enhancing high-throughput phenotyping by integrating 3D traits for increased resolution and measuring traits that are not amenable to 2D imaging approaches. The study shows that the phenotype traits derived from the 3D models are highly correlated with manually measured phenotypic traits (<i>R</i><sup>2</sup> > 0.91). Moreover, we present a systematic analysis of different settings of the imaging systems and a comparison with the traditional system, which provide recommendations for plant scientists to improve the accuracy of 3D construction. In summary, our proposed imaging systems are suggested for 3D reconstruction of plants. Moreover, the analysis results of the different settings in this paper can be used for designing new customized imaging systems and improving their accuracy. |
| first_indexed | 2024-03-10T10:57:36Z |
| format | Article |
| id | doaj.art-7d3036d4e781416f8c24a7df665c3ff3 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-10T10:57:36Z |
| publishDate | 2021-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-7d3036d4e781416f8c24a7df665c3ff32023-11-21T21:44:24ZengMDPI AGRemote Sensing2072-42922021-05-011311211310.3390/rs13112113Novel 3D Imaging Systems for High-Throughput Phenotyping of PlantsTian Gao0Feiyu Zhu1Puneet Paul2Jaspreet Sandhu3Henry Akrofi Doku4Jianxin Sun5Yu Pan6Paul Staswick7Harkamal Walia8Hongfeng Yu9Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USADepartment of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USADepartment of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583, USADepartment of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583, USADepartment of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583, USADepartment of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USADepartment of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USADepartment of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583, USADepartment of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68583, USADepartment of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE 68588, USAThe use of 3D plant models for high-throughput phenotyping is increasingly becoming a preferred method for many plant science researchers. Numerous camera-based imaging systems and reconstruction algorithms have been developed for the 3D reconstruction of plants. However, it is still challenging to build an imaging system with high-quality results at a low cost. Useful comparative information for existing imaging systems and their improvements is also limited, making it challenging for researchers to make data-based selections. The objective of this study is to explore the possible solutions to address these issues. We introduce two novel systems for plants of various sizes, as well as a pipeline to generate high-quality 3D point clouds and meshes. The higher accuracy and efficiency of the proposed systems make it a potentially valuable tool for enhancing high-throughput phenotyping by integrating 3D traits for increased resolution and measuring traits that are not amenable to 2D imaging approaches. The study shows that the phenotype traits derived from the 3D models are highly correlated with manually measured phenotypic traits (<i>R</i><sup>2</sup> > 0.91). Moreover, we present a systematic analysis of different settings of the imaging systems and a comparison with the traditional system, which provide recommendations for plant scientists to improve the accuracy of 3D construction. In summary, our proposed imaging systems are suggested for 3D reconstruction of plants. Moreover, the analysis results of the different settings in this paper can be used for designing new customized imaging systems and improving their accuracy.https://www.mdpi.com/2072-4292/13/11/21133D reconstructionpoint cloudimaging systemhigh-throughput phenotyping |
| spellingShingle | Tian Gao Feiyu Zhu Puneet Paul Jaspreet Sandhu Henry Akrofi Doku Jianxin Sun Yu Pan Paul Staswick Harkamal Walia Hongfeng Yu Novel 3D Imaging Systems for High-Throughput Phenotyping of Plants Remote Sensing 3D reconstruction point cloud imaging system high-throughput phenotyping |
| title | Novel 3D Imaging Systems for High-Throughput Phenotyping of Plants |
| title_full | Novel 3D Imaging Systems for High-Throughput Phenotyping of Plants |
| title_fullStr | Novel 3D Imaging Systems for High-Throughput Phenotyping of Plants |
| title_full_unstemmed | Novel 3D Imaging Systems for High-Throughput Phenotyping of Plants |
| title_short | Novel 3D Imaging Systems for High-Throughput Phenotyping of Plants |
| title_sort | novel 3d imaging systems for high throughput phenotyping of plants |
| topic | 3D reconstruction point cloud imaging system high-throughput phenotyping |
| url | https://www.mdpi.com/2072-4292/13/11/2113 |
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