Comparison Between Rice Plant Traits and Color Indices Calculated from UAV Remote Sensing Images
Remote sensing technology for monitoring plant trains has a huge potential to accelerate breeding process. In this paper, we have studied on remote sensing of using an unmanned aerial vehicle (UAV) system for plant traits phenotyping in rice. The images of rice canopy were taken by a RGB camera from...
| Main Authors: | , , , , , , , , , |
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| Format: | Journal Article |
| Language: | Chinese |
| Published: |
Society of Eco-Engineering
2017
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10568/89638 |
| _version_ | 1855522214564069376 |
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| author | Shimojima, Kohei Ogawa, Satoshi Naito, Hiroki Valencia Ortiz, Milton Orlando Shimizu, Yo Hosoi, Fumiki Uga, Yusaku Ishitani, Manabu Selvaraj, Michael Gomez Omasa, Kenji |
| author_browse | Hosoi, Fumiki Ishitani, Manabu Naito, Hiroki Ogawa, Satoshi Omasa, Kenji Selvaraj, Michael Gomez Shimizu, Yo Shimojima, Kohei Uga, Yusaku Valencia Ortiz, Milton Orlando |
| author_facet | Shimojima, Kohei Ogawa, Satoshi Naito, Hiroki Valencia Ortiz, Milton Orlando Shimizu, Yo Hosoi, Fumiki Uga, Yusaku Ishitani, Manabu Selvaraj, Michael Gomez Omasa, Kenji |
| author_sort | Shimojima, Kohei |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Remote sensing technology for monitoring plant trains has a huge potential to accelerate breeding process. In this paper, we have studied on remote sensing of using an unmanned aerial vehicle (UAV) system for plant traits phenotyping in rice. The images of rice canopy were taken by a RGB camera from the UAV at three growing stages; Vegetative (VG), Flowering (FW) and Grain filling (GF). Typical color indices (r, g, b, INT, VIG, L*, a*, b*, H) were calculated by image processing. Single regression analysis was conducted between rice plant traits (leaf area index (LAI), grain yield, above ground biomass, plant height, panicle length, grain filling rate, tiller number) and color indices. The index a* at FW and GF had close liner relationships with LAI (the coefficient of determination R2 > 0.70) and grain yield (R2 > 0.50). Moreover, a* and g at FW and GF showed high R2 with plant height and grain filling rate (R2 > 0.50). The R2 between grain yield and color indices increased above 0.5 for about 40% of models at three growing stages by multiple regression analysis. In particular, the models of H and INT and of H and L* at VG were closely related (R2 > 0.70). Our findings show the analysis of color images taken by UAV remote sensing is useful to assessing four rice traits; LAI, grain yield, plant height and grain filling rate at early stage, and especially more available for grain yield estimation. |
| format | Journal Article |
| id | CGSpace89638 |
| institution | CGIAR Consortium |
| language | Chinese |
| publishDate | 2017 |
| publishDateRange | 2017 |
| publishDateSort | 2017 |
| publisher | Society of Eco-Engineering |
| publisherStr | Society of Eco-Engineering |
| record_format | dspace |
| spelling | CGSpace896382025-03-13T09:44:09Z Comparison Between Rice Plant Traits and Color Indices Calculated from UAV Remote Sensing Images Shimojima, Kohei Ogawa, Satoshi Naito, Hiroki Valencia Ortiz, Milton Orlando Shimizu, Yo Hosoi, Fumiki Uga, Yusaku Ishitani, Manabu Selvaraj, Michael Gomez Omasa, Kenji oryza sativa rice remote sensing image processing yield teledetección tratamiento de imágenes Remote sensing technology for monitoring plant trains has a huge potential to accelerate breeding process. In this paper, we have studied on remote sensing of using an unmanned aerial vehicle (UAV) system for plant traits phenotyping in rice. The images of rice canopy were taken by a RGB camera from the UAV at three growing stages; Vegetative (VG), Flowering (FW) and Grain filling (GF). Typical color indices (r, g, b, INT, VIG, L*, a*, b*, H) were calculated by image processing. Single regression analysis was conducted between rice plant traits (leaf area index (LAI), grain yield, above ground biomass, plant height, panicle length, grain filling rate, tiller number) and color indices. The index a* at FW and GF had close liner relationships with LAI (the coefficient of determination R2 > 0.70) and grain yield (R2 > 0.50). Moreover, a* and g at FW and GF showed high R2 with plant height and grain filling rate (R2 > 0.50). The R2 between grain yield and color indices increased above 0.5 for about 40% of models at three growing stages by multiple regression analysis. In particular, the models of H and INT and of H and L* at VG were closely related (R2 > 0.70). Our findings show the analysis of color images taken by UAV remote sensing is useful to assessing four rice traits; LAI, grain yield, plant height and grain filling rate at early stage, and especially more available for grain yield estimation. 2017 2017-12-05T16:36:44Z 2017-12-05T16:36:44Z Journal Article https://hdl.handle.net/10568/89638 zh Limited Access Society of Eco-Engineering Shimojima, Kohei; Ogawa, Satoshi; Naito, Hiroki; Valencia, Milton Orlando; Shimizu, Yo; Hosoi, Fumiki; Uga, Yusaku; Ishitani, Manabu; Selvaraj, Michael Gomez; Omasa, Kenji. 2017. Comparison Between Rice Plant Traits and Color Indices Calculated from UAV Remote Sensing Images . Eco-Engineering 29(1): 11-16. |
| spellingShingle | oryza sativa rice remote sensing image processing yield teledetección tratamiento de imágenes Shimojima, Kohei Ogawa, Satoshi Naito, Hiroki Valencia Ortiz, Milton Orlando Shimizu, Yo Hosoi, Fumiki Uga, Yusaku Ishitani, Manabu Selvaraj, Michael Gomez Omasa, Kenji Comparison Between Rice Plant Traits and Color Indices Calculated from UAV Remote Sensing Images |
| title | Comparison Between Rice Plant Traits and Color Indices Calculated from UAV Remote Sensing Images |
| title_full | Comparison Between Rice Plant Traits and Color Indices Calculated from UAV Remote Sensing Images |
| title_fullStr | Comparison Between Rice Plant Traits and Color Indices Calculated from UAV Remote Sensing Images |
| title_full_unstemmed | Comparison Between Rice Plant Traits and Color Indices Calculated from UAV Remote Sensing Images |
| title_short | Comparison Between Rice Plant Traits and Color Indices Calculated from UAV Remote Sensing Images |
| title_sort | comparison between rice plant traits and color indices calculated from uav remote sensing images |
| topic | oryza sativa rice remote sensing image processing yield teledetección tratamiento de imágenes |
| url | https://hdl.handle.net/10568/89638 |
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