Identification of High Nitrogen Use Efficiency Phenotype in Rice (Oryza sativa L.) Through Entire Growth Duration by Unmanned Aerial Vehicle Multispectral Imagery
Identification of high Nitrogen Use Efficiency (NUE) phenotypes has been a long-standing challenge in breeding rice and sustainable agriculture to reduce the costs of nitrogen (N) fertilizers. There are two main challenges: (1) high NUE genetic sources are biologically scarce and (2) on the technica...
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Frontiers Media S.A.
2021
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oai:doaj.org-article:d6407df217a44053b8c14ab2fcc2293f2021-12-03T05:40:55ZIdentification of High Nitrogen Use Efficiency Phenotype in Rice (Oryza sativa L.) Through Entire Growth Duration by Unmanned Aerial Vehicle Multispectral Imagery1664-462X10.3389/fpls.2021.740414https://doaj.org/article/d6407df217a44053b8c14ab2fcc2293f2021-12-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fpls.2021.740414/fullhttps://doaj.org/toc/1664-462XIdentification of high Nitrogen Use Efficiency (NUE) phenotypes has been a long-standing challenge in breeding rice and sustainable agriculture to reduce the costs of nitrogen (N) fertilizers. There are two main challenges: (1) high NUE genetic sources are biologically scarce and (2) on the technical side, few easy, non-destructive, and reliable methodologies are available to evaluate plant N variations through the entire growth duration (GD). To overcome the challenges, we captured a unique higher NUE phenotype in rice as a dynamic time-series N variation curve through the entire GD analysis by canopy reflectance data collected by Unmanned Aerial Vehicle Remote Sensing Platform (UAV-RSP) for the first time. LY9348 was a high NUE rice variety with high Nitrogen Uptake Efficiency (NUpE) and high Nitrogen Utilization Efficiency (NUtE) shown in nitrogen dosage field analysis. Its canopy nitrogen content (CNC) was analyzed by the high-throughput UAV-RSP to screen two mixed categories (51 versus 42 varieties) selected from representative higher NUE indica rice collections. Five Vegetation Indices (VIs) were compared, and the Normalized Difference Red Edge Index (NDRE) showed the highest correlation with CNC (r = 0.80). Six key developmental stages of rice varieties were compared from transplantation to maturation, and the high NUE phenotype of LY9348 was shown as a dynamic N accumulation curve, where it was moderately high during the vegetative developmental stages but considerably higher in the reproductive developmental stages with a slower reduction rate. CNC curves of different rice varieties were analyzed to construct two non-linear regression models between N% or N% × leaf area index (LAI) with NDRE separately. Both models could determine the specific phenotype with the coefficient of determination (R2) above 0.61 (Model I) and 0.86 (Model II). Parameters influencing the correlation accuracy between NDRE and N% were found to be better by removing the tillering stage data, separating the short and long GD varieties for the analysis and adding canopy structures, such as LAI, into consideration. The high NUE phenotype of LY9348 could be traced and reidentified across different years, locations, and genetic germplasm groups. Therefore, an effective and reliable high-throughput method was proposed for assisting the selection of the high NUE breeding phenotype.Ting LiangTing LiangTing LiangBo DuanXiaoyun LuoXiaoyun LuoXiaoyun LuoYi MaYi MaZhengqing YuanZhengqing YuanZhengqing YuanRenshan ZhuRenshan ZhuRenshan ZhuYi PengYi PengYan GongYan GongShenghui FangShenghui FangXianting WuXianting WuXianting WuXianting WuFrontiers Media S.A.articleUAVhigh throughput phenotypingentire growth durationcanopy nitrogen contenthigh NUE phenotypePlant cultureSB1-1110ENFrontiers in Plant Science, Vol 12 (2021) |
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| topic |
UAV high throughput phenotyping entire growth duration canopy nitrogen content high NUE phenotype Plant culture SB1-1110 |
| spellingShingle |
UAV high throughput phenotyping entire growth duration canopy nitrogen content high NUE phenotype Plant culture SB1-1110 Ting Liang Ting Liang Ting Liang Bo Duan Xiaoyun Luo Xiaoyun Luo Xiaoyun Luo Yi Ma Yi Ma Zhengqing Yuan Zhengqing Yuan Zhengqing Yuan Renshan Zhu Renshan Zhu Renshan Zhu Yi Peng Yi Peng Yan Gong Yan Gong Shenghui Fang Shenghui Fang Xianting Wu Xianting Wu Xianting Wu Xianting Wu Identification of High Nitrogen Use Efficiency Phenotype in Rice (Oryza sativa L.) Through Entire Growth Duration by Unmanned Aerial Vehicle Multispectral Imagery |
| description |
Identification of high Nitrogen Use Efficiency (NUE) phenotypes has been a long-standing challenge in breeding rice and sustainable agriculture to reduce the costs of nitrogen (N) fertilizers. There are two main challenges: (1) high NUE genetic sources are biologically scarce and (2) on the technical side, few easy, non-destructive, and reliable methodologies are available to evaluate plant N variations through the entire growth duration (GD). To overcome the challenges, we captured a unique higher NUE phenotype in rice as a dynamic time-series N variation curve through the entire GD analysis by canopy reflectance data collected by Unmanned Aerial Vehicle Remote Sensing Platform (UAV-RSP) for the first time. LY9348 was a high NUE rice variety with high Nitrogen Uptake Efficiency (NUpE) and high Nitrogen Utilization Efficiency (NUtE) shown in nitrogen dosage field analysis. Its canopy nitrogen content (CNC) was analyzed by the high-throughput UAV-RSP to screen two mixed categories (51 versus 42 varieties) selected from representative higher NUE indica rice collections. Five Vegetation Indices (VIs) were compared, and the Normalized Difference Red Edge Index (NDRE) showed the highest correlation with CNC (r = 0.80). Six key developmental stages of rice varieties were compared from transplantation to maturation, and the high NUE phenotype of LY9348 was shown as a dynamic N accumulation curve, where it was moderately high during the vegetative developmental stages but considerably higher in the reproductive developmental stages with a slower reduction rate. CNC curves of different rice varieties were analyzed to construct two non-linear regression models between N% or N% × leaf area index (LAI) with NDRE separately. Both models could determine the specific phenotype with the coefficient of determination (R2) above 0.61 (Model I) and 0.86 (Model II). Parameters influencing the correlation accuracy between NDRE and N% were found to be better by removing the tillering stage data, separating the short and long GD varieties for the analysis and adding canopy structures, such as LAI, into consideration. The high NUE phenotype of LY9348 could be traced and reidentified across different years, locations, and genetic germplasm groups. Therefore, an effective and reliable high-throughput method was proposed for assisting the selection of the high NUE breeding phenotype. |
| format |
article |
| author |
Ting Liang Ting Liang Ting Liang Bo Duan Xiaoyun Luo Xiaoyun Luo Xiaoyun Luo Yi Ma Yi Ma Zhengqing Yuan Zhengqing Yuan Zhengqing Yuan Renshan Zhu Renshan Zhu Renshan Zhu Yi Peng Yi Peng Yan Gong Yan Gong Shenghui Fang Shenghui Fang Xianting Wu Xianting Wu Xianting Wu Xianting Wu |
| author_facet |
Ting Liang Ting Liang Ting Liang Bo Duan Xiaoyun Luo Xiaoyun Luo Xiaoyun Luo Yi Ma Yi Ma Zhengqing Yuan Zhengqing Yuan Zhengqing Yuan Renshan Zhu Renshan Zhu Renshan Zhu Yi Peng Yi Peng Yan Gong Yan Gong Shenghui Fang Shenghui Fang Xianting Wu Xianting Wu Xianting Wu Xianting Wu |
| author_sort |
Ting Liang |
| title |
Identification of High Nitrogen Use Efficiency Phenotype in Rice (Oryza sativa L.) Through Entire Growth Duration by Unmanned Aerial Vehicle Multispectral Imagery |
| title_short |
Identification of High Nitrogen Use Efficiency Phenotype in Rice (Oryza sativa L.) Through Entire Growth Duration by Unmanned Aerial Vehicle Multispectral Imagery |
| title_full |
Identification of High Nitrogen Use Efficiency Phenotype in Rice (Oryza sativa L.) Through Entire Growth Duration by Unmanned Aerial Vehicle Multispectral Imagery |
| title_fullStr |
Identification of High Nitrogen Use Efficiency Phenotype in Rice (Oryza sativa L.) Through Entire Growth Duration by Unmanned Aerial Vehicle Multispectral Imagery |
| title_full_unstemmed |
Identification of High Nitrogen Use Efficiency Phenotype in Rice (Oryza sativa L.) Through Entire Growth Duration by Unmanned Aerial Vehicle Multispectral Imagery |
| title_sort |
identification of high nitrogen use efficiency phenotype in rice (oryza sativa l.) through entire growth duration by unmanned aerial vehicle multispectral imagery |
| publisher |
Frontiers Media S.A. |
| publishDate |
2021 |
| url |
https://doaj.org/article/d6407df217a44053b8c14ab2fcc2293f |
| work_keys_str_mv |
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