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Conventional and hyperspectral time-series imaging of maize lines widely used in field trials

View ORCID ProfileZhikai Liang, Piyush Pandey, Vincent Stoerger, Yuhang Xu, Yumou Qiu, Yufeng Ge, View ORCID ProfileJames C. Schnable
doi: https://doi.org/10.1101/169045
Zhikai Liang
1Center for Plant Science Innovation, Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, 68503, USA
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Piyush Pandey
2Department of Biological System Engineering, University of Nebraska-Lincoln, Lincoln, 68503, USA
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Vincent Stoerger
3Plant Phenotyping Facilities Manager, University of Nebraska-Lincoln, Lincoln, 68503, USA
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Yuhang Xu
4Department of Statistics, University of Nebraska-Lincoln, Lincoln, 68503, USA
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Yumou Qiu
4Department of Statistics, University of Nebraska-Lincoln, Lincoln, 68503, USA
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Yufeng Ge
2Department of Biological System Engineering, University of Nebraska-Lincoln, Lincoln, 68503, USA
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James C. Schnable
1Center for Plant Science Innovation, Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, 68503, USA
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Posted September 21, 2017.
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Conventional and hyperspectral time-series imaging of maize lines widely used in field trials
Zhikai Liang, Piyush Pandey, Vincent Stoerger, Yuhang Xu, Yumou Qiu, Yufeng Ge, James C. Schnable
bioRxiv 169045; doi: https://doi.org/10.1101/169045
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Conventional and hyperspectral time-series imaging of maize lines widely used in field trials
Zhikai Liang, Piyush Pandey, Vincent Stoerger, Yuhang Xu, Yumou Qiu, Yufeng Ge, James C. Schnable
bioRxiv 169045; doi: https://doi.org/10.1101/169045

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