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Microbiome-enabled genomic selection improves prediction accuracy for nitrogen-related traits in maize
View ORCID ProfileZhikai Yang, Tianjing Zhao, View ORCID ProfileHao Cheng, Jinliang Yang
doi: https://doi.org/10.1101/2023.03.03.530932
Zhikai Yang
1Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
2Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE 68583, USA
Tianjing Zhao
3Department of Animal Science, University of California Davis, Davis, CA 95616, USA
Hao Cheng
3Department of Animal Science, University of California Davis, Davis, CA 95616, USA
Jinliang Yang
1Department of Agronomy and Horticulture, University of Nebraska-Lincoln, Lincoln, NE 68588, USA
2Center for Plant Science Innovation, University of Nebraska-Lincoln, Lincoln, NE 68583, USA
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Posted November 14, 2023.
Microbiome-enabled genomic selection improves prediction accuracy for nitrogen-related traits in maize
Zhikai Yang, Tianjing Zhao, Hao Cheng, Jinliang Yang
bioRxiv 2023.03.03.530932; doi: https://doi.org/10.1101/2023.03.03.530932
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