Anatomics: High-throughput phenotyping of plant anatomy
Anatomics is a novel phenotyping strategy focused on high-throughput imaging and quantification of plant anatomy from field-grown plants. Here we highlight its potential applications for genetic and physiological analysis of plant anatomical phenotypes.
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Published in | Trends in plant science Vol. 27; no. 6; pp. 520 - 523 |
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Main Authors | , , |
Format | Journal Article |
Language | English |
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England
Elsevier Ltd
01.06.2022
Elsevier BV |
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Abstract | Anatomics is a novel phenotyping strategy focused on high-throughput imaging and quantification of plant anatomy from field-grown plants. Here we highlight its potential applications for genetic and physiological analysis of plant anatomical phenotypes. |
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AbstractList | Anatomics is a novel phenotyping strategy focused on high-throughput imaging and quantification of plant anatomy from field-grown plants. Here we highlight its potential applications for genetic and physiological analysis of plant anatomical phenotypes. Anatomics is a novel phenotyping strategy focused on high-throughput imaging and quantification of plant anatomy from field-grown plants. Here we highlight its potential applications for genetic and physiological analysis of plant anatomical phenotypes.Anatomics is a novel phenotyping strategy focused on high-throughput imaging and quantification of plant anatomy from field-grown plants. Here we highlight its potential applications for genetic and physiological analysis of plant anatomical phenotypes. |
Author | Schneider, Hannah M. Strock, Christopher F. Lynch, Jonathan P. |
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References | Zhu (bb0070) 2015; 39 Zhao (bb0040) 2019; 24 Choudhury (bb0055) 2019; 10 Levin (bb0035) 2021; 40 Brodersen, Roddy (bb0030) 2016; 103 Hall (bb0015) 2019; 31 Lobet (bb0045) 2013; 9 Strock (bb0020) 2019; 70 Schneider (bb0060) 2021; 118 Schneider (bb0065) 2020; 13 Liu (bb0010) 2021; 4 Atkinson, Wells (bb0025) 2017; 8 Jayakody (bb0050) 2021; 17 Lynch (bb0005) 2021; 466 Lynch (10.1016/j.tplants.2022.02.009_bb0005) 2021; 466 Brodersen (10.1016/j.tplants.2022.02.009_bb0030) 2016; 103 Zhao (10.1016/j.tplants.2022.02.009_bb0040) 2019; 24 Schneider (10.1016/j.tplants.2022.02.009_bb0065) 2020; 13 Choudhury (10.1016/j.tplants.2022.02.009_bb0055) 2019; 10 Hall (10.1016/j.tplants.2022.02.009_bb0015) 2019; 31 Levin (10.1016/j.tplants.2022.02.009_bb0035) 2021; 40 Atkinson (10.1016/j.tplants.2022.02.009_bb0025) 2017; 8 Schneider (10.1016/j.tplants.2022.02.009_bb0060) 2021; 118 Zhu (10.1016/j.tplants.2022.02.009_bb0070) 2015; 39 Liu (10.1016/j.tplants.2022.02.009_bb0010) 2021; 4 Jayakody (10.1016/j.tplants.2022.02.009_bb0050) 2021; 17 Strock (10.1016/j.tplants.2022.02.009_bb0020) 2019; 70 Lobet (10.1016/j.tplants.2022.02.009_bb0045) 2013; 9 |
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SubjectTerms | anatomy genetic analysis genetic traits high-throughput phenotyping image analysis imaging phenomics phenotype Phenotyping plant analysis plant anatomy planting |
Title | Anatomics: High-throughput phenotyping of plant anatomy |
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