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      Dynamic plant height QTL revealed in maize through remote sensing phenotyping using a high-throughput unmanned aerial vehicle (UAV)

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          Abstract

          Plant height (PH) is a key factor in maize ( Zea mays L.) yield, biomass, and plant architecture. We investigated the PH of diverse maize inbred lines (117 temperate lines, 135 tropical lines) at four growth stages using unmanned aerial vehicle high-throughput phenotypic platforms (UAV-HTPPs). We extracted PH data using an automated pipeline based on crop surface models and orthomosaic model. The correlation between UAV and manually measured PH data reached 0.95. Under temperate field conditions, temperate maize lines grew faster than tropical maize lines at early growth stages, but tropical lines grew faster at later growth stages and ultimately became taller than temperate lines. A genome-wide association study identified 68 unique quantitative trait loci (QTLs) for seven PH-related traits, and 35% of the QTLs coincided with those previously reported to control PH. Generally, different QTLs controlled PH at different growth stages, but eight QTLs simultaneously controlled PH and growth rate at multiple growth stages. Based on gene annotations and expression profiles, we identified candidate genes controlling PH. The PH data collected by the UAV-HTPPs were credible and the genetic mapping power was high. Therefore, UAV-HTPPs have great potential for use in studies on PH.

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          Green revolution: a mutant gibberellin-synthesis gene in rice.

          The chronic food shortage that was feared after the rapid expansion of the world population in the 1960s was averted largely by the development of a high-yielding semi-dwarf variety of rice known as IR8, the so-called rice 'green revolution'. The short stature of IR8 is due to a mutation in the plant's sd1 gene, and here we identify this gene as encoding an oxidase enzyme involved in the biosynthesis of gibberellin, a plant growth hormone. Gibberellin is also implicated in green-revolution varieties of wheat, but the reduced height of those crops is conferred by defects in the hormone's signalling pathway.
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            Color Indices for Weed Identification Under Various Soil, Residue, and Lighting Conditions

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              Estimating Biomass of Barley Using Crop Surface Models (CSMs) Derived from UAV-Based RGB Imaging

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                Author and article information

                Contributors
                rentlang2003@163.com
                maizezhao@126.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                5 March 2019
                5 March 2019
                2019
                : 9
                : 3458
                Affiliations
                [1 ]ISNI 0000 0004 0646 9053, GRID grid.418260.9, Beijing Key Laboratory of Maize DNA Fingerprinting and Molecular Breeding, Maize Research Center, , Beijing Academy of Agriculture & Forestry Sciences, ; Beijing, 100097 China
                [2 ]Key Laboratory of Quantitative Remote Sensing in Agriculture of Ministry of Agriculture, Beijing Research Center for Information Technology in Agriculture, Beijing, 100097 China
                [3 ]ISNI 0000 0004 1757 5302, GRID grid.440639.c, College of Architecture and Geomatics Engineering, , Shanxi Datong University, ; Datong, 037009 China
                [4 ]ISNI 0000 0004 1790 4137, GRID grid.35155.37, Key Laboratory of Agricultural Animal Genetics, Breeding and Reproduction, Ministry of Education, College of Animal Science and Technology, , Huazhong Agricultural University, ; Wuhan, 430070 China
                Author information
                http://orcid.org/0000-0003-2044-6846
                Article
                39448
                10.1038/s41598-019-39448-z
                6401315
                30837510
                bfd829c3-275e-484e-ae49-7feabbe04498
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 November 2018
                : 25 January 2019
                Funding
                Funded by: the Science and Technology Planning Project of Beijing (D161100005716002)
                Funded by: the National Key Research and Development Program of China (2016YFD0300106) the Sci-Tech Innovative Ability Project (KJCX20170423) the Innovative Team Construction Project of BAAFS (JNKYT201603) China Agriculture Research System (CARS-02-11) the Beijing Scholars Program (BSP041)
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