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  • Phenomic prediction of maize hybrids.

    Author(s) : Edlich-Muth, C.Muraya, M. M.Altmann, T.Selbig, J.

    Author Affiliation : Bioinformatics Group, Institute for Biochemistry and Biology, University of Potsdam, Potsdam 14476, Germany.

    Author Email : edlich@mpimp-golm.mpg.de

    Journal article : BioSystems 2016 Vol.146 pp.102-109

    Abstract : Phenomic experiments are carried out in large-scale plant phenotyping facilities that acquire a large number of pictures of hundreds of plantsplantsSubject Category: Organism Names
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    simultaneously. With the aid of automated image processing, the data are converted into genotype-feature matrices that cover many consecutive days of development. Here, we explore the possibility of predicting the biomassbiomassSubject Category: Miscellaneous
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    of the fully grown plant from early developmental stage image-derived features. We performed phenomic experiments on 195 inbred and 382 hybrid maizes varietiesvarietiesSubject Category: Organism Groups
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    and followed their progress from 16 days after sowing (DAS) to 48 DAS with 129 image-derived features. By applying sparse regression methods, we show that 73% of the variance in hybrid fresh weight of fully-grown plants is explained by about 20 features at the three-leaf-stage or earlier. Dry weight prediction explained over 90% of the variance. When phenomic features of parental inbred linesinbred linesSubject Category: Organism Groups
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    were used as predictors of hybrid biomass, the proportion of variance explained was 42 and 45%, for fresh weight and dry weight models consisting of 35 and 36 features, respectively. These models were very robust, showing only a small amount of variation in performance over the time scale of the experiment. We also examined mid-parent heterosisheterosisSubject Category: Properties
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    in phenomic features. Feature heterosis displayed a large degree of variance which resulted in prediction performance that was less robust than models of either parental or hybrid predictors. Our results show that phenomic prediction is a viable alternative to genomic and metabolic prediction of hybrid performance. In particular, the utility of early-stage parental lines is very encouraging.

    ISSN : 0303-2647

    DOI : 10.1016/j.biosystems.2016.05.008

    Record Number : 20163342525

    Publisher : Elsevier Ltd

    Location of publication : Oxford

    Country of publication : UK

    Language of text : English

    Indexing terms for this abstract:

    Organism descriptor(s) : Zea mayszea maysSubject Category: Organism Names
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    Descriptor(s) : biomassbiomassSubject Category: Miscellaneous
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    , crossescrossesSubject Category: Miscellaneous
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    , heterosisheterosisSubject Category: Properties
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    , hybridshybridsSubject Category: Organism Groups
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    , inbred linesinbred linesSubject Category: Organism Groups
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    , maizemaizeSubject Category: Commodities and Products
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    , varietiesvarietiesSubject Category: Organism Groups
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    Identifier(s) : corn, hybrid vigor, hybrid vigour, outbreeding enhancement, pure lines

    Broader term(s) : ZeazeaSubject Category: Organism Names
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    , PoaceaepoaceaeSubject Category: Organism Names
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    , PoalespoalesSubject Category: Organism Names
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    , commelinidscommelinidsSubject Category: Organism Names
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    , monocotyledonsmonocotyledonsSubject Category: Organism Names
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    , angiospermsangiospermsSubject Category: Organism Names
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    , SpermatophytaspermatophytaSubject Category: Organism Names
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    , plantsplantsSubject Category: Organism Names
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    , eukaryoteseukaryotesSubject Category: Organism Names
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