@article{EdlichMuthMurayaAltmannetal.2016,
  author    = {Edlich-Muth, Christian and Muraya, Moses M. and Altmann, Thomas and Selbig, Joachim},
  title     = {Phenomic prediction of maize hybrids},
  series = {Biosystems : journal of biological and information processing sciences},
  volume    = {146},
  journal   = {Biosystems : journal of biological and information processing sciences},
  publisher = {Elsevier},
  address   = {Oxford},
  issn      = {0303-2647},
  doi       = {10.1016/j.biosystems.2016.05.008},
  pages     = {102 -- 109},
  year      = {2016},
  abstract  = {Phenomic experiments are carried out in large-scale plant phenotyping facilities that acquire a large number of pictures of hundreds of plants 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 biomass of the fully grown plant from early developmental stage image-derived features. We performed phenomic experiments on 195 inbred and 382 hybrid maizes varieties 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 lines 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 heterosis 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. (C) 2016 Elsevier Ireland Ltd. All rights reserved.},
  language  = {en}
}
@article{CwiekKupczynskaAltmannArendetal.2016,
  author    = {´Cwiek-Kupczynska, Hanna and Altmann, Thomas and Arend, Daniel and Arnaud, Elizabeth and Chen, Dijun and Cornut, Guillaume and Fiorani, Fabio and Frohmberg, Wojciech and Junker, Astrid and Klukas, Christian and Lange, Matthias and Mazurek, Cezary and Nafissi, Anahita and Neveu, Pascal and van Oeveren, Jan and Pommier, Cyril and Poorter, Hendrik and Rocca-Serra, Philippe and Sansone, Susanna-Assunta and Scholz, Uwe and van Schriek, Marco and Seren, {\"U}mit and Usadel, Bjorn and Weise, Stephan and Kersey, Paul and Krajewski, Pawel},
  title     = {Measures for interoperability of phenotypic data: minimum information requirements and formatting},
  series = {Plant Methods},
  volume    = {12},
  journal   = {Plant Methods},
  publisher = {BioMed Central},
  address   = {London},
  issn      = {1746-4811},
  doi       = {10.1186/s13007-016-0144-4},
  pages     = {18},
  year      = {2016},
  abstract  = {Background: Plant phenotypic data shrouds a wealth of information which, when accurately analysed and linked to other data types, brings to light the knowledge about the mechanisms of life. As phenotyping is a field of research comprising manifold, diverse and time-consuming experiments, the findings can be fostered by reusing and combining existing datasets. Their correct interpretation, and thus replicability, comparability and interoperability, is possible provided that the collected observations are equipped with an adequate set of metadata. So far there have been no common standards governing phenotypic data description, which hampered data exchange and reuse. Results: In this paper we propose the guidelines for proper handling of the information about plant phenotyping experiments, in terms of both the recommended content of the description and its formatting. We provide a document called "Minimum Information About a Plant Phenotyping Experiment", which specifies what information about each experiment should be given, and a Phenotyping Configuration for the ISA-Tab format, which allows to practically organise this information within a dataset. We provide examples of ISA-Tab-formatted phenotypic data, and a general description of a few systems where the recommendations have been implemented. Conclusions: Acceptance of the rules described in this paper by the plant phenotyping community will help to achieve findable, accessible, interoperable and reusable data.},
  language  = {en}
}
@misc{ĆwiekKupczyńskaAltmannArendetal.2016,
  author    = {Ćwiek-Kupczyńska, Hanna and Altmann, Thomas and Arend, Daniel and Arnaud, Elizabeth and Chen, Dijun and Cornut, Guillaume and Fiorani, Fabio and Frohmberg, Wojciech and Junker, Astrid and Klukas, Christian and Lange, Matthias and Mazurek, Cezary and Nafissi, Anahita and Neveu, Pascal and van Oeveren, Jan and Pommier, Cyril and Poorter, Hendrik and Rocca-Serra, Philippe and Sansone, Susanna-Assunta and Scholz, Uwe and van Schriek, Marco and Seren, {\"U}mit and Usadel, Bj{\"o}rn and Weise, Stephan and Kersey, Paul and Krajewski, Paweł},
  title     = {Measures for interoperability of phenotypic data},
  series = {Plant methods},
  journal   = {Plant methods},
  url       = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-407299},
  pages     = {18},
  year      = {2016},
  abstract  = {Background: Plant phenotypic data shrouds a wealth of information which, when accurately analysed and linked to other data types, brings to light the knowledge about the mechanisms of life. As phenotyping is a field of research comprising manifold, diverse and time ‑consuming experiments, the findings can be fostered by reusing and combin‑ ing existing datasets. Their correct interpretation, and thus replicability, comparability and interoperability, is possible provided that the collected observations are equipped with an adequate set of metadata. So far there have been no common standards governing phenotypic data description, which hampered data exchange and reuse. Results: In this paper we propose the guidelines for proper handling of the information about plant phenotyping experiments, in terms of both the recommended content of the description and its formatting. We provide a docu‑ ment called "Minimum Information About a Plant Phenotyping Experiment", which specifies what information about each experiment should be given, and a Phenotyping Configuration for the ISA ‑Tab format, which allows to practically organise this information within a dataset. We provide examples of ISA ‑Tab ‑formatted phenotypic data, and a general description of a few systems where the recommendations have been implemented. Conclusions: Acceptance of the rules described in this paper by the plant phenotyping community will help to achieve findable, accessible, interoperable and reusable data.},
  language  = {en}
}