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
see more details 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
see more details 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
see more details 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
see more details 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
see more details 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
see more details
Descriptor(s) :
biomassbiomassSubject Category: Miscellaneous
see more details, crossescrossesSubject Category: Miscellaneous
see more details, heterosisheterosisSubject Category: Properties
see more details, hybridshybridsSubject Category: Organism Groups
see more details, inbred linesinbred linesSubject Category: Organism Groups
see more details, maizemaizeSubject Category: Commodities and Products
see more details, varietiesvarietiesSubject Category: Organism Groups
see more details
Identifier(s) :
corn, hybrid vigor, hybrid vigour, outbreeding enhancement, pure lines
Broader term(s) :
ZeazeaSubject Category: Organism Names
see more details, PoaceaepoaceaeSubject Category: Organism Names
see more details, PoalespoalesSubject Category: Organism Names
see more details, commelinidscommelinidsSubject Category: Organism Names
see more details, monocotyledonsmonocotyledonsSubject Category: Organism Names
see more details, angiospermsangiospermsSubject Category: Organism Names
see more details, SpermatophytaspermatophytaSubject Category: Organism Names
see more details, plantsplantsSubject Category: Organism Names
see more details, eukaryoteseukaryotesSubject Category: Organism Names
see more details