New high-throughput phenotyping techniques are changingplant sciences in general and plant breeding in particular. Theyproduce huge volumes of data points through time requiringspecial statistical methods to extract meaningful information forplant breeding purposes.
The course introduces infrastructure needed for field and indoorplatform phenomics. Then specific experimental designs andcorresponding mixed models will be treated in detail togetherwith spatial and longitudinal modelling. Statistical and machinelearning techniques will be presented for pre-processing ofphenomic data. Methodologies for the identification of thegenetic basis of new phenotypic traits will be demonstrated.Finally, phenomic traits will be integrated in prediction modelsfor yield. Examples and exercises will use real data fromphenotyping platforms and field experiments.
New high-throughput phenotyping techniques are changingplant sciences in general and plant breeding in particular. Theyproduce huge volumes of data points through time requiringspecial statistical methods to extract meaningful information forplant breeding purposes.
The course introduces infrastructure needed for field and indoorplatform phenomics. Then specific experimental designs andcorresponding mixed models will be treated in detail togetherwith spatial and longitudinal modelling. Statistical and machinelearning techniques will be presented for pre-processing ofphenomic data. Methodologies for the identification of thegenetic basis of new phenotypic traits will be demonstrated.Finally, phenomic traits will be integrated in prediction modelsfor yield. Examples and exercises will use real data fromphenotyping platforms and field experiments.