Crop growth models for the -omics era: the EU-SPICY project

The prediction of phenotypic responses from genetic and environmental information is an area of active research in genetics, physiology and statistics. Rapidly increasing amounts of phenotypic information become available as a consequence of high throughput phenotyping techniques, while more and cheaper genotypic data follow from the development of new genotyping platforms. , A wide array of -omics data can be generated linking genotype and phenotype. Continuous monitoring of environmental conditions has become an accessible option. This wealth of data requires a drastic rethinking of the traditional quantitative genetic approach to modeling phenotypic variation in terms of genetic and environmental differences. Where in the past a single phenotypic trait was partitioned in a genetic and environmental component by analysis of variance techniques, nowadays we desire to model multiple, interrelated and often time dependent, phenotypic traits as a function of genes (QTLs) and environmental inputs, while we would like to include transcription information as well. The EU project 'Smart tools for Prediction and Improvement of Crop Yield' (KBBE-2008-211347), or SPICY, aims at the development of genotype-to-phenotype models that fully integrate genetic, genomic, physiological and environmental information to achieve accurate phenotypic predictions across a wide variety of genetic and environmental configurations. Pepper (Capsicum annuum) is chosen as the model crop, because of the availability of genetically characterized populations and of generic models for continuous crop growth and greenhouse production. In the presentation the objectives and structure of SPICY as well as its philosophy will be discussed