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D4.1 Selection of phenotype traits to predict for each business case - Executive Summary

GLOMICAVE aims to exploit the information hidden in the existent scientific literature and large- scale omics datasets for a better understanding of genotype-phenotype relationships. For this purpose, it is essential to define the phenotypes of interest for the three industrial sectors (livestock, agro-biotechnology, and environment) of the project that will be predicted using machine-learning. The partners involved in Task4.1 selected a number of precise phenotypic traits relative to the six business cases (cattle fertility, meat quality, fruit quality, plant growth, pollutant removal, bioenergy production) of the project. The selection included both quantitative and qualitative traits that will be further used as targets for the predictive approaches (regression and classification) deployed by WP4. A total of 72 phenotypic traits (~24 per sector) were selected, of which 46 are quantitative and 26 qualitative. A better understanding of the selected target traits will offer an important contribution to the knowledge advancement of the three industrial sectors.