Myriad applications for genomic information in animal breeding and selection have emerged over the last decade. This is largely due to developments in high-throughput DNA sequencing and genotyping technologies. As animal breeding relies on the availability of accurate and specific phenotype data to reach its goals, phenotyping is increasingly being recognized as a limiting factor in all applications of livestock genetics and genomics. The acquisition of relevant phenotypes is also fundamental to routine and daily management of livestock populations to optimize reproduction strategies, disease control and welfare of the animals and reduce the environmental impact of the animal productions. Consequently, this knowledge gap needs to be filled to facilitate long-term improvement and a sustainable landscape for livestock production that can help meet current challenges in line with the EU Farm to Fork strategy and the United Nations Sustainable Development Goals.

Phenomics is emerging as a major new technical discipline in biology. Phenomics is focused on one major aim: to systematically describe the phenome, referred to as the physical and molecular traits of an organism. This discipline can be defined as the ensemble of methodologies and technologies for the acquisition, analysis, and exploitation of high-dimensional phenotypic data on an organism-wide scale. Depending on the level of analysis, phenotypes can also be classified i) as external or final phenotypes and ii) as internal or molecular phenotypes (endophenotypes). Examples of final phenotypes are performance, morphological, disease resistance and behavioral traits. Examples of molecular phenotypes are the level or the presence/absence of different types of biomolecules (and their modifications) in animal biofluids and tissues and so on. Phenomics can benefit from the development and application of automatic sampling or non-invasive methods to obtain repeated sampling and images, records or continuous data collection (including photographs, videos, sounds, movement traces, and so on) from a part of an animal, the whole individual or a population at different stages, or on the final animal products to describe final external phenotypes with high resolution and in real-time. To capture internal phenotypes, phenomics can also use sequence-based and functional omics technologies to detect and quantify molecular phenotypes (e.g. DNA methylation, RNA transcripts, proteins, metabolites, microbiota, glycomics, etc.).

The major goal of phenomics in the livestock sector is to provide information critical to informed decision-making genetic improvement, as well as to improve on-farm management of animals through the lens of the precision livestock farming (PLF) concept. For practical applications, novel phenotypes should be identified, standardized and their measurement be made economically feasible and automatable for electronic data collection. Development, application, and integration of high-throughput data assembly techniques derived from multiple research disciplines and targeting different biological levels are therefore urgently required. In addition, novel and repurposed analytics and computational approaches will be required to mine and interpret the vast data sets that will accumulate rapidly through application of phenomics to livestock production systems.

The development, integration, organization and practical implementation of technologies and high-performance tools that can be used to scan the animal phenome (including both external and molecular phenotypes), together with the acquisition, interpretation and sharing of the resulting data, are major challenges to improving scientific knowledge of animal biology and livestock production systems. This knowledge will enhance genomic selection strategies and applications and help to implement PLF approaches. Phenomics data should therefore be linked to high-resolution sequence and functional genome information to further expand implementation of genome-enabled breeding technologies. Livestock phenomics is a data analytics (“big data”) discipline that is focused on livestock species.

The development and the application of phenomics in livestock clearly requires multi-disciplinary and multi-actor approaches to bring together different expertise, resources, and expectations. This will allow projection of a vision of the livestock production sector over the next 30 years. Livestock phenomics requires experts in many fields (e.g. animal breeding and genetics, animal science, animal feeding and nutrition, animal welfare, veterinary medicine, genomics, transcriptomics, metabolomics, proteomics, biomedicine, epidemiology, engineering, chemistry, physics, informatics, bioinformatics, database management, law, economics, and the social sciences) and animal science areas (e.g. researchers, breeding industries, associations, farmers and policy and decision makers). Therefore, there is a need to create a European-based network able to respond to the complex scientific, technical, and societal challenges that will need to be tackled in the context of livestock phenomics. The main aim of EU-LIPHE is to create a Europe-centered multidisciplinary, interconnected, and inclusive community of experts from COST Members, COST Near Neighbor Countries (NNC) and International Partner Countries (IPC), involving researchers, industry representatives, policy makers and other relevant stakeholders. This multi-actor group will enhance scientific collaboration, catalyze developments, and transfer livestock phenomics concepts and applications to improve the sustainability and competitiveness of the European livestock production sector. Furthermore, EU-LI-PHE will generate and disseminate knowledge about emerging and innovative animal phenotyping technologies and approaches to dissecting, cataloguing, and understanding animal phenomes. It will also prepare the next generation of animal scientists for the advent of phenomics as a big data discipline. It will be interconnected with the other major 21^st century biological disciplines and will communicate and inform decision makers and society at large about the foreseen and unforeseen novel innovations that will positively impact food security in Europe, taking into account the reduction of the environmental impact of the livestock productions, as a consequence of the application of phenomics to livestock populations.