Feed efficiency of dairy cattle as genetic trait

This review article is devoted to the use of feed efficiency traits in dairy cattle breeding. An efficient cow is defined as the one that produces the same amount of milk and milk solids while consuming less feed and remaining healthy and fertile; thus, allowing to reduce costs without decrease in production. Improving feed efficiency is economically important due to the increasing price of fodder. Feed efficiency is a genetically complex trait that can be described as units of product output (e.g., milk yield) per unit of feed input. Nowadays genetic evaluation of dairy cattle for feed efficiency is routinely conducted in several countries, including Australia, USA, Canada, Netherlands, Denmark, Sweden, Finland, Norway and United Kingdom. Different countries use different measures of feed efficiency of dairy cows. The main feed efficiency traits are dry matter intake, gross feed efficiency, residual feed intake, energy balance and feed saved. Genome-wide association studies demonstrated that feed efficiency in polygenic trait. Nevertheless, several genes with large effects on feed efficiency were identified. Estimates of heritability of these traits vary from 0.07 to 0.49 and show the presence of considerable genetic variation of these traits and therefore, the possibility of their genetic improvement under the conditions of inclusion in breeding programs. Changes in diet and rumen microbiome substantially impact feed efficiency of dairy cows. Feed efficiency is related to methane emissions and excess nitrogen excretion. Genetic improvement of feed efficiency requires recording of individual data on feed intake in cows. Such data are limited. Two options exist to solve this problem: use of indirect predictors and genomic prediction. Accuracy of genomic prediction varies from 0.21 to 0.61 across countries. International cooperative pro­jects such as Efficient Dairy Genome Project in Canada were launched to establish large databases and to increase accuracy of feed efficiency traits genomic prediction. Future directions of research are the use of novel technologies: mid-infrared spectroscopy, artificial intelligence, holo-omics.