Location: Animal Genomics and Improvement Laboratory
Project Number: 8042-31310-114-003-R
Project Type: Reimbursable Cooperative Agreement
Start Date: Feb 1, 2019
End Date: Jul 31, 2024
Objective:
The project objective is to expand existing genomic tools for improving feed efficiency in dairy cattle to enable inclusion of genomic breeding values for feed efficiency in the U.S. Net Merit Index. There are 4 Specific Aims as follows: Aim 1 is to increase the reliability of genomic predictions for feed efficiency on young sires so that efficiency is included in the US Net Merit Index. Aim 2 is to identify proxies for predicting feed intake on individual cows. Aim 3 is to implement a long-term strategy for adding animals to the feed efficiency reference population at a reasonable price so that reliable selection can continue for the next 25 years. Aim 4 is to determine the relationship of methane emissions to feed efficiency and if genomics can be used to predict emissions. The long-term goal is to enable US dairy farmers to make breeding decisions that will decrease feed costs and increase efficiency, sustainability, and profitability.
Approach:
Aim 1 is to increase the reliability of genomic predictions for feed efficiency on young sires so that efficiency is included in the US Net Merit Index. ARS will do this by measuring phenotypes and adding 3500 new cows to our reference population in the next 5 years and by working with Artificial Insemination (AI) companies to increase the number of cows that are full sibs, half sibs, and daughters of the top young bulls in the industry. The added data and closer relationships could potentially double genomic reliability for young calves from the current 12% to above 20% by year 5 of our proposal. Aim 2 is to identify proxies for predicting feed intake on individual cows. We will collect milk spectral data and outfit cows with systems for continuous monitoring of temperature, rumen pH, chewing, rumination, and locomotion to determine if we can enhance the accuracy of DMI predictions, and therefore lessen the need to measure DMI of individual cows. We expect that an index combining these proxies will be correlated with RFI, and this index could be used to supplement our reference population for genomic breeding values and to develop new systems for culling the least efficient animals within a herd. Aim 3 is to implement a long-term strategy for adding animals to the feed efficiency reference population at a reasonable price so that reliable selection can continue for the next 25 years. ARS will seek partners for maintaining intake in research herds and for outfitting some commercial farms with automated feed intake measuring systems and/or monitors from Aim 2. Developing a system for collection of >700 new cows each year that are closely related to the top 70 young bulls is projected to give genomic reliability for RFI at ~40%. ARS will also will continue to develop methods and agreements for international exchanges of feed efficiency data; toward this end, the more US data we have, the more likely it is that international parties will want to make exchanges. Aim 4 is to determine the relationship of methane emissions to feed efficiency and if genomics can be used to predict emissions. Methane emissions will be collected on a sub-fraction of these cows to get estimates on their relationship to RFI in North American cows.
