Selection indexes for residual feed intake derived from milk spectra

Area of Science:

• Animal Science
• Genetics
• Agricultural Engineering

Background:

• Improving dairy production efficiency and reducing environmental impact are key industry goals.
• Enhanced feed-to-milk conversion efficiency is essential for sustainable dairy farming.
• Current methods for measuring feed efficiency in commercial herds are impractical, hindering genetic selection.

Purpose of the Study:

• To evaluate the genetic accuracy of selection indexes derived from milk's Fourier-transform mid-infrared (FTIR) spectra.
• To assess the feasibility of indirect selection for residual feed intake (RFI) using FTIR spectral data.
• To compare the accuracy of FTIR-based indexes with direct phenotypic selection for RFI.

Main Methods:

• Utilized 7,793 weekly records from 537 genotyped cows, including residual feed intake (RFI) and FTIR spectra.
• Fitted various selection indexes using complete FTIR milk spectra data.
• Estimated the heritability of RFI and calculated the accuracy of indirect selection indexes.

Main Results:

• The estimated heritability of RFI was 0.12 ± 0.02.
• Indirect selection accuracy was highest with a principal components index (0.16 ± 0.07), followed by a penalized index (0.14 ± 0.06).
• An index based on spectral data from ~25 daughters showed accuracy comparable to direct phenotypic selection for RFI.

Conclusions:

• Indirect selection for RFI using FTIR milk spectra data is a viable strategy for genetic improvement in dairy cattle.
• FTIR-based selection indexes, especially when utilizing progeny data, can achieve significant accuracy.
• Further research with larger sample sizes is recommended to validate these findings and optimize the application of FTIR technology in dairy breeding programs.