Multiple-trait random regression modeling of feed efficiency in US Holsteins
ABSTRACT: Residual feed intake (RFI) and feed saved (FS) are important feed efficiency traits that have been increasingly considered in genetic improvement programs. Future sustainability of these genetic evaluations will depend upon greater flexibility to accommodate sparsely recorded dry matter in...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-07-01
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| Series: | Journal of Dairy Science |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S0022030222003186 |
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| author | P. Khanal K.L. Parker Gaddis M.J. Vandehaar K.A. Weigel H.M. White F. Peñagaricano J.E. Koltes J.E.P. Santos R.L. Baldwin J.F. Burchard J.W. Dürr R.J. Tempelman |
| author_facet | P. Khanal K.L. Parker Gaddis M.J. Vandehaar K.A. Weigel H.M. White F. Peñagaricano J.E. Koltes J.E.P. Santos R.L. Baldwin J.F. Burchard J.W. Dürr R.J. Tempelman |
| author_sort | P. Khanal |
| collection | DOAJ |
| description | ABSTRACT: Residual feed intake (RFI) and feed saved (FS) are important feed efficiency traits that have been increasingly considered in genetic improvement programs. Future sustainability of these genetic evaluations will depend upon greater flexibility to accommodate sparsely recorded dry matter intake (DMI) records on many more cows, especially from commercial environments. Recent multiple-trait random regression (MTRR) modeling developments have facilitated days in milk (DIM)-specific inferences on RFI and FS, particularly in modeling the effect of change in metabolic body weight (MBW). The MTRR analyses, using daily data on the core traits of DMI, MBW, and milk energy (MilkE), were conducted separately for 2,532 primiparous and 2,379 multiparous US Holstein cows from 50 to 200 DIM. Estimated MTRR variance components were used to derive genetic RFI and FS and DIM-specific genetic partial regressions of DMI on MBW, MilkE, and change in MBW. Estimated daily heritabilities of RFI and FS varied across lactation for both primiparous (0.05–0.07 and 0.11–0.17, respectively) and multiparous (0.03–0.13 and 0.10–0.17, respectively) cows. Genetic correlations of RFI across DIM varied (>0.05) widely compared with FS (>0.54) within either parity class. Heritability estimates based on average lactation-wise measures were substantially larger than daily heritabilities, ranging from 0.17 to 0.25 for RFI and from 0.35 to 0.41 for FS. The partial genetic regression coefficients of DMI on MBW (0.11 to 0.16 kg/kg0.75 for primiparous and 0.12 to 0.14 kg/kg0.75 for multiparous cows) and of DMI on MilkE (0.45 to 0.68 kg/Mcal for primiparous and 0.36 to 0.61 kg/Mcal for multiparous cows) also varied across lactation. In spite of the computational challenges encountered with MTRR, the model potentially facilitates an efficient strategy for harnessing more data involving a wide variety of data recording scenarios for genetic evaluations on feed efficiency. |
| first_indexed | 2024-12-12T08:39:33Z |
| format | Article |
| id | doaj.art-4474809b91e24f749112ed10a83d89c8 |
| institution | Directory Open Access Journal |
| issn | 0022-0302 |
| language | English |
| last_indexed | 2024-12-12T08:39:33Z |
| publishDate | 2022-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of Dairy Science |
| spelling | doaj.art-4474809b91e24f749112ed10a83d89c82022-12-22T00:30:49ZengElsevierJournal of Dairy Science0022-03022022-07-01105759545971Multiple-trait random regression modeling of feed efficiency in US HolsteinsP. Khanal0K.L. Parker Gaddis1M.J. Vandehaar2K.A. Weigel3H.M. White4F. Peñagaricano5J.E. Koltes6J.E.P. Santos7R.L. Baldwin8J.F. Burchard9J.W. Dürr10R.J. Tempelman11Department of Animal Science, Michigan State University, East Lansing 48824-1225Council on Dairy Cattle Breeding, Bowie, MD 20716Department of Animal Science, Michigan State University, East Lansing 48824-1225Department of Animal and Dairy Sciences, University of Wisconsin, Madison 53706Department of Animal and Dairy Sciences, University of Wisconsin, Madison 53706Department of Animal and Dairy Sciences, University of Wisconsin, Madison 53706Department of Animal Science, Iowa State University, Ames 50011Department of Animal Science, University of Florida, Gainesville 32608Animal Genomics and Improvement Laboratory, Agricultural Research Service, USDA, Beltsville, MD 20705Council on Dairy Cattle Breeding, Bowie, MD 20716Council on Dairy Cattle Breeding, Bowie, MD 20716Department of Animal Science, Michigan State University, East Lansing 48824-1225; Corresponding authorABSTRACT: Residual feed intake (RFI) and feed saved (FS) are important feed efficiency traits that have been increasingly considered in genetic improvement programs. Future sustainability of these genetic evaluations will depend upon greater flexibility to accommodate sparsely recorded dry matter intake (DMI) records on many more cows, especially from commercial environments. Recent multiple-trait random regression (MTRR) modeling developments have facilitated days in milk (DIM)-specific inferences on RFI and FS, particularly in modeling the effect of change in metabolic body weight (MBW). The MTRR analyses, using daily data on the core traits of DMI, MBW, and milk energy (MilkE), were conducted separately for 2,532 primiparous and 2,379 multiparous US Holstein cows from 50 to 200 DIM. Estimated MTRR variance components were used to derive genetic RFI and FS and DIM-specific genetic partial regressions of DMI on MBW, MilkE, and change in MBW. Estimated daily heritabilities of RFI and FS varied across lactation for both primiparous (0.05–0.07 and 0.11–0.17, respectively) and multiparous (0.03–0.13 and 0.10–0.17, respectively) cows. Genetic correlations of RFI across DIM varied (>0.05) widely compared with FS (>0.54) within either parity class. Heritability estimates based on average lactation-wise measures were substantially larger than daily heritabilities, ranging from 0.17 to 0.25 for RFI and from 0.35 to 0.41 for FS. The partial genetic regression coefficients of DMI on MBW (0.11 to 0.16 kg/kg0.75 for primiparous and 0.12 to 0.14 kg/kg0.75 for multiparous cows) and of DMI on MilkE (0.45 to 0.68 kg/Mcal for primiparous and 0.36 to 0.61 kg/Mcal for multiparous cows) also varied across lactation. In spite of the computational challenges encountered with MTRR, the model potentially facilitates an efficient strategy for harnessing more data involving a wide variety of data recording scenarios for genetic evaluations on feed efficiency.http://www.sciencedirect.com/science/article/pii/S0022030222003186residual feed intakefeed savedmultiple traitrandom regression |
| spellingShingle | P. Khanal K.L. Parker Gaddis M.J. Vandehaar K.A. Weigel H.M. White F. Peñagaricano J.E. Koltes J.E.P. Santos R.L. Baldwin J.F. Burchard J.W. Dürr R.J. Tempelman Multiple-trait random regression modeling of feed efficiency in US Holsteins Journal of Dairy Science residual feed intake feed saved multiple trait random regression |
| title | Multiple-trait random regression modeling of feed efficiency in US Holsteins |
| title_full | Multiple-trait random regression modeling of feed efficiency in US Holsteins |
| title_fullStr | Multiple-trait random regression modeling of feed efficiency in US Holsteins |
| title_full_unstemmed | Multiple-trait random regression modeling of feed efficiency in US Holsteins |
| title_short | Multiple-trait random regression modeling of feed efficiency in US Holsteins |
| title_sort | multiple trait random regression modeling of feed efficiency in us holsteins |
| topic | residual feed intake feed saved multiple trait random regression |
| url | http://www.sciencedirect.com/science/article/pii/S0022030222003186 |
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