A strategy to maximize genetic gain in dairy farming is to identify genetically elite females through genomic testing. Indeed, direct genomic values (DGV) are early accessible at a cost-effective also in young stock and are subsequently blended to estimated breeding values (GEBV) once prediction of genetic merit is undertaken when phenotypes are available. These criteria can be used by farmers to rank females and service the best ones with (sexsorted) semen of elite bulls to achieve greater gain while simultaneously reducing the number of non-productive animals. Feed efficiency is nowadays the most popular issue for animal scientists working with ruminants. The purpose of the current research was to validate feed efficiency breeding values using real dry matter intake (DMI) data. For this purpose, we quantified the association between DGV/GEBV of predicted feed efficiency (PFE) and on-field feed intake data. Up to date, the total number of genotyped subjects at the UNIBO experimental herd is 279. Cows are routinely enrolled into experimental nutritional trials in which individual DMI (kg/d) information are collected on a daily basis. DGV/GEBV for PFE are calculated by ANAFIBJ within the national genetic and genomic evaluation; proofs are standardized to a mean of 100 and standard deviation of 5. Data were analysed with a linear mixed model, separately for primiparae and pluriparae, by adjusting the dependant variable DMI for the fixed effects of daily milk yield (linear covariate), PFE DGV/GEBV (two classes: <100 or ≥100), and days-post-calving (<120 or ≥120); random terms were cow nested within experimental trial and contemporary group (experimental trial-test date). Mean PFE was 99.50 (±1.48) while daily individual DMI averaged 23.48 (±3.44) and 26.91 (±3.14) kg/d for primiparae and pluriparae, respectively. The Pearson’s correlation coefficient between PFE and feed intake was −0.14, suggesting that cows with higher genetic merit have lower DMI. Differences between least squares means of the two PFE levels were −0.23 (±1.10; p > 0.05) and −0.26 (±0.75; p > 0.05) kg DMI/d in first- and later-parity cows, respectively. Although not significantly different, estimates indicated that, irrespective of systematic effects, cows with higher genetic merit for PFE have a lower individual daily intake compared to those with a lower genetic merit. Future efforts should be pursued to augment the sample size in order to increase the robustness of these estimates.

Visentin Giulio, B.G. (2023). Validation of genomic breeding values for feed efficiency using field data: experience from UNIBO experimental herd. Taylor & Francis.

Validation of genomic breeding values for feed efficiency using field data: experience from UNIBO experimental herd

Visentin Giulio;Buonaiuto Giovanni;Cavallini Damiano;Costa Angela;Formigoni Andrea
2023

Abstract

A strategy to maximize genetic gain in dairy farming is to identify genetically elite females through genomic testing. Indeed, direct genomic values (DGV) are early accessible at a cost-effective also in young stock and are subsequently blended to estimated breeding values (GEBV) once prediction of genetic merit is undertaken when phenotypes are available. These criteria can be used by farmers to rank females and service the best ones with (sexsorted) semen of elite bulls to achieve greater gain while simultaneously reducing the number of non-productive animals. Feed efficiency is nowadays the most popular issue for animal scientists working with ruminants. The purpose of the current research was to validate feed efficiency breeding values using real dry matter intake (DMI) data. For this purpose, we quantified the association between DGV/GEBV of predicted feed efficiency (PFE) and on-field feed intake data. Up to date, the total number of genotyped subjects at the UNIBO experimental herd is 279. Cows are routinely enrolled into experimental nutritional trials in which individual DMI (kg/d) information are collected on a daily basis. DGV/GEBV for PFE are calculated by ANAFIBJ within the national genetic and genomic evaluation; proofs are standardized to a mean of 100 and standard deviation of 5. Data were analysed with a linear mixed model, separately for primiparae and pluriparae, by adjusting the dependant variable DMI for the fixed effects of daily milk yield (linear covariate), PFE DGV/GEBV (two classes: <100 or ≥100), and days-post-calving (<120 or ≥120); random terms were cow nested within experimental trial and contemporary group (experimental trial-test date). Mean PFE was 99.50 (±1.48) while daily individual DMI averaged 23.48 (±3.44) and 26.91 (±3.14) kg/d for primiparae and pluriparae, respectively. The Pearson’s correlation coefficient between PFE and feed intake was −0.14, suggesting that cows with higher genetic merit have lower DMI. Differences between least squares means of the two PFE levels were −0.23 (±1.10; p > 0.05) and −0.26 (±0.75; p > 0.05) kg DMI/d in first- and later-parity cows, respectively. Although not significantly different, estimates indicated that, irrespective of systematic effects, cows with higher genetic merit for PFE have a lower individual daily intake compared to those with a lower genetic merit. Future efforts should be pursued to augment the sample size in order to increase the robustness of these estimates.
2023
ASPA 25th Congress Book of Abstract
259
259
Visentin Giulio, B.G. (2023). Validation of genomic breeding values for feed efficiency using field data: experience from UNIBO experimental herd. Taylor & Francis.
Visentin Giulio, Buonaiuto Giovanni, Cavallini Damiano, Finocchiaro Raffaella, Cassandro Martino, Costa Angela, Formigoni Andrea
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/936033
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