Natural Resources Institute Finland (Luke), 31600 Jokioinen, Finland.
Natural Resources Institute Finland (Luke), 31600 Jokioinen, Finland.
Animal. 2023 Sep;17(9):100917. doi: 10.1016/j.animal.2023.100917. Epub 2023 Jul 22.
The efficiency with which a dairy cow utilises feed for the various physiological and metabolic processes can be evaluated by metrics that contrast realised feed intake with expected feed intake. In this study, we presented a new metric - regression on expected feed intake (ReFI). This metric is based on the idea of regressing DM intake (DMI) on expected DMI using a random regression model, where energy requirement formulations are applied for the calculation of expected DMI covariables. We compared this new metric with the metrics residual feed intake (RFI) and genetic residual feed intake (gRFI), by applying them on 18 581 feed efficiency records from 654 primiparous Nordic Red dairy cows. We estimated variance components for the three metrics and their respective genetic correlations with intake and production traits. In addition, we examined the phenotypes of superior cows. With ReFI, we estimated for feed efficiency a higher genetic variation (4.7%) and heritability (0.23) compared to applying RFI or gRFI. The ReFI metric was genetically uncorrelated with DMI and negatively correlated within energy-corrected milk (ECM), whereas the RFI metric was genetically positively correlated with DMI and metabolic BW. The gRFI metric was genetically positively correlated with DMI and uncorrelated with energy sink traits. Overall, the estimated SE were large. The ReFI metric resulted in a different ranking of cows compared to those based on RFI or gRFI and was superior in selecting the most efficient animals. When the selection was based on ReFI breeding values, then the 10% most efficient cows produced 12.3% more ECM per unit metabolisable energy intake, whereas the corresponding values were only 4.3 or 5.9% when using RFI or gRFI breeding values, respectively. Based on ReFI, superior cows had also higher milk production, whereas based on RFI or gRFI milk production either decreased or was unaffected, respectively. The superiority of the ReFI metric in selecting efficient cows was due to a better modelling of the expected feed intake. The ReFI metric simplified modelling of feed utilisation efficiency in dairy cattle and resulted in breeding values that are equal to percentages of feed saved.
奶牛利用饲料进行各种生理和代谢过程的效率可以通过与实际饲料摄入量相对比的指标来评估。在本研究中，我们提出了一种新的指标 - 预期饲料摄入量的回归（ReFI）。该指标基于使用随机回归模型将干物质摄入量（DMI）回归到预期 DMI 的想法，其中能量需求公式用于计算预期 DMI 协变量。我们将这种新指标与剩余饲料摄入量（RFI）和遗传剩余饲料摄入量（gRFI）进行了比较，将它们应用于 654 头北欧红牛初产奶牛的 18581 个饲料效率记录。我们估计了这三个指标及其与摄入和生产性状的遗传相关性的方差分量。此外，我们还研究了优秀奶牛的表型。应用 ReFI 时，我们估计饲料效率的遗传变异（4.7%）和遗传力（0.23）高于应用 RFI 或 gRFI。ReFI 指标与 DMI 遗传上不相关，与能量校正乳（ECM）内呈负相关，而 RFI 指标与 DMI 和代谢 BW 遗传上呈正相关。gRFI 指标与 DMI 遗传上呈正相关，与能量汇性状无关。总体而言，估计的 SE 较大。与基于 RFI 或 gRFI 的指标相比，ReFI 指标导致了奶牛排名的不同，并且在选择最有效的动物方面表现出色。当基于 ReFI 育种值进行选择时，10%最有效的奶牛每单位可代谢能摄入生产的 ECM 增加了 12.3%，而使用 RFI 或 gRFI 育种值时，相应的值仅为 4.3%或 5.9%。基于 ReFI，优秀奶牛的产奶量也更高，而基于 RFI 或 gRFI，产奶量要么减少，要么不受影响。ReFI 指标在选择高效奶牛方面的优势归因于对预期饲料摄入量的更好建模。ReFI 指标简化了奶牛饲料利用效率的建模，产生的育种值等于节省的饲料百分比。
