Continuous estimation of feed efficiency across the lactation
Problem & Solution
Feed efficiency is a priority for the dairy sector and is traditionally estimated by residual feed intake (RFI). Yet, current methodology does not provide enough flexibility as predictors may vary during lactation. A new methodology based on a multi-trait random regression model that estimates RFI in a dynamic and continuous manner across the lactation was developed.
Outcome
This approach allows a continuous and more precise estimation of RFI over time, accounting for correlations between predictors and free from all time-related issues. RFI for each cow on each day of lactation is estimated as the difference between the actual intake and the intake predicted from three other traits using a multi-trait random regression model.
Practical recommendations
• The model needs continuous repeated measurements (every week or every day) across the lactation, ideally without missing data.
• The amount of data available is important: a sufficient number of cows with enough individual measurements is necessary for the model to work well.
• The model deals relatively smoothly with missing data. However, deduced individual effects that are outside the range of the actual measurements should not be used as a prediction.
• This approach is adaptable, and improvements are possible, e.g., by adding pedigree or genomic information that would allow separating the genetic from the environmental effect.
On-farm application
Individual intake measurements are mostly limited to experimental farms, hampering the application of the model to commercial farms. However, it can be adapted and used in a genetic or genomic selection context, with the aim of establishing a genomic selection on RFI.
GenTORE - Genomic management Tools to Optimise Resilience and Efficiency
Ongoing | 2017-2022
- Main funding source
- Horizon 2020 (EU Research and Innovation Programme)
- Geographical location
- France