Best prediction of actual lactation yields. My credentials. Best Prediction VanRaden JDS 80:3015-3022 (1997), 6 th WCGALP XXIII:347-350 (1998) . Selection Index Predict missing yields from measured yields. Condense test days into lactation yield and persistency.
Predict missing yields from measured yields.
Condense test days into lactation yield and
Only phenotypic covariances are needed.
Mean and variance of herd assumed known.
Daily yield predicted from lactation yield and persistency.
Single or multiple trait prediction
Calculation of lactation records for milk (M), fat (F), protein (P), and somatic cell score (SCS) using best prediction (BP) began in November 1999.
Replaced the test interval method and projection factors at AIPL.
Used for cows calving in January 1997 and later.
Small for most 305-d lactations but larger for lactations with infrequent testing or missing component samples.
More precise estimation of records for SCS because test days are adjusted for stage of lactation.
Yield records have slightly lower SD because BP regresses estimates toward the herd average.
AIPL: Calculation of lactation yields and data collection ratings (DCR).
DCR indicates the accuracy of lactation records obtained from BP.
Breed Associations: Publish DCR on pedigrees.
DRPCs: Interested in replacing test interval estimates with BP.
Can also calculate persistency.
May have management applications.
Limited to 305-d lactations used since 1935.
Used simple linear interpolation for calculation of standard curves.
Could not obtain BP for individual days of lactation.
Difficult to change parameters.
Can accommodate lactations of any length (tested to 999 d).
Lactation-to-date and projected yields calculated.
BP of daily yields, test day yields, and standard curves now output.
The function which models correlations among test day yields was updated.
Inputs: TD and herd averages in
Standard curve calculated
Cow’s lactation curve based on TD deviations from standard curve
Outputs: Actual lactation yields, persistency, and daily BP of yield
Dematawewa et al. (2007) recommend simple models, such as Wood's (1967) curve, for long lactations.
Curves were developed for M, F, and P yield, but not SCS.
Little previous work on fitting lactation curves to SCS (Rodriguez-Zas et al., 2000).
BP also requires curves for the standard deviation (SD) of yields.
Holstein TD data were extracted from the national dairy database.
The data of Dematawewa et al. (2007) were used.
1st through 5th parities
Lactations were at least 250 d for the 305 d group and800 dfor the999 dgroup.
Records were made in a single herd.
At least five tests reported.
Only twice-daily milking reported.
Test day yields were assigned to 30-d intervals and means and SD were calculated for each interval.
Curves were fit to the resulting means (SCS) and SD (all traits).
SD of yield modeled with Woods curves.
SCS means and SD modeled using curve C4 from Morant and Gnanasakthy (1989).
Rather than calculate each correlation separately we use a formula to approximate them.
Our model accounts for biological changes and daily measurement error.
The programs were updated to use a simpler formula with similar accuracy.
Example – HO 2nd versus JE 2nd
MT uses information on 3 or 4 traits simultaneously.
Provides more accurate estimates of components yield.
Advantage greatest with infrequent testing or missing component samples.
Canavesi et al. (2007)
Daily yields can be adjusted for known sources of variation.
Example: Daily loss from clinical mastitis (Rajala-Schultz et al., 1999).
This could lead to animal-specific rather than group-specific adjustments.
Research into optimal management strategies.
Management support in on-farm computer software.
When testing is complete:
Yields in the AIPL database will be updated.
Data will be submitted to Interbull for a test run.
The BP programs have been sent to 4 DRPCs for testing.
Correlations among successive test days may require periodic re-estimation as lactation curves change.
Many cows can produce profitably for >305 days in milk, and the revised BP program provides a flexible tool to model those records.
Daily BP of yields may be useful for on-farm management.