# Presentation: 103217

## Genetic Evaluation of Calving Traits in US Holsteins

## Introduction

**A national evaluation was implemented for calving ease (****CE****) in August 2002 and for stillbirth (****SB****) for Holstein in August 2006.**
**A calving ability index (****CA$****) which includes SB and calving ease (****CE****) was developed.**
**Some challenges with the CE and SB evaluations remain**

## History

**1977 – NAAB-sponsored evaluations within AI organizations**
**1980 – NAAB-sponsored evaluations across AI organizations**
**1988 – Ordered categorical threshold model**
**1990 – Semiannual evaluations**
**1999 – Processing change from Iowa State University to USDA (November)**
**2002 – Sire-maternal grandsire (MGS) model**

## Threshold model

**Scores assumed to be observations on a continuous underlying scale**
**Thresholds estimated to relate observed scores to underlying scale**

**Procedure allows for differences in amount of change between consecutive scores**

**Observed scores**

## Calving Ease Definition

**Reported on a five-point scale:**
**	****	****1 = No problem**
**	****	****2 = Slight problem**
**	****	****3 = Needed assistance**
**	****	****4 = Considerable force**
**	****	****5 = Extreme difficulty**
**Scores of 4 and 5 are combined**

## Stillbirth Definition

**Reported on a three-point scale:**
**Scores of 2 and 3 are combined**

| 1 = calf born alive, |
| --- |
| 2 = calf born dead, |
| 3 = calf died within 48 h of parturition. |

## Distribution of Stillbirth and Calving Ease Scores

- Calving Ease Score

- Stillbirth Score

## Stillbirth Records by Lactation

## Detecting Stillbirth Data Errors

## Data and Edits

**7 million**** SB records were available for Holstein cows calving since 1980**
**Herds needed ≥10 calving records with SB scores of 2 or 3 for inclusion**
**Herd-years were required to include ≥20 records**
**Only single births were used (no twins)**

## Sire-MGS Threshold Model

**Implemented for calving ease (Aug 2002) and stillbirth (Aug 2006)**
**Sire effects allow for corrective matings in heifers to avoid large calves**
**MGS effects control against selection for small animals which would have difficulty calving**

## Genetic Evaluation Model

**A sire-maternal grandsire (****MGS****) threshold model was used:**
**Fixed:**** year-season, parity-sex, sire and MGS birth year**
**Random:**** herd-year, sire, MGS**
**(Co)variance components were estimated by Gibbs sampling**
**Heritabilities are ****3.0%**** (direct) and ****6.5%**** (MGS)**

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## Trait Definition

**PTA are expressed as the expected percentage of stillbirths**
**Direct**** SB measures the effect of the calf itself**
**Maternal**** SB measures the effect of a particular cow (daughter)**
**A base of ****8%**** was used for both traits:**
**Direct:**** bulls born 1996****–****2000**
**Maternal:**** bulls born 1991****–****1995**

## Phenotypic Trend for Stillbirths

## Genetic Trend for Stillbirths

## Distribution of PTA

## Distribution of Reliabilities

## Dystocia and Stillbirth

**Meyer et al. (2001) make a strong argument for the inclusion of dystocia in models for SB**
**Difficulty of interpretation**** - formidable educational challenge**
**Interbull trait harmonization**** - none of the March 2006 test run participants included dystocia in their models**
**Changes in sire and MGS solutions on the underlying scale between models were small**

## Evaluation Conclusions

**Reliabilities for SB averaged ****45%**** versus ****60%**** for CE**
**Phenotypic and genetic trends from 1980 to 2005 were both small**
**An industry-wide effort is underway to improve recording of calf livability**

## Index Data

**7 million SB records were available for Holstein cows calving since 1980**
**Calvings with unknown MGS were eliminated for VCE**
**Records with sire and MGS among the 2,600 most-frequently appearing bulls were selected**

## Data (cont’d)

**Herds needed ≥10 calving records with SB scores of 2 or 3 in the database to be included**
**Herd-years were required to include ≥20 records and only single births were used**
**Inclusion of all records for a cow was not guaranteed**
**The final dataset included ****2,083,979**** calving records from ****5,765**** herds and ****33,304**** herd-years**

## Sampling

**Six datasets of ****~250,000**** records each were created by randomly sampling herd codes without replacement**
**Datasets ranged from ****239,192**** to ****286,794**** observations, and all averaged ****7%**** stillbirths**
**A common pedigree file was used to facilitate comparisons between sire and MGS solutions**

## Bayesian (co)variance components estimates

|  | Var(Sire) |  |  | Var(MGS) |  |  | Cov(S-MGS) |  |
| --- | --- | --- | --- | --- | --- | --- | --- | --- |
| Sample | Mean | SD |  | Mean | SD |  | Mean | SD |
| 1 | 0.010 | 0.002 |  | 0.018 | 0.002 |  | 0.004 | 0.001 |
| 2 | 0.007 | 0.002 |  | 0.017 | 0.002 |  | 0.005 | 0.001 |
| 3 | 0.009 | 0.001 |  | 0.019 | 0.002 |  | 0.005 | 0.001 |
| 4 | 0.008 | 0.001 |  | 0.019 | 0.002 |  | 0.004 | 0.001 |
| 5 | 0.008 | 0.001 |  | 0.018 | 0.002 |  | 0.002 | 0.001 |
| 6 | 0.009 | 0.002 |  | 0.017 | 0.002 |  | 0.004 | 0.001 |
| Mean | 0.009 | 0.002 |  | 0.018 | 0.002 |  | 0.004 | 0.001 |

## Heritabilities

**Calving Ease (Direct)****	****	****8.6%**
**Calving Ease (MGS)****	****	****3.6%**
**Stillbirth (Direct)****	****	****	****3.0%**
**Stillbirth (MGS)****	****	****	****6.5%**

## Genetic Correlations Among SB and CE

| Trait |  | CE |  |  | SB |  |
| --- | --- | --- | --- | --- | --- | --- |
|  |  | Direct | Maternal |  | Direct | Maternal |
| CE | Direct | 1.00 | 0.46 |  | 0.67 | 0.25 |
|  | Maternal |  | 1.00 |  | 0.29 | 0.63 |
| SB | Direct |  |  |  | 1.00 | 0.28 |
|  | Maternal |  |  |  |  | 1.00 |

## Economic Assumptions

**Newborn calf value**
**Expenses per difficult birth (CE ≥4) **

| $450 for females |
| --- |
| $150 for males |

| $75 labor and veterinary |
| --- |
| $100 reduced milk yield |
| $75 reduced fertility and longevity |
| 1.5% chance of cow death ($1800) |

## Calving Ability Index

**CA$ has a genetic correlation of ****0.85**** with the combined direct and maternal CE values in 2003 NM$ and ****0.77**** with maternal CE in TPI**
**Calving traits receive ****6%**** of the total emphasis in NM$ (August 2006 revision)**

## Breeds Other Than Holstein

**Brown Swiss**** economic values are   ****−6**** for SCE and ****−8**** for DCE**
**Separate SB evaluations are not available**
**CE values include the correlated response in SB**
**Other breeds**** will be assigned CA$ of ****0**

## Calving Ease Genetic CorrelationsService sire above diagonal, daughter below

| Ctry | CAN | DNK | FRA | ITA | NLD | SWE | USA |
| --- | --- | --- | --- | --- | --- | --- | --- |
| CAN |  | .87 | .81 | .70 | .80 | .86 | .75 |
| DNK | .84 |  | .93 | .77 | .86 | .96 | .90 |
| FRA | .80 | .80 |  | .74 | .84 | .91 | .88 |
| ITA | .58 | .59 | .85 |  | .60 | .70 | .61 |
| NLD | .89 | .81 | .79 | .59 |  | .89 | .79 |
| SWE | .75 | .82 | .89 | .78 | .69 |  | .86 |
| USA | .71 | .78 | .93 | .76 | .77 | .87 |  |

## Stillbirth Genetic CorrelationsService sire above diagonal, daughter below

| Ctry | DNK | FIN | ISR | NLD | SWE | USA |
| --- | --- | --- | --- | --- | --- | --- |
| DNK |  | .85 | .82 | .67 | .92 | .70 |
| FIN | .82 |  | .77 | .64 | .82 | .65 |
| ISR | .67 | .70 |  | .73 | .80 | .66 |
| NLD | .82 | .77 | .60 |  | .65 | .63 |
| SWE | .88 | .92 | .65 | .73 |  | .64 |
| USA | .81 | .87 | .60 | .71 | .87 |  |

## Brown Swiss Calving Ease Service sire correlations above diagonal, daughter below

| Ctry | CHE | DEU | NLD | USA |
| --- | --- | --- | --- | --- |
| CHE |  | .83 | .81 | .68 |
| DEU | .61 |  | .77 | .67 |
| NLD | .89 | .76 |  | .79 |
| USA | .70 | .61 | .76 |  |

## Index Conclusions

**A routine evaluation for stillbirth in US Holsteins was implemented in August 2006**
**Direct and maternal stillbirth were included in NM$ for Holsteins starting in August 2006**
**August 2006 data were included in the September 2006 Interbull test run**
**The US will participate in routine Interbull evaluations beginning in November 2006**

## Recent Calving Ease Research

## Abnormal Herd-Years

**Many herd-years have abnormal distributions of scores**
**Two recent approaches to problem**
**Eliminate HY based on GoF tests**
**Collapse categories when mode > 1**
**Both strategies improve prediction of later evaluations by earlier**

## An Illustration

- Herds with unusual distributions of data affect evaluations of bulls
- Worst case is when large share of records for a bull are in one “bad” herd
- Herd reporting changes over time

## Test Edits - 2 GoF statistics

**Based on multinomial distributions**
**Independent of herd size **

## Percentage of Score by Parity In All (AN) and GoF Excluded (AG) Herds

**0**

**10**

**20**

**30**

**40**

**50**

**60**

**70**

**80**

**90**

**100**

**1**

**2**

**3**

**4**

**5**

**Calving Ease Score**

**Counts by Herd-Parity (%)**

**Parity 1 - AN**

**Parity 2 - AN**

**Parity 1 - AG**

**Parity 2 - AG**

## Collapse Categories

**The mode for CE scores in a herd is expected to be 1, but was higher for nearly ****10%**** of data**
**Data from herd-years with a mode of 4 or 5 (1.2%) were deleted**
**A mode of 3 is assumed to indicate that the scorer normalized the data (middle score of 3 for an 'average' birth)**

## Collapse Categories

**Herds with a mode of 2 or 3:**** scores up to the mode were changed to 1, and scores greater than the mode were decreased accordingly**
**Herd-years with a mode of 3:**** scores 1-3 all become 1, scores of 4 are changed to 2, and scores of 5 are changed to 3**
**Combining categories lowered the portion of difficult calvings and increased the impact of the subsequent goodness-of-fit test**
**Overall, ****6.4%**** of data were excluded**

## Conclusions

**Exclusion of herds with poor distributions improves prediction of future evaluations across birth years **
**Correlations across all data increased from .66 to .68**
**Herds with poor score distributions were  excluded uniformly across herd size**
**Exclusion of herds results in loss of evaluations for some bulls**

## Separate Parity Effects

**First and later parities currently modelled as a single trait**
**cblup90iod**** only accepts one threshold trait**
**Options for bivariate analysis**
**Gibbs sampling (****thrgibbs1****)**
**Linearization (****airemlf90****)**
**RR on parity (****cblup90iod****)**

## Results

**RR on a 0-1 parity effect does not account for heterogeneous variances**
**GS and AIREML solutions were similar**
**GS required more processing time than is desirable for routine national evaluations**
**The impact of the approximation necessary to linearize the scores is not known**
**Implementation of a bivariate analysis is desirable, but challenging**

## Acknowledgments

**Jeff Berger, Iowa State University**
**John Clay, Dairy Records Management Systems**
**Ignacy Misztal and Shogo Tsuruta, University of Georgia**
**National Association of Animal Breeders**