# Presentation: 398076

## Prediction of Service Sire Fertility 

**M.T. Kuhn****1*****, J.L. Hutchison****1****, and J.S. Clay****2**
**1****Animal Improvement Programs Laboratory**
** ****Agriculture Research Service, USDA, Beltsville, MD**
**2****Dairy Records Management Systems, Raleigh, NC.**

## Introduction

**Currently, two predictions of service sire (****SSR****) fertility are being done**
**ERCR by DRMS**
**ATA Bull Fertility Summary**
**Request for AIPL to conduct a **_**national**_** evaluation for SSR fertility**

## Introduction 

**ERCR**
**Began in 1986**
**Published annually in Hoard’s Dairyman**
**Currently includes data from**
**-**** DRMS,  Ag Source,  MN DHIA**
**	****	****-**** About 64% of US**
**ATA **
** ****Began in 2003**
** ****Somewhat less publicized than ERCR**
** ****Primarily western herds**

## ERCR

**Trait**
**Non-Return at 70 days (NR70)**
**	****	****=> Only first service used**
**Linear animal model**
** ****Factors**
**	****	****HYM****	****    Milk    Parity    DIM    SSR    A****cow**** **
**	****	****PE****cow****    ****SSR_age    SSRxHerd**
** ****Var(SSR) = I********2****ssr****	****	****Var(A****cow****) = A********a****2**** **

## ATA Bull Fertility Summary

**Trait**
**Conception (0, 1) on up to first 5 services**
**Threshold model**
**Factors**
**	****	****SSR       Cow    Herd-Yr-Mo-Tech  **
**	****	****Herd-P-Milk    Herd-DIM    Herd-SSR_Age**
** ****Var(SSR) = I********2****ssr****	****	****Var(Cow) = I********2****cow**

## Overall Objective

**Develop national (phenotypic) evaluation for **
**	****service sire fertility**
** ****Data collection**
** ****Trait definition**
** ****Model development**
** ****Appropriate edits for field data**

## Alternatives to be Investigated

**1) ERCR**
**2) ATA Bull Fertility Summary**
**3) Alternative model(s) using all services**
**Linear model**
**Threshold model**
**Linear model using predicted value for  **
**	****breedings with no pregnancy confirmation**

## Immediate Objectives

**1) Compare models**
** ****ERCR**
** ****An alternative linear model  (****AIPL_LM****)**
**2) Compare trait definitions for AIPL_LM**
** ****All services**
** ****First service only (NR70)**

## AIPL_LM

**	****	****	****    ****Factors Included****	****	****	**
**	****	****	****HYS****	****	****	****     A****ssr**
**	****	****	****ST-MO****	****	****     PE****ssr**
**	****	****	****Parity****	****	****     Stud**
**	****	****	****Cow****	****	****	****     EFI****ssr****	**
**	****	****	****Milk****	****	****	****     F****ssr**
**	****	****	****DIM****	****	****	****     SSR_age**
**	****	****	****Cow_Age**
**          ****Var(Cow) = I********2****cow****	**
**          ****Var(A****ssr****) = A********2****a****	****	****Var(PE****ssr****) = I********2****PE**

**Cow**
**Effects**

**Env’l**
**Effects**

**SSR**
**Effects**

## Predictor for AIPL_LM

**CR  =****	****A****ssr****   +   PE****ssr****  +   Stud   +  **
**	****	****  ****	****ß****1*****EFI   +   ß****2*****F****ssr****   ****	****+  **
**	****	****  ****	****ß****3*****SSR_age**

## Data

**Breeding records from 4 DRPCs**
**Years available: 1995-1999**
**Date of breeding, service sire, service number **
**    ****recorded for each service on each cow-lactation**
**No pregnancy check information available**
** ****Last service on file, assumed successful**
**1997 ERCRs supplied by DRMS**
**	****	**

## Methods

**AIPL_LM predictions computed, for each bull, using records from 1995 to 1997**
**	****	****	****=**** CR****AIPL-1****    ****for first service only**
**	****	****	****= ****CR****AIPL-All****  ****for all services**
**Each bull’s conception rate in **_**1998**_**, adjusted for herd effects, was calculated **
**	****	****	****= ****CR****98**

## Methods

**Criterion for comparison of predictors was correlation with CR****98**
** ****Cor(ERCR,       CR****98****)**
** ****Cor(CR****AIPL-1****,    CR****98****)**
** ****Cor(CR****AIPL-All****,  CR****98****)**

## Results

| Min. No. of Mates | ERCR | CRAIPL-1 | CRAIPL-ALL | No. Bulls |
| --- | --- | --- | --- | --- |
| 100 | 0.44 | 0.51 | 0.62 | 271 |
| 200 | 0.53 | 0.59 | 0.66 | 192 |
| 500 | 0.64 | 0.72 | 0.78 | 128 |
| 1000 | 0.67 | 0.74 | 0.80 | 76 |

- Correlation of Predictors with CR98

## Results

- Correlations Among Predictors

|  | Minimum No. of Mates |  |  |  |
| --- | --- | --- | --- | --- |
|  | 100 | 200 | 500 | 1000 |
| ERCR, CRAIPL-1 | 0.52 | 0.55 | 0.67 | 0.78 |
| ERCR, CRAIPL-ALL | 0.61 | 0.65 | 0.73 | 0.78 |
| CRAIPL-1, CRAIPL-ALL | 0.74 | 0.80 | 0.83 | 0.90 |

## Summary and Conclusions

**Use of multiple services improves accuracy.**
**Model alterations can also improve accuracy.**
**Agreement between alternative models and trait definitions increases with increasing number of mates.**
**Modeling the SSR effect in separate components appears effective.**

## Summary and Conclusions

**Further modeling research**
** ****Additional factors to include**
** ****Modeling effects related to time**
** ****Threshold vs. linear model**
** ****Accounting for uncertainty of **
**    ****pregnancy status**