1. Enhancing Quality Of Dystocia Data By Integration Into A National Dairy Cattle Production Database C. P. Van Tassell 1,2 and G. R. Wiggans 1 Animal Improvement Programs Laboratory 1 and Gene Evaluation and Mapping Laboratory 2 Agricultural Research Service, United States Department of Agriculture Beltsville, MD 20705-2350, USA World Congress on Genetics Applied to Livestock Production Le Corum, Montpellier – France – August 19-23 2002 7 th August 20, Session 20: “Prediction of Breeding Values” No. 20-17 INTRODUCTION  1999 - AIPL first calculated national genetic evaluations for calving ease (CE) (dystocia).  The addition of maternal effects improves evaluations by addressing antagonism between direct and maternal genetic effects on dystocia.  Only 58% of the records submitted to AIPL include maternal grandsire (MGS) identification (ID).  Integrating the CE database with the production database was expected to improve data editing. MATERIALS and METHODS  Master file of dystocia data obtained by AIPL in 1999 is updated biannually with DHIA and AI cooperators’ data.  CE database includes two primary tables: CE records. Pedigree information supplemental to the production database.  Dystocia records are compared to the production database.  In the case of ambiguous or unknown dam ID a negative key is assigned to the dam. Allows retention of data. Preserves MGS ID.  Duplicate records were identified. Records with the same positive dam key and calving  6mo. Records with the same negative dam key and non-zero dam ID, in the same herd, and calving  6mo. Records with no dam ID, in the same herd, with the same calving date.  Editing of CE data is improved by accessing information from existing databases.  Rate of MGS ID increased via existing pedigree data.  Database supports complex queries and on-line access. RESULTS and DISCUSSION CE Database Source Data Input11,063,139 Updates373,318 Duplicates132,160 Rejects79,371 Accepted10,478,290 Accepted Records Non-Holstein62,390 Born <198089,058 Multiple birth52,996 Bull >15yr old78,749 Extracted data10,195,097 Distribution of CE scores Source Data Extracted Data CE Score Percent 1 – No Problem 76.076.3 2 – Slight Problem 10.110.5 3 – Needed Assistance 9.08.8 4 – Considerable Force 2.9 5 – Extreme Difficulty 1.5 Percent Distribution of CE Scores by Parity for Extracted Data  Rate of MGS ID increased from 58% to 73%.  Nearly 70% of the accepted dams were matched with the production database and 99% of these records included MGS ID.  Of dams with a negative key, only 13% included MGS ID.  Variation in the distribution of CE Score within herd was considerable.  The extraction process produce no appreciable change in the distribution of CE scores.  Percentage of male calves was 51.5 in both the accepted source data and the database extract.  The distribution of records across parity was similar in the accepted source data and the database extract.  First calvings were significantly more difficult, but little difference was seen between later parities. CONCLUSIONS Parity 1 st 2 nd ≥3 rd Accepted data26.129.344.6 Extracted data25.629.445.2