Iowa State University Capstones, Theses and Retrospective Theses and Dissertations Dissertations 1987 Genetics of racing performance in the American Quarter Horse Samuel T. Buttram Iowa State University Follow this and additional works at: https://lib.dr.iastate.edu/rtd Part of the Biostatistics Commons Recommended Citation Buttram, Samuel T., "Genetics of racing performance in the American Quarter Horse " (1987). Retrospective Theses and Dissertations. 11670. https://lib.dr.iastate.edu/rtd/11670 This Dissertation is brought to you for free and open access by the Iowa State University Capstones, Theses and Dissertations at Iowa State University Digital Repository. It has been accepted for inclusion in Retrospective Theses and Dissertations by an authorized administrator of Iowa State University Digital Repository. For more information, please contact [email protected]. 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For the Graduate College Iowa State University Ames, Iowa 1987 il TABLE OF CONTENTS Page INTRODUCTION 1 SECTION I. DESCRIPTION OF THE DATA 3 Abstract 3 Introduction 4 Materials and Methods 5 Results and Discussion 7 References 27 SECTION II. ADJUSTMENT FACTORS AND CONTEMPORARY GROUPS 28 Abstract 28 Introduction 29 Materials and Methods 30 Data 3 0 Adjustment factors 31 Contemporary group effects 32 Results and Discussion 33 Data 33 Adjustment factors 35 Contemporary group effects 45 References 48 ixi SECTION III. VARIANCE COMPONENT ESTIMATION 50 Abstract 50 Introduction 51 Materials and Methods 53 Data 53 Model 53 Estimation procedures 55 Computational aspects 58 Heritability and repeatability 59 Results and Discussion 61 References 73 SUMMARY 77 REFERENCES 79 ACKNOWLEDGEMENTS 83 APPENDIX A. TALBES AND FIGURES 84 APPENDIX B. COMPUTER PROGRAM TO EDIT DATA, ASSIGN EQUATION NUMBERS AND SORT RECORDS 109 APPENDIX C. PL/1 PROGRAM TO ADJUST RACING TIMES FOR SEX AND AGE 113 APPENDIX D. PL/1 PROGRAM TO ABSORB CONTEMPORARY GROUP EQUATIONS INTO SIRE AND HORSE EQUATIONS 116 APPENDIX E. FORTRAN PROGRAM TO ESTIMATE VARIANCE COMPONENTS USING IHSM 122 APPENDIX F. FROTRAN PROGRAM TO ESTIMATE VARIANCE COMPONENTS USING THM 127 iv LIST OF TABLES Page Table 1. Distributional properties of racing time by distance 8 Table 2. Frequency distributions and means of horses grouped by number of races run and distance 14 Table 3. Frequency distributions and progeny means of sires grouped by number of progeny records and distance 16 Table 4. Summary of racing time by age and distance 21 Table 5. Summary of racing time by sex and distance 22 Table 1. Summary of racing times used to estimate fixed effects by distance 34 Table 2. Means used for calculating sex adjustment factors 36 Table 3. Additive and multiplicative sex adjustment factors by distance 37 Table 4. Additive age adjustments by sex and distance 42 Table 5. Regression coefficients for adjusting racing times for differences in handicap weight by sex and distance 44 Table 6. Percentages of the total variance accounted for by tracks, years, days and individual races by distance 46 Table 1. Summary of data sets used for estimating variance components by distance 64 Table 2. Estimates of heritability for racing performance by data set from three methods 66 Table 3. Estimates of repeatability for racing performance by data set from three methods 67 V Weighted means of heritability and repeatability estimates from the prior method by age and data source 69 Weighted means of heritability and repeatability estimates from the prior method by distance 71 Number of racing records by year and distance from 1971-1986 85 Means for racing time by year and distance from 1971-1986 86 Summary of racing time by month and distance 87 Frequency distributions for number of horses per race by distance 88 Summary of racing times at the five largest tracks for each of five racing distances 89 Frequency distributions for number of tracks per horse by distance 90 Frequency distributions for number of tracks per sire by distance 91 Handicap weight means and standard deviations by distance 92 vi LIST OF FIGURES Page Figure 1. Frequency distribution of racing times from 320 m racing records 11 Figure 2. Relationship between handicap weight and mean racing time from 320 m racing data (data labels are the percentages of the data represented) 19 Figure 3. Relationship between age and mean racing time from 320 m racing records by sex 25 Figure 1. Actual (symbols only) and predicted (regression lines) age effects relative to two-year-olds from 320 m racing records by sex 40 Figure Al. Frequency distribution of racing times from 201 m racing records 93 Figure A2. Frequency distribution of racing times from 366 m racing records 94 Figure A3. Frequency distribution of racing times from 402 m racing records 95 Figure A4. Frequency distribution of racing times from 796 m racing records 96 Figure A5. Relationship between handicap weight and mean racing time from 201 m racing data (data labels are the percentages of the data represented) 97 Figure A6. Relationship between handicap weight and mean racing time from 366 m racing data (data labels are the percentages of the data represented) 98 Figure A7. Relationship between handicap weight and mean racing time from 402 m racing data (data labels are the percentages of the data represented) 99 vii Figure A8. Relationship between handicap weight and mean racing time from 796 m racing data (data leQaels are the percentages of the data represented) 100 Figure A9. Relationship between age and mean racing time from 201 m racing records by sex 101 Figure AlO. Relationship between age and mean racing time from 366 m racing records by sex 102 Figure All. Relationship between age and mean racing time from 402 m racing records by sex 103 Figure A12. Relationship between age and mean racing time from 796 m racing records by sex 104 Figure A13. Actual (symbols only) and predicted (regression lines) age. effects relative to two-year-olds from 201 m racing records by sex 105 Figure A14. Actual (symbols only) and predicted (regression lines) age effects relative to two-year-olds from 366 m racing records by sex 106 Figure A15. Actual (symbols only) and predicted (regression lines) age effects relative to two-year-olds from 402 m racing records by sex 107 Figure A16. Actual (symbols only) and predicted (regression lines) age effects relative to three-year-olds from 796 m racing records by sex 108 1 INTRODUCTION Quarter Horse racing began in the United States as early as 1674 in Virginia (Essary, 1983) and became popular because the short sprint races could be run down village streets. Quarter Horse races are still characterized as short races run at top speed, usually on a straight track, but today Quarter Horse racing is an industry. More than 100 race tracks that conduct Quarter Horse races are located throughout North America. The American Quarter Horse Association maintains individual racing records for all horses that race in officially sanctioned races at these tracks. These records have been maintained since 1940 and provide an extensive data base from which breeders may receive information on the performance of individual horses.