The efficacy of predicting dystocia in yearling beef heifers: II. Using discriminant analysis.
Discriminant analysis was used to develop equations for predicting dystocia in 2-yr-old, first-calf beef heifers. Data collected on 893 yearling heifers from 34 farms were used to derive four sets of prediction equations (Data Set 1). There was a set of equations for British x British (BRBR) heifers at prebreeding, BRBR heifers at pregnancy check, Continental x British-Continental x Continental (CNBR-CNCN) heifers at prebreeding, and CNBR-CNCN heifers at pregnancy check. A second set of data collected on 3,728 heifers at prebreeding and 875 heifers at pregnancy check were used to test these equations (Data Set 2). Measurements taken prebreeding and at pregnancy check included heifer age, weight, body condition score, pelvic height, pelvic width, pelvic area, hip height, and shoulder height. A precalving estimate of average calf birth weight (AVGBWT) and actual calf birth weight (BWT) were also recorded. When actual calf BWT was used, the prediction equations developed for BRBR heifers at prebreeding and at pregnancy check correctly classified 84.6 and 88.5% of the heifers in Data Set 1, respectively. The prediction equations developed for CNBR-CNCN heifers correctly classified 88.1% of the heifers at prebreeding and 87.9% at pregnancy check. When AVGBWT was used, the accuracy of these four sets of prediction equations ranged from 77.1 to 83.1% for heifers in Data Set 1. In Data Set 2, the prebreeding equations correctly classified 78.5% of BRBR and 79.0% of CNBR-CNCN heifers when AVGBWT was used. Culling by these prebreeding equations would have reduced difficult birth rate in BRBR and CNBR- CNCN heifers by 8.5 and 15.7%, respectively.(ABSTRACT TRUNCATED AT 250 WORDS)
Basarab
J A
JA
Animal Industry Division, Alberta Agriculture, Edmonton, Canada.
Rutter
L M
LM
Day
P A
PA
D000367:Age Factors; D000818:Animals; D001724:Birth Weight; D001835:Body Weight; D002417:Cattle / Q000033:anatomy & histology*; D002418:Cattle Diseases / Q000209:etiology*; D016002:Discriminant Analysis; D004420:Dystocia / Q000209:etiology / Q000662:veterinary*; D005260:Female; D005544:Forecasting; D016018:Least-Squares Analysis; D009752:Nutritional Status; D010388:Pelvis / Q000033:anatomy & histology; D011247:Pregnancy