
%0 Journal Article
%A O'Rourke, PK 
%A Doogan, VJ 
%A McCosker, TH 
%A Eggington, AR 
%T Prediction of conception rate in extensive beef herds in north-western Australia. 1. Seasonal mating and improved management
%J Australian Journal of Experimental Agriculture
%D 1991/02/01
%V 31
%N 1
%P 1-7
%K 
%R https://doi.org/10.1071/EA9910001
%U https://www.publish.csiro.au/paper/EA9910001 
%X Statistical models for conception rate were developed using data collected at a mid dry season (August-September) muster from a controlled-mated and supplemented herd of 900 Brahman cross cows at Mt Bundey from 1980-84. Average conception rates were 74% for maidens, 25% for first-lactation cows, 51 % for 4-10-year-old lactating cows, 54% for >10-year-old lactating cows and 96% for non-lactating cows. Although year effects dominated, they were partially explained by severity of the dry season and were consistent across levels of the other factors. Pregnant maiden heifers weighed 13 kg more than non-pregnant ones at the end of mating, after allowing for the weight of the fetus and gravid uterus. Conception rate of first-lactation cows was not affected by month of calving, adjusted mid dry season weight or condition score, possibly because of narrow ranges in these factors based on selection. For mature lactating cows the main effects on conception rate were month of calving (+11% for September to -16% for December or later), previous lactation (+6% for having reared a calf), adjusted mid dry season weight (-16% for <300 kg to +9% for >350 kg) and condition score (-17% for backward and store to +16% for good condition). Corresponding effects for aged lactating cows were +14% for September to -19% for December or later calving, +8% for previously rearing a calf, and -24% for backward store and store to +23% for good condition cows. The high conception rates for non-lactating cows corresponded with high liveweights and condition scores. A low cost, practical implementation of these models is based on previous lactation status and condition score in the mid dry season, with pregnancy diagnosis added at the next stage. Reproductive classes could be segregated on this basis for improved management and nutrition and to gain an economic return on capital invested in cattle control. 
