An integrated pig growth model specific to the dietary formulations, genetic quality and environmental conditions of western Canada has been developed. A computer program was designed to simulate growth of pigs between 20 kgs and 100 kgs live weight. A spreadsheet format -Lotus 123 - was used to allow programming steps to be understood by all users, including those who do not possess a high degree of programming skill. A linear programming system was also incorporated through the use of an algorithm - Optimal Solutions. A useful method of avoiding circular errors, through an initial prediction of growth, was developed through the use of a 'Gompertz' style equation which describes growth; B.W. = A exp (-B exp (-k(t))) where B.W. is body weight (kg), A is mature body weight [estimate based on NRC(1988):164 kg], B is a rate constant [4.46], k is a rate constant [range from 0.01 to 0.015] and t is the time in days. A model of nutrient flow was developed with components which include, [1] body composition at the start of growth, [2] energy and amino acid intake, [3] the utilization of ingested amino acids, [4] the upper limit to daily protein retention, [5] The interaction between metabolizable energy and protein as a proportion of the deposition of body lipid and protein, and [6] equations which assist in the prediction of performance factors. A model proof was undertaken through a study of pig performance across 4 diets varying in protein level. Pig performance indicators included; feed intake, feed efficiency, carcass index and carcass yield. A significant correlation (p<0.05) was shown between model predictions of market age and trial results. Pig rearing conditions differ in western Canada, compared to the rest of North America, due to the influence of British breeding companies and the common use of barley as a key ingredient of swine diets. The growth model developed was found to be a good predictor of performance of pigs being grown in western Canada. Feed intake and the genetic potential for protein deposition were found to be the most important predictors of pig performance. / Land and Food Systems, Faculty of / Graduate