A bioeconomic simulation model for a hierarchical swine breeding structure

Abstract

A stochastic computer model was developed to simulate individual pigs in a hierarchical breeding system. The bioeconomic model was designed as a tool to facilitate the evaluation of selection, culling, and management strategies for a three-tiered breeding structure. Events such as mating, farrowing, and selection occurred weekly. Variables included number of pigs born alive, survival rate from birth to weaning, average daily gain and backfat at 110 kg, number of pigs weaned, feed per gain, days from weaning to 110 kg, age at puberty, and growth rate and weight of sows and service boars. Also included were probabilities of conception, return to estrus by week, survival, involuntary culling, male infertility, and unacceptable conformation. Variables important for selection were determined by breeding value, individual and maternal heterosis, parity, size of birth litter, sex, age of dam, genetic and environmental relationships between variables, and common litter, permanent, and random environmental effects. Variables derived from selection variables were computed by regression using phenotypic relationships between all variables. Also, a random environmental effect was added to predicted performance. Means and variances of variables differed between genetic lines. Production costs included feed, non-feed operating, fixed, and replacement stock costs. Income included market animals, culls, and replacements sold to lower tiers. Effects of changes in backfat on market value and sow maintenance feed costs were not modeled. An example is given to illustrate model output.

Genetic and economic analyses of sow replacement rates in the commercial tier of a hierarchical swine breeding structure

“…General Approach. Systems of parity culling levels for a 10-yr planning horizon were simulated using the three-tiered stochastic swine life-cycle model described by Faust et al (1992b). Briefly, the model simulated production of market hogs from a three-breed, static crossing scheme and consisted of three distinct nucleus populations (maternal grandam, maternal grandsire, and terminal sire), a multiplier tier producing F1 gilts, and a commercial tier.…”

“…All boars that were not removed for involuntary reasons were culled after 11 wk of service. Involuntary culling for sows was described by Faust et al (1992b) and resulted in an annual rate of approximately 10% (excluding mortality and barrenness rates). Maximum sow parities within each tier were determined by the experimental design with combinations of 1-and 5-parity nucleus and 1-, 5-, and 10-parity multiplier and commercial strategies (Table 1).…”

Genetic improvement of sow longevity and its economic impact on commercial pork production

“…Simulation models have been used to examine the effect of culling rate, replacement gilt cost and other factors on the profitability of commercial swine operations. Faust et al (1992Faust et al ( , 1993a developed simulation models of swine breeding system to evaluated various effects, including culling, on profitability. The simulation models demonstrated that systems with the lowest commercial replacement rates (i.e.…”