ANALYZING PORK CARCASS EVALUATION TECHNOLOGIES IN A SWINE BIOECONOMICMODEL

Inaccurate pork (Sus scrofa) carcass evaluation technologies have the potential to send inaccurate economic signals to producers regarding l eanness. The objective of this study was to estimate the difference in the optimal level of returns to management and operator labor under a lternative assumptions about the carcass evaluation technology employe d and the actual returns based on carcass dissection data. Two genotyp es of barrows and gilts reflecting significant genetic variation were analyzed. The carcass evaluation technologies examined were: an optica l probe (PROBE), electromagnetic scanner (EMSCAN), and a combination o f both technologies (BOTH). A deterministic bioeconomic model of swine growth was formulated to measure the effect of these technologies on pork producer profitability. Relationships between biological variable s for feed efficiency, live weight, lean weight, fat weight, carcass w eight, and backfat depth were estimated as functions of time for two g enotypes of barrows and gilts. Economic variables included production costs and revenues from a component pricing model with separate paymen ts for lean, fat, and byproducts. Error was defined as the optimal ret urn to management and operator labor derived from the bioeconomic opti mization model minus the actual return as determined from carcass diss ection. The range of error was $-5.41 (lean genotype gilts) to $0.23 p er pig (fat genotype barrows) for the PROBE model. For the EMSCAN mode l this range was $-2.63 (lean genotype barrows) to $5.46 (fat genotype barrows) while the BOTH model had a range of $-3.54 (fat genotype gil ts) to $1.54 (fat genotype barrows). The results indicated that the ab solute error (sum of errors across genotype and sex) For each technolo gy was 40% higher for the PROBE model than the EMSCAN or BOTH models. Optimal marketing weights were lowest for the PROBE model and highest for the EMSCAN model.