Agricultural economics: Analyzing pork carcass evaluation technologies in a swine bioeconomic model

Inaccurate pork (Sus scrofa) carcass evaluation technologies have the potential to send inaccurate economic signals to producers regarding leanness. The objective of this study was to estimate the difference in the optimal level of returns to management and operator labor under alternative assumptions about the carcass evaluation technology employed and the actual returns based on carcass dissection data. Two genotypes of barrows and gilts reflecting significant genetic variation were analyzed. The carcass evaluation technologies examined were: an optical probe (PROBE), electromagnetic scanner (EMSCAN), and a combination of 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 variables for feed efficiency, live weight, lean weight, fat weight, carcass weight, and backfat depth were estimated as functions of time for two genotypes of barrows and gilts. Economic variables included production costs and revenues from a com-ponent pricing model with separate payments for lean, fat, and byproducts. Error was defined as the optimal return to management and operator labor derived from the bioeconomic optimization model minus the actual return as determined from carcass dissection. The range of error was $-5.41 (lean genotype gilts) to $0.23 per pig (fat genotype barrows) for the PROBE model. For the EMSCAN model 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 gilts) to $1.54 (fat genotype barrows). The results indicated that the absolute error (sum of errors across genotype and sex) for each technology 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.