Moisture absorption early postmortem predicts ultimate drip loss in fresh pork.

Water-holding capacity is the ability of meat to hold moisture and is subject to postmortem metabolism. The objective of this study was to characterize the loss of moisture from muscle postmortem and investigate whether these losses are useful in predicting the ultimate drip loss of fresh pork. Cotton-rayon absorptive-based devices were inserted in the longissimus dorsi muscles of pork carcasses (n = 51) postmortem and removed at various intervals for 24h. Greatest moisture absorption was observed at 105 min post exsanguination. Drip loss varied (0.6-15.3%) across carcasses. Individual absorption at 75 min correlated (r = 0.33) with final drip loss. Correlations improved using individual absorption values at 90 min (r = 0.48) and accumulated absorption values at 150 min (r = 0.41). Results show that significant moisture is lost from muscle tissue early postmortem and suggest that capture of this moisture may be useful in predicting final drip loss of fresh meat.

Evaluation of the prediction of alternative measures of pork carcass composition by three optical probes.

The accuracy of 3 optical probes (HGP4 Hennessey Grading Probe, Destron-Feering PG-100 probe, and Giraldo OPTO-Electronic PG-200 probe) to predict the carcass percentage of 5 alternative measures of carcass composition (fat-tissue-free lean, lipid-free soft tissue, lipid-free lean, total fat tissue, and soft tissue lipid) was evaluated on 203 barrows and gilts of 7 genetic populations. The optical probe backfat depths were more closely correlated (P < 0.001, 0.963 to 0.983) than the LM depths (r = 0.695 to 0.734). The optical probe backfat depths were related to lean percentage (r = -0.82 to -0.88), total fat tissue percentage (r = 0.84 to 0.88), and soft tissue lipid percentage (r = 0.86 to 0.87). Optical probe LM depths were weakly related (P < 0.05; r = 0.23 to 0.34) to measures of carcass lean percentage and total fat tissue percentage (r = -0.16 to -0.26). Fat-free lean percentage was predicted with residual SD (RSD) of 3.7% for equations including last-rib midline backfat thickness, 2.4 to 2.7% for equations including optical probe backfat and LM depth, and 2.3% for ribbed carcass measurements. The RSD for the optical probe equations ranged from 2.1 to 2.4% for lipid-free soft tissue percentage and from 2.0 to 2.3% for lipid-free lean percentage. The RSD for the optical probe equations ranged from 2.9 to 3.3% for total fat tissue percentage and 2.5 to 2.8% for soft tissue lipid percentage. Quadratic and cross-product variables of optical probe fat depth, LM depth, and carcass weight were significant (P < 0.05) and reduced the RSD of the equations. Optical probe backfat and LM measurements can be used to predict alternative measures of carcass composition. The predicted relationships in fat-free lean percentage to backfat depth were nearly identical for each optical probe.

Ractopamine treatment biases in the prediction of pork carcass composition.

Carcass and live measurements of 45 barrows were used to evaluate the magnitude of ractopamine (RAC) treatment prediction biases for measures of carcass composition. Barrows (body weight = 69.6 kg) were allotted by weight to three dietary treatments and fed to an average body weight of 114 kg. Treatments were: 1) 16% crude protein, 0.82% lysine control diet (CON); 2) control diet + 20 ppm RAC (RAC16); 3) a phase feeding sequence with 20 ppm RAC (RAC-P) consisting of 18% crude protein (1.08% lysine) during wk 1 and 4, 20% crude protein (1.22% lysine) during wk 2 and 3, 16% crude protein (0.94% lysine) during wk 6, and 16% crude protein (0.82% lysine) during wk 6. The four lean cuts from the right side of the carcasses (n = 15/treatment) were dissected into lean and fat tissue. The other cut soft tissue was collected from the jowl, ribs, and belly. Proximate analyses were completed on these three tissue pools and a sample of fat tissue from the other cut soft tissue. Prediction equations were developed for each of five measures of carcass composition: fat-free lean, lipid-free soft tissue, dissected lean in the four lean cuts, total carcass fat tissue, and soft-tissue lipid mass. Ractopamine treatment biases were found for equations in which midline backfat, ribbed carcass, and live ultrasonic measures were used as single technology sets of measurements. Prediction equations from live or carcass measurements underpredicted the lean mass of the RAC-P pigs and underpredicted the lean mass of the CON pigs. Only 20 to 50% of the true difference in fat-free lean mass or lipid-free soft-tissue mass between the control pigs and pigs fed RAC was predicted from equations including standard carcass measurements. The soft-tissue lipid and total carcass fat mass of RAC-P pigs was overpredicted from the carcass and live ultrasound measurements. Prediction equations including standard carcass measurements with dissected ham lean alone or with dissected loin lean reduced the residual standard deviation and magnitude of biases for the three measures of carcass leanmass. Prediction equations including the percentage of lipid of the other cut soft tissue improved residual standard deviation and reduced the magnitude of biases for total carcass fat mass and soft-tissue lipid. Prediction equations for easily obtained carcass or live ultrasound measures will only partially predict the true effect of RAC to increase carcass leanness. Accurate prediction of the carcass composition of RAC-fed pigs requires some partial dissection, chemical analysis, or alternative technologies.

Early postmortem electrical stimulation simulates PSE pork development.

Carcasses from 64 gilts were subjected to electrical stimulation (ES) at 3, 15, 25, 35, 45, and 55 min postmortem or were untreated (NS). Temperature and pH of longissimus muscles were recorded at 1, 7, 14, 20, 30, 40, 50, and 60 min, and 24 h postmortem. Muscle samples were collected at 1, 30 and 60 min, and 24 h for determining glycolytic metabolite concentrations. ES at 3, 15, and 25 min resulted in lower (P<0.05) muscle pH, but stimulation after 25 min had no effect on muscle pH. Likewise, ES prior to 25 min resulted in greater (P<0.05) muscle temperatures. Muscle lactate concentrations were greater (P<0.05) in carcasses stimulated before 45 min postmortem. Glucose 6-phosphate concentration decreased (P<0.05) during the first hr postmortem and increased (P<0.05) thereafter. ES of carcasses at 45 and 55 min resulted in higher (P<0.05) concentrations of muscle glucose 6-phosphate at 24 h compared with NS and early-stimulated carcasses. Muscle glycogen concentrations at 30 min in carcasses stimulated at 3, 15 and 25 min were lower (P<0.05) than NS carcasses. Carcasses stimulated at 3 and 15 min exhibited lower (P<0.05) concentrations of muscle glycogen at 60 min than NS carcasses. Carcasses stimulated at 3 and 15 min postmortem exhibited lower (P<0.05) color and firmness scores, while ES at 3 and 25 min postmortem resulted in lower (P<0.05) water holding capacity. ES had no significant effect on CIE L(∗), a(∗), b(∗), or 24 h muscle pH. These data show that ES of pork carcasses during the first 25 min postmortem creates PSE-like quality characteristics and suggest that ES is a potential model for studying pork quality development.

Evaluation of alternative measures of pork carcass composition.

Carcass and live measurements of 203 pigs representing seven genetic populations and four target live weights (100, 114, 128, and 152 kg) were used to evaluate alternative measures of carcass composition. Measures of carcass lean (fat tissue-free lean, FFLM; lipid-free soft tissue, LFSTIS; and dissected lean in the four lean cuts, DL), fat (total carcass fat tissue, TOFAT), and lipid mass (soft tissue lipid, STLIP) were evaluated. Overall, LFSTIS was 22.8% greater than FFLM (47.8 vs 38.9 kg) and TOFAT was 30% greater than STLIP (38.5 vs 29.6 kg). The allometric growth coefficients relative to carcass weight were different for the measures: b = 0.776, 0.828, 0.794, 1.37, and 1.49 for FFLM, LFSTIS, DL, TOFAT, and STLIP, respectively. At 90 kg carcass weight, the predicted growth of FFLM, LFSTIS, TOFAT, and STLIP was 0.314, 0.420, 0.553, and 0.446 kg/kg increase in carcass weight. The difference between FFLM and LFSTIS, representing nonlipid components of the carcass fat tissue, was greater for barrows than for gilts (9.2 vs 8.6 kg). Lipid-free soft tissue mass was predicted more accurately from carcass or live animal measurements than FFLM with smaller relative RSD (4.6 vs 6.5% of their mean values). The alternative measures of carcass composition were evaluated as predictors of empty body protein (MTPRO) and lipid (MTLIP) mass. Empty body protein was predicted with similar accuracy (R2 = 0.74 to 0.81) from either DL, FFLM, LFSTIS, or ribbed carcass measurements. Empty body lipid was predicted more accurately from TOFAT (R2 = 0.92) or STLIP (R2 = 0.93) than ribbed carcass measurements (R2 = 0.88). Although the alternative measures of lean mass (LFSTIS vs FFLM) and lipid mass (TOFAT vs STLIP) were highly related to each other (r = 0.93 to 0.98), they had different relative growth rates (allometric coefficients) and thus cannot be predicted as linear functions of the similar alternative variable without significant weight group biases. From the 100- to 152-kg target weight groups, gilts gained 12.9% greater FFLM and 12.1% greater MTPRO but only 4.4% greater LFSTIS than barrows. Fat-free lean mass is more precise as a measure of muscle growth and as a predictor of lysine requirements. Lipid-free soft tissue can be obtained more quickly and predicted more accurately from carcass or live animal measurements.

Junction adhesion molecule is a receptor for reovirus.

Virus attachment to cells plays an essential role in viral tropism and disease. Reovirus serotypes 1 and 3 differ in the capacity to target distinct cell types in the murine nervous system and in the efficiency to induce apoptosis. The binding of viral attachment protein sigma1 to unidentified receptors controls these phenotypes. We used expression cloning to identify junction adhesion molecule (JAM), an integral tight junction protein, as a reovirus receptor. JAM binds directly to sigma1 and permits reovirus infection of nonpermissive cells. Ligation of JAM is required for reovirus-induced activation of NF-kappaB and apoptosis. Thus, reovirus interaction with cell-surface receptors is a critical determinant of both cell-type specific tropism and virus-induced intracellular signaling events that culminate in cell death.

Utilization of sialic acid as a coreceptor enhances reovirus attachment by multistep adhesion strengthening.

Many serotype 3 reoviruses bind to two different host cell molecules, sialic acid and an unidentified protein, using discrete receptor-binding domains in viral attachment protein, final sigma1. To determine mechanisms by which these receptor-binding events cooperate to mediate cell attachment, we generated isogenic reovirus strains that differ in the capacity to bind sialic acid. Strain SA+, but not SA-, bound specifically to sialic acid on a biosensor chip with nanomolar avidity. SA+ displayed 5-fold higher avidity for HeLa cells when compared with SA-, although both strains recognized the same proteinaceous receptor. Increased avidity of SA+ binding was mediated by increased k(on). Neuraminidase treatment to remove cell-surface sialic acid decreased the k(on) of SA+ to that of SA-. Increased k(on) of SA+ enhanced an infectious attachment process, since SA+ was 50-100-fold more efficient than SA- at infecting HeLa cells in a kinetic fluorescent focus assay. Sialic acid binding was operant early during SA+ attachment, since the capacity of soluble sialyllactose to inhibit infection decreased rapidly during the first 20 min of adsorption. These results indicate that reovirus binding to sialic acid enhances virus infection through adhesion of virus to the cell surface where access to a proteinaceous receptor is thermodynamically favored.

Assessment of fresh pork color with color machine vision.

Currently, fresh pork color is visually evaluated using either the Japanese Pork Color Standards (JPCS) or the National Pork Producers Council Pork Quality Standards (NPPC) as a reference. Although useful, visual evaluation of meat color can vary with evaluator and may be quite expensive. In this study, three separate studies were used to compare the ability of color machine vision (CMV) and untrained panelists to evaluate pork color. Panels visually evaluated over 200 pork loin chops using either the JPCS or NPPC reference standards. Results from each panel were used to evaluate the ability of the CMV to sort pork loin chops based on the same criteria. Representative samples, typical of each color class, were used to train neural-network-based image processing software. After training, the CMV system was used to evaluate quality classes of pork samples based on color distribution. Classification by CMV was compared with the average panel score, rounded to the nearest integer. Training the CMV system using images of actual meat samples resulted in a stronger correlation to panel scores than training with either set of artificial color standards. Agreement between the CMV system and the panels was as high as 90%. Agreement between individual panelists and the integer panel average (52 to 85%) was less than that observed for CMV classification. Finally, the on-line performance of CMV using a laboratory conveyor system was simulated by repeatedly classifying 37 samples at a speed of 1 sample per second. Collectively, these results demonstrate that CMV is a rapid and repeatable means of evaluating pork color.

Development of technology for the early post mortem prediction of water holding capacity and drip loss in fresh pork.

Two different technologies were tested on the slaughterline for their ability to predict drip loss at 24 h, namely near infrared reflectance (NIR) and impedance measurements using a tetra polar measuring geometry at a frequency of 1000 Hz. The results demonstrate that NIR measurements (900-1800 nm) acquired during a 6 min period starting only 30 min post exsanguination through a fibre optic probe in combination with multivariate data analysis can be used for predicting drip loss 24 h after slaughter. A correlation higher than 0.8 was observed for a trial on 99 carcasses measured at a commercial slaughterhouse. The tetrapolar impedance measurements did not perform as well as NIR yielding a correlation of 0.5 with 24 h drip loss.

Using current on-line carcass evaluation parameters to estimate boneless and bone-in pork carcass yield as influenced by trim level.

The objective of this study was to develop prediction equations for estimating proportional carcass yield to a variety of external trim levels and bone-in and boneless pork primal cuts. Two hundred pork carcasses were selected from six U.S. pork processing plants and represented USDA carcass grades (25% USDA #1, 36% USDA #2, 25% USDA #3, and 14% USDA #4). Carcasses were measured (prerigor and after a 24 h chill) for fat and muscle depth at the last rib (LR) and between the third and fourth from last rib (TH) with a Hennessy optical grading probe (OGP). Carcasses were shipped to Texas A&M University, where one was randomly assigned for fabrication. Selected sides were fabricated to four lean cuts (ham, loin, Boston butt, and picnic shoulder) then fabricated progressively into bone-in (BI) and boneless (BL) four lean cuts (FLC) trimmed to .64, .32, and 0 cm of s.c. fat, and BL 0 cm trim, seam fat removed, four lean cuts (BLS-OFLC). Total dissected carcass lean was used to calculate the percentage of total carcass lean (PLEAN). Lean tissue subsamples were collected for chemical fat-free analysis and percentage carcass fat-free lean (FFLEAN) was determined. Longissimus muscle area and fat depth also were collected at the 10th and 11th rib interface during fabrication. Regression equations were developed from linear carcass and OGP measurements predicting FLC of each fabrication point. Loin muscle and fat depths from the OPG obtained on warm, prerigor carcasses at the TH interface were more accurate predictors of fabrication end points than warm carcass probe depth obtained at the last rib or either of the chilled carcass probe sites (probed at TH or LR). Fat and loin muscle depth obtained via OGP explained 46.7, 52.6, and 57.1% (residual mean square error [RMSE] = 3.30, 3.19, and 3.04%) of the variation in the percentage of BI-FLC trimmed to .64, .32, and 0 cm of s.c. fat, respectively, and 49.0, 53.9, and 60.7% (RMSE = 2.91, 2.81, and 2.69%) of the variation in the percentage of BL-FLC trimmed to .64, .32, and 0 cm of s.c. fat, respectively. Fat and loin muscle depth from warm carcass OGP probes at the TH interface accounted for 62.4 and 63.5% (RMSE = 3.38 and 3.27%) of the variation in PLEAN and FFLEAN, respectively. These equations provide an opportunity to estimate pork carcass yield for a variety of procurement end point equations using existing on-line techniques.

Analysis of body composition changes of swine during growth and development.

This study was conducted to model the growth of carcass, viscera, and empty body components and component composition of pigs. Quantitative tissue and chemical composition of 319 swine, representative of barrows and gilts from five commercial genetic populations, was determined at eight stages of growth between 25 and 152 kg. After whole body grinding and carcass dissection, proximate analyses were performed to calculate concentrations of protein, lipid, moisture, and ash of carcass, viscera, empty body, carcass lean, and carcass fat. Linear and nonlinear equations were developed to investigate the growth patterns of each component. Nonlinear growth functions accounted for the greatest amount of variation in empty body protein, lipid, moisture, and ash mass. Differences (P < .05) existed between barrows and gilts for nearly all components investigated. Carcass lean and fat tissues significantly increased in lipid percentage and decreased in moisture percentage as live weight increased. There were significant changes in the ratio and composition of the tissues of barrows and gilts during growth. Nonlinear models fitted the data better than allometric equations for nearly all of the components investigated.

Biases associated with genotype and sex in prediction of fat-free lean mass and carcass value in hogs.

Carcass and live measurements of 165 market hogs that represented seven genotypes were used to investigate genotype and sex biases associated with the prediction of fat-free lean mass (FFLM) and carcass value. Carcass value was determined as the sum of the product of weight of individual cuts and their average unit prices adjusted for slaughter and processing costs. Independent variables used in the prediction equations included carcass measurements, such as optical probe, midline ruler, ribbed carcass measurements, and electromagnetic scanning (EMSCAN), and live animal ultrasonic scanning. The effect of including subpopulation mean values of independent variables in the prediction equations for FFLM and carcass value was also investigated. Genotype and sex biases were found in equations in which midline backfat, ribbed carcass, EMSCAN, and live ultrasonic scanning were used as single technology sets of measurements. The prediction equations generally undervalued genotypes with above-average carcass value. Biases were reduced when measurements of combined technologies and mean adjusted variables were used. The FFLM and carcass value of gilts were underestimated, and they were overestimated of barrows. Equations that combined OP and EMSCAN technologies were the most accurate and least biased for both FFLM and carcass value. Equations that included carcass weight and midline last-rib backfat thickness measurements were the least accurate and most biased. Genotype and sex biases must be considered when predicting FFLM and carcass value.

Pork carcass composition derived from a neural network model of electromagnetic scans.

We used an advanced computer logic system (NETS 3.0) to decipher electromagnetic (EM) scans in lieu of traditional linear regression for estimation of pork carcass composition. Fifty EM scans of pork carcasses were obtained on-line (prerigor) at a swine slaughter facility. Right sides were cut into wholesale parts and dissected into fat, lean, and bone to obtain total dissected carcass and primal cut lean. In this study, the input layer consisted of 81 nodes (80-point EM scan curve and warm carcass weight), one hidden layer of 42 nodes, and an output layer consisting of one node, which were run separately for outputs of ham, loin, or shoulder lean. The hidden layer connected to the output of total lean contained 50 nodes. Thirty-five scans were used for training of the network. The new network was then tested with 15 previously unseen input/output pairs. Separate neural networks were developed for the estimation of dissected total carcass, ham, loin, and shoulder lean. The NETS configuration improved on linear regression equations for estimation of total carcass lean by .31 kg, ham lean by .284 kg, and shoulder lean by .148 kg. Our results show that advanced computer logic systems have the capacity to improve upon traditional linear regression equations for prediction of pork carcass composition.

Effect of halothane genotype on porcine meat quality and myoglobin autoxidation.

The objective of this study was to determine effects of light (40-80 kg) or heavy (100-130 kg) slaughter weight and halothane status (positive, nn; negative, NN; and heterozygous, Nn), on meat quality. Longissimus muscle (LM) pH at 45 min (pH(45)) post-exsanguination was 6.25, 6.03, and 5.84 (different at p < 0.01) for NN, Nn, and nn genotype, respectively. At heavier weights (100-130 kg), genotype correlated (r = -0.71) with LM pH(45), 10th costae LM (TENLM) color score (r = -0.55), TENLM Hunter L(∗)-value (r = 0.47), water holding capacity (r = 0.42) and TENLM subjective firmness-wetness score (r = 0.51). Rate constants for metmyoglobin accumulation and oxymyoglobin autoxidation, indicators for fresh meat color stability, increased (p < 0.05) with decreasing pH. Color stability for NN muscle was more stable than nn muscle (p < 0.05). Electrofocusing of myoblobin revealed two bands (MW 17.10(3)) at pI 6.1 and 6.5 across genotypes. Because differences were not observed across genotypes, an observed increase (p < 0.05) in 24 hr myoglobin autoxidation rate constant (associated with increased expression of the HAL gene) are presumed dependent upon post-mortem muscle changes. These data show that changes in halothane status affect fresh pork quality and that lowered meat quality results in further color destruction due to altered chemical reactions involving myoglobin oxidation.

Evaluation of electronic technology to assess lamb carcass composition.

Accurate price signals are essential for producers of American lamb to ensure production of uniformly lean animals. Development of carcass merit-pricing systems will require the use of objective technology for assessing carcass composition or lean distribution. The objective of this study was to evaluate electronic technologies for accurate determination of lamb carcass composition. Lambs (n = 106) were selected as a representation of U.S. market lambs that transcended geographic location, sex, breed, carcass weight, yield grade, and production system. The independent variables used to predict lamb composition varied with the technology. The electronic technologies tested included realtime ultrasound, optical reflectance probe, bioelectrical impedance analysis, and electromagnetic scanning (TOBEC). All technologies, except realtime ultrasound, were tested on warm (prerigor) carcasses and repeated after a 24-h chill. Longitudinal ultrasonic scans of fat and muscle tissue depth and grading probe fat depths were marginal predictors of proportional carcass yield. The TOBEC measurements often accounted for more variability associated with kilograms of dissected lean and percentage of carcass lean than did carcass weight. Equations from TOBEC measurements were the most accurate predictors of weight and percentage of dissected and fat-free lean. Bioelectrical impedance measurements of resistance and reactance combined with carcass weight were also good predictors of carcass composition. Prediction of carcass lean distribution by measures of TOBEC were the most accurate for prediction of leg lean. The implications of usefulness of these technologies will depend on the commitment of the U. S. sheep industry in development of a lamb price discovery system based on carcass composition.

Assessment of lamb carcass composition from live animal measurement of bioelectrical impedance or ultrasonic tissue depths.

Market weight lambs, average weight 52.5 kg (+/-6.1), were used to evaluate nontraditional live animal measurements as predictors of carcass composition. The sample population (n = 106) represented U.S. market lambs and transcended geographic location, breed, carcass weight, yield grade, and production system. Realtime ultrasonic (RU) measurements and bioelectrical impedance analysis (BIA) were used for development and evaluation of prediction equations for % boneless, closely trimmed primal cuts (BCTPC), weight or % of dissected lean tissue (TDL), and chemically derived weight or % fat-free lean (FFL). Longitudinal ultrasonic images were obtained parallel to the longissimus thoracis et lumborum (LTL), positioning the last costae in the center of the transducer head. Images were saved and fat and LTL depths were derived from printed images of the ultrasonic scans. Bioelectrical impedance analysis was administered via a four-terminal impedance plethysmograph operating at 800 microA at 50 kHz. Impedance measurements of whole-body resistance and reactance were recorded. Prediction equations including common linear measurements of live weight, heart girth, hindsaddle length, and shoulder height were also evaluated. All measurements were taken just before slaughter. Bioelectrical impedance measurements (as compared to RU and linear measurements) provided equations for %BCTPC, TDL, %TDL, FFL and %FFL with the highest R2 and lowest root mean square error. Even though BIA provided the best equations of the three methodologies tested, prediction of proportional yield (%BCTPC, %TDL, and %FFL) was marginal (R2 = .296, .551, and .551, respectively). Equations combining BIA, RU, and linear measurements greatly improved equations for prediction of proportional lean yield.

Electrical measurement for detecting early postmortem changes in porcine muscle.

Use of electrical measurements to detect quality defects in porcine muscle in the early postmortem period was evaluated. Justification for use of a tetrapolar, constant current electrode configuration instead of bipolar electrodes was provided for measurements at low frequencies. Interrelationships among electrical properties, pH values, ATP decline, temperature, time postmortem, and final water-holding capacity (WHC) of porcine muscle were quantified using 25 hogs. Immediately after exsanguination, a section of the left longissimus muscle (LM) was excised to obtain rigor shortening patterns and complex impedance measurements over a 10-h period at 37 degrees C. Complex impedance measurements were taken using a tetrapolar electrode configuration at 1 kHz and .156 mA. At 15, 45, and 90 min postmortem, pH, ATP/IMP absorbance (R), and conductivity measured by the Tecpro Pork Quality Meter (PQM) were measured on the right side LM. At 24 h postmortem, WHC, pH, R, PQM, Hunter Color Lab values, and subjective quality scores were evaluated on the left LM. The WHC measurements were used to group carcasses into normal (n = 17) and abnormal (n = 8) categories. Mean pH and R at 45 and 90 min were different (P < .05) but pH at 24 h was not different between the normal and abnormal groups. Onset and completion of rigor were more rapid in carcasses with low WHC (P < .05). The PQM values were greater (P < .05) in the abnormal group at 90 min and 24 h postmortem. Excised muscle measurements of relative impedance (Z*) and phase (theta*) showed Z* and theta* increased more rapidly within the first 15 min postmortem (P < .1) for samples with abnormal WHC. However, one PSE carcass showed an immediate rapid decrease in Z* and theta*. Results suggest measurement of rate of change of impedance and phase angle before 90 min postmortem would be a better prediction of ultimate quality than absolute magnitude of impedance.

Alternative pork carcass evaluation techniques: I. Differences in predictions of value.

Dissected and predicted wholesale and lean boneless values for 154 pork carcasses representing seven genotypes with substantial variation in carcass composition and percentage of lean were determined. Dissected carcass value was determined using a component pricing model, and four alternative models were specified to predict that value. The models included measurements from a ruler (RULER) and two carcass evaluation technologies, Hennessy probe (PROBE) and electromagnetic scanner (EMS1). A combination of the PROBE and EMS1 models (EMS2) was also used. For wholesale value, R2 were .40, .70, .59, and .74, and the RSD were 8.18, 5.77, 6.76, and 5.38 ($/100 kg of carcass value) for RULER, PROBE, EMS1, and EMS2, respectively. For lean boneless value, the R2 were .41, .73, .59, and .74, and the RSD were 8.34, 5.67, 6.99, and 5.51 ($/100 kg of carcass value) for RULER, PROBE, EMS1, and EMS2, respectively. The results indicate that a combination of probe and electromagnetic scanner measurements provided the best fit to dissected value.

Alternative pork carcass evaluation techniques: II. Statistical analysis of error attributable to sex, genotype, and weight.

Carcasses of 154 hogs representing seven genotypes with substantial variation in carcass composition and percentage of lean were completely dissected and analyzed. Measurements from a ruler, Hennessy probe, and electromagnetic scanner were each used to predict wholesale and lean boneless carcass value. Error, defined as dissected value minus predicted value, due to the omission of sex, genotype, weight, and their interactions was estimated for each model. The errors were significantly different from zero for the models using ruler and electromagnetic scanning measurements separately (P < .01). Errors due to sex, genotype, weight, and their interactions were greatest for the less lean barrows. A combination of probe and electromagnetic scanner measurements resulted in the least error. The value of barrows with low percentage of lean was consistently overpredicted, whereas the value of leaner gilts was underpredicted for the models using ruler and electromagnetic scanning separately (P < .001).