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

The association of P2 and lean % estimates from commercial measurement systems with computed tomography determined composition within Australian pork abattoirs

Pork carcasses were obtained from three abattoirs in Australia (n = 345) where technologies enabled collection of post slaughter measures of P2 fat depth (mm) (Hennessy Grading Probe (HGP), AutoFom III, PorkScan Lite) and estimates of carcass lean % (HGP, AutoFom III, PorkScan Plus). Computed tomography (CT) was used to scan carcasses and determine lean and fat %, with the strength of associations with abattoir measurement devices determined. The AutoFom III lean % demonstrated the strongest associations with whole carcass CT lean % (R2 0.63, RMSE 1.73) and fat % (R2 0.68, RMSE 1.80) and with section (fore, loin, belly and hind) CT composition. The association of P2 from AutoFom III was lower in comparison, however remained superior to other commercial devices (PorkScan Lite and HGP). Porkscan Plus lean % demonstrated moderate associations with whole carcass and section CT lean and fat %, with R2 values generally less than half those of the AutoFom III. The HGP demonstrated weakest associations with CT lean and fat % using either lean % or P2 outputs, which is likely related to data being collected from only the P2 measurement site. This is the first experiment to compare the strength of associations between multiple pork abattoir measurement devices and CT lean and fat % in Australia. P2 is the current industry standard for the assessment of lean yield in pork, however demonstrates weaker associations with carcass CT composition than devices capable of capturing multiple measures across the carcass like AutoFom III and PorkScan Plus.

Comparison of an advanced automated ultrasonic scanner (AutoFom III) and a handheld optical probe (Destron PG-100) to determine lean yield in pork carcasses

This study compared the accuracy of two methods for predicting carcass leanness (i.e., predicted lean yield) with fat-free lean yields obtained by manual carcass side cut-out and dissection of lean, fat, and bone components. The two prediction methods evaluated in this study estimated lean yield by measuring fat thickness and muscle depth at one location with an optical grading probe (Destron PG-100) or by scanning the entire carcass with advanced ultrasound technology (AutoFom III). Pork carcasses (166 barrows and 171 gilts; head-on hot carcass weights (HCWs) ranging from 89.4 to 138.0 kg) were selected based on their fit within desired HCW ranges, their fit within specific backfat thickness ranges, and sex (barrow or gilt). Data (n = 337 carcasses) were analyzed using a 3 × 2 factorial arrangement in a randomized complete block design including the fixed effects of the method for predicting lean yield, sex, and their interaction, and random effects of producer (i.e., farm) and slaughter date. Linear regression analysis was then used to examine the accuracy of the Destron PG-100 and AutoFom III data for measuring backfat thickness, muscle depth, and predicted lean yield when compared with fat-free lean yields obtained with manual carcass side cut-outs and dissections. Partial least squares regression analysis was used to predict the measured traits from image parameters generated by the AutoFom III software. There were method differences (P < 0.01) for determining muscle depth and lean yield with no method differences (P = 0.27) for measuring backfat thickness. Both optical probe and ultrasound technologies strongly predicted backfat thickness (R2 ≥ 0.81) and lean yield (R2 ≥ 0.66), but poorly predicted muscle depth (R2 ≤ 0.33). The AutoFom III improved accuracy [R2 = 0.77, root mean square error (RMSE) = 1.82] for the determination of predicted lean yield vs. the Destron PG-100 (R2 = 0.66, RMSE = 2.22). The AutoFom III was also used to predict bone-in/boneless primal weights, which is not possible with the Destron PG-100. The cross-validated prediction accuracy for the prediction of primal weights ranged from 0.71 to 0.84 for bone-in cuts and 0.59 to 0.82 for boneless cut lean yield. The AutoFom III was moderately (r ≤ 0.67) accurate for the determination of predicted lean yield in the picnic, belly, and ham primal cuts and highly (r ≥ 0.68) accurate for the determination of predicted lean yield in the whole shoulder, butt, and loin primal cuts.

An update of the predicted lean yield equation for the Destron PG-100 optical grading probe

The objective was to update the equation used for prediction of pork carcass leanness with the Destron PG-100 optical grading probe. A recent cutout study (completed in 2020-2021) consisting of 337 pork carcasses was used for this research. An updated equation was generated using a calibration dataset (N = 188 carcasses) and prediction precision and prediction accuracy of the new equation was evaluated using a validation dataset (N = 149 carcasses). The updated equation was generated using forward stepwise multiple regression selection techniques in PROC REG of SAS, and the same parameters as the existing equation were used to fit the model. The updated Destron equation [89.16298 - (1.63023 × backfat thickness) - (0.42126 × muscle depth) + (0.01930 × backfat thickness2) + (0.00308 × muscle depth2) + (0.00369 × backfat thickness × muscle depth)] and the existing Destron equation [68.1863 - (0.7833 × backfat thickness) + (0.0689 × muscle depth) + (0.0080 × backfat thickness2) - (0.0002 × muscle depth2) + (0.0006 × backfat thickness × muscle depth)] were similar in their prediction precision for determination of carcass lean yield (LY), with the updated equation R2 = 0.75 and root mean square error (RMSE) = 1.97 and the existing equation R2 = 0.75 and RMSE = 1.94. However, when prediction accuracy was evaluated using the variance explained by predictive models based on cross-validation (VEcv) and Legates and McCabe's efficiency coefficient (E1), the updated equation (VEcv = 67.97%; E1 = 42.41%) was much more accurate compared with the existing equation (VEcv = -117.53%; E1 = -69.24%). Furthermore, when accuracy was evaluated by separating carcasses into 3% carcass LY groupings ranging from less than 50% LY to greater than 62% LY, the existing equation correctly estimated carcass LY 8.1% of the time, while the updated equation correctly estimated carcass LY 47.7% of the time. In an effort to further compare the abilities of the updated equation, comparisons were made with an advanced automated ultrasonic scanner (AutoFom III), which scans the entire carcass. The prediction precision of the AutoFom III was R2 = 0.83 and RMSE = 1.61, while the AutoFom III correctly estimated carcass LY 38.2% of the time and prediction accuracy calculations for the AutoFom III were VEcv = 44.37% and E1 = 21.34%). Overall, refinement of the Destron PG-100 predicted LY equation did not change prediction precision, but substantially improved prediction accuracy.

Replacing dietary antibiotics with 0.20% l-glutamine in swine nursery diets: impact on health and productivity of pigs following weaning and transport1,2,3

Antibiotic use has been limited in U.S. swine production. Therefore, the objective was to determine whether supplementing l-glutamine at cost-effective levels can replace dietary antibiotics to improve piglet welfare and productivity following weaning and transport. Based on previous research, we hypothesized that withholding dietary antibiotics would negatively affect pigs while diet supplementation with 0.20% l-glutamine (GLN) would have similar effects on pig performance and health as antibiotics. Mixed sex piglets (N = 480; 5.62 ± 0.06 kg BW) were weaned (18.4 ± 0.2 d of age) and transported for 12 h in central Indiana, for 2 replicates, during the summer of 2016 and the spring of 2017. Pigs were blocked by BW and allotted to 1 of 3 dietary treatments (n = 10 pens/dietary treatment/replicate [8 pigs/pen]); antibiotics (A; chlortetracycline [441 ppm] + tiamulin [38.6 ppm]), no antibiotics (NA), or GLN fed for 14 d. On days 15 to 34, pigs were provided common antibiotic-free diets in 2 phases. Data were analyzed using PROC MIXED in SAS 9.4. Day 14 BW and days 0 to 14 ADG were greater (P = 0.01) for A (5.6% and 18.5%, respectively) and GLN pigs (3.8% and 11.4%, respectively) compared with NA pigs, with no differences between A and GLN pigs. Days 0 to 14 ADFI increased for A (P < 0.04; 9.3%) compared with NA pigs; however, no differences were detected when comparing GLN with A and NA pigs. Once dietary treatments ceased, no differences (P > 0.05) in productivity between dietary treatments were detected. On day 13, plasma tumor necrosis factor alpha (TNF-α) was reduced (P = 0.02) in A (36.7 ± 6.9 pg/mL) and GLN pigs (40.9 ± 6.9 pg/mL) vs. NA pigs (63.2 ± 6.9 pg/mL). Aggressive behavior tended to be reduced overall (P = 0.09; 26.4%) in GLN compared with A pigs, but no differences were observed between A and GLN vs. NA pigs. Huddling, active, and eating/drinking behaviors were increased overall (P < 0.02; 179%, 37%, and 29%, respectively) in the spring replicate compared with the summer replicate. When hot carcass weight (HCW) was used as a covariate, loin depth and lean percentage were increased (P = 0.01; 4.0% and 1.1%, respectively) during the spring replicate compared with the summer replicate. In conclusion, GLN supplementation improved pig performance and health after weaning and transport similarly to A across replicates; however, the positive effects of A and GLN were diminished when dietary treatments ceased.

The impact of feeding diets of high or low energy concentration on carcass measurements and the weight of primal and subprimal lean cuts

Pigs from four sire lines were allocated to a series of low energy (LE, 3.15 to 3.21 Mcal ME/kg) corn-soybean meal-based diets with 16% wheat midds or high energy diets (HE, 3.41 to 3.45 Mcal ME/kg) with 4.5 to 4.95% choice white grease. All diets contained 6% DDGS. The HE and LE diets of each of the four phases were formulated to have equal lysine:Mcal ME ratios. Barrows (N = 2,178) and gilts (N = 2,274) were fed either high energy (HE) or low energy (LE) diets from 27 kg BW to target BWs of 118, 127, 131.5 and 140.6 kg. Carcass primal and subprimal cut weights were collected. The cut weights and carcass measurements were fitted to allometric functions (Y = A CW(B)) of carcass weight. The significance of diet, sex or sire line with A and B was evaluated by linearizing the equations by log to log transformation. The effect of diet on A and B did not interact with sex or sire line. Thus, the final model was (B)) where Diet = -0.5 for the LE and 0.5 for HE diets and A and B are sire line-sex specific parameters. cut weight = (1+bD(Diet)) A(CW Diet had no affect on loin, Boston butt, picnic, baby back rib, or sparerib weights (p>0.10, bD = -0.003, -0.0029, 0.0002, 0.0047, -0.0025, respectively). Diet affected ham weight (bD = -0.0046, p = 0.01), belly weight (bD = 0.0188, p = 0.001) three-muscle ham weight (bD = -0.014, p = 0.001), boneless loin weight (bD = -0.010, p = 0.001), tenderloin weight (bD = -0.023, p = 0.001), sirloin weight (bD = -0.009, p = 0.034), and fat-free lean mass (bD = -0.0145, p = 0.001). Overall, feeding the LE diets had little impact on primal cut weight except to decrease belly weight. Feeding LE diets increased the weight of lean trimmed cuts by 1 to 2 percent at the same carcass weight.