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

Author:

Dorleku Justice B1,Wormsbecher Lisa2,Christensen Mette3,Campbell Cheryl P4,Mandell Ira B4,Bohrer Benjamin M5

Affiliation:

1. Department of Food Science, University of Guelph , Guelph, ON N1G 2W1 , Canada

2. Conestoga Meat Packers Ltd. , Breslau, ON N0B 1M0 , Canada

3. Frontmatec Smørum A/S , Hassellunden 9, 2765 Smørum , Denmark

4. Department of Animal Biosciences, University of Guelph , Guelph, ON N1G 2W1 , Canada

5. Department of Animal Sciences, The Ohio State University , Columbus, OH 43210 , USA

Abstract

AbstractThis 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.

Publisher

Oxford University Press (OUP)

Subject

Genetics,Animal Science and Zoology,General Medicine,Food Science

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