Evidence map›Paper›PMID 36807699›Full record

ArticleJournal of animal science2023

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

Justice B Dorleku, Lisa Wormsbecher, Mette Christensen, Cheryl P Campbell, Ira B Mandell, Benjamin M Bohrer

Open access · greenAbstract read
In one paragraph

Article in Journal of animal science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 3 institutions in 2 countries.

Justice B DorlekuDepartment of Food Science, University of Guelph, Guelph, ON N1G 2W1, Canada.
Lisa WormsbecherConestoga Meat Packers Ltd., Breslau, ON N0B 1M0, Canada.
Mette ChristensenFrontmatec Smørum A/S, Hassellunden 9, 2765 Smørum, Denmark.
Cheryl P CampbellDepartment of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada.
Ira B MandellDepartment of Animal Biosciences, University of Guelph, Guelph, ON N1G 2W1, Canada.
Benjamin M BohrerDepartment of Animal Sciences, The Ohio State University, Columbus, OH 43210, USA.
University of Guelph · CAConestoga Meat Packers (Canada) · CAThe Ohio State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Pork MeatRed MeatAdipose TissueAnimalsBody CompositionFemaleLeast-Squares AnalysisMeatMuscle, SkeletalSus scrofaSwineUltrasonicsAutoFomcarcass predictionDestronlean yieldpork gradingultrasound

Identifiers

PMID36807699
PMCPMC10032186
OpenAlexW4321352046

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.