Files and links (1)
CC BY V4.0, Open Access
Journal article
Improved cut weight predictions from DEXA scans of lamb carcasses enables more accurate allocation of cuts to processing plans
Meat Science, Vol.216, 109556
2024
Abstract
The value of precise dual energy X-ray absorptiometry (DEXA) cut weight predictions to lamb allocation to cut plans is unknown. Lambs (n = 191) varying in carcase weight (HSCW) and GR (tissue depth over the 12th rib) were DEXA scanned and boned out to weigh retail cuts. Cut weights were predicted using HSCW; HSCW + GR; HSCW + DEXA and HSCW + DEXA image components in GLM models. DEXA improved cut weight predictions in most cuts (P < 0.05). A dataset of 10,000 carcases was then simulated using the associations between HSCW, GR and cut weights, before being truncated to 4500 lambs representing onel day's HSCW distribution. A lamb Carcase Optimisation Tool scenario was developed with 2–3 cut options per carcase section and cut weight thresholds applied to several cuts. Processing costs, market values and actual cut weights were input into the Optimiser to determine carcase allocation to cut options for optimised profits. This scenario was repeated using the predicted cut weights to determine the cut misallocations caused. DEXA-predicted cut weights produced 16.7% and 8.0% less misallocations than HSCW and GR. DEXA produced 20.8% and 14.3% less misallocations than HSCW and GR in shortloins, and 25.5% and 12.9% less in hindquarters. While cut misallocations have little direct impact on total profits, as product is over and under-valued when misallocated, reducing cut misallocations will improve processor compliance when sorting carcases into cut plans- reducing their need to retrim, downgrade and repackage product or the erosion of customer confidence caused by supplying product not meeting market specifications.
Details
- Title
- Improved cut weight predictions from DEXA scans of lamb carcasses enables more accurate allocation of cuts to processing plans
- Authors/Creators
- Honor Calnan - Murdoch University, Centre for Animal Production and HealthA. Williams - Murdoch UniversityC. Alston-Knox - Predictive ScienceG. WangW.S. Pitchford - The University of AdelaideGraham Gardner - Murdoch University, Centre for Animal Production and Health
- Publication Details
- Meat Science, Vol.216, 109556
- Publisher
- Elsevier Ltd.
- Identifiers
- 991005674867607891
- Copyright
- © 2024 The Authors.
- Murdoch Affiliation
- School of Agricultural Sciences; Centre for Animal Production and Health
- Resource Type
- Journal article
UN Sustainable Development Goals (SDGs)
This output has contributed to the advancement of the following goals:
Metrics
9 File views/ downloads
36 Record Views
InCites Highlights
These are selected metrics from InCites Benchmarking & Analytics tool, related to this output
- Collaboration types
- Domestic collaboration
- Citation topics
- 3 Agriculture, Environment & Ecology
- 3.51 Dairy & Animal Sciences
- 3.51.206 Meat Quality
- Web Of Science research areas
- Food Science & Technology
- ESI research areas
- Agricultural Sciences