Prediction of Whole Pork Loin and Individual Chops’ Intramuscular Fat Using Computer Vision System Technology
The objective of this study was to compare different methods of evaluating intramuscular fat (IMF) in pork and test the accuracy of using a computer vision system (CVS) on different locations of the loin. Whole pork loins (n = 1,400) were obtained from 6 pork processing plants. Subjective marbling s...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Iowa State University Digital Press
2020-11-01
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| Series: | Meat and Muscle Biology |
| Subjects: | |
| Online Access: | https://www.iastatedigitalpress.com/mmb/article/id/11127/ |
| _version_ | 1797222187001708544 |
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| author | David Newman Jeng-Hung Liu Jennifer M. Young Xin (Rex) Sun |
| author_facet | David Newman Jeng-Hung Liu Jennifer M. Young Xin (Rex) Sun |
| author_sort | David Newman |
| collection | DOAJ |
| description | The objective of this study was to compare different methods of evaluating intramuscular fat (IMF) in pork and test the accuracy of using a computer vision system (CVS) on different locations of the loin. Whole pork loins (n = 1,400) were obtained from 6 pork processing plants. Subjective marbling scores and CVS IMF percentage (CVS IMF%) were assessed on the ventral lean surface of the whole loin and the 3rd (A) and 10th (B) rib chops. Additionally, the A and B chops were evaluated for crude fat percentage (CF%) using ether extract. The CF% of the whole loin was represented by using the average CF% of A and B chops. A combination of the bootstrap method and stepwise regression models was used to increase prediction and robustness for CF% prediction. To better understand whether plants played an effect, models for individual plants and using all plants together were built, tested, and compared. Results were that subjective marbling score had stronger correlations with CF% compared to CVS IMF% for the whole loin (0.70 vs. 0.58), A chop (0.79 vs.0.62), and B chop (0.74 vs. 0.61). When using the stepwise regression models to predict CF%, B chop (71.8%) had the highest prediction accuracy (estimates within 0.5% residual compared to CF% were considered accurate) followed by A chop (58.1%) and whole loin (48.2%). When comparing individual plant models and overall models, the overall accuracy improved; however, this improvement in accuracy was not consistent through every single plant. In conclusion, CVS has shown potential to estimate pork IMF on all locations, especially the posterior pork chop. |
| first_indexed | 2024-04-24T13:17:20Z |
| format | Article |
| id | doaj.art-9102e71b480d46d8ad5b3680beb34d34 |
| institution | Directory Open Access Journal |
| issn | 2575-985X |
| language | English |
| last_indexed | 2024-04-24T13:17:20Z |
| publishDate | 2020-11-01 |
| publisher | Iowa State University Digital Press |
| record_format | Article |
| series | Meat and Muscle Biology |
| spelling | doaj.art-9102e71b480d46d8ad5b3680beb34d342024-04-04T17:28:21ZengIowa State University Digital PressMeat and Muscle Biology2575-985X2020-11-014110.22175/mmb.11127Prediction of Whole Pork Loin and Individual Chops’ Intramuscular Fat Using Computer Vision System TechnologyDavid Newman0Jeng-Hung Liu1Jennifer M. Young2https://orcid.org/0000-0002-3171-9187Xin (Rex) Sun3N/aDepartment of Animal Sciences, North Dakota State UniversityAnimal Sciences, North Dakota State UniversityN/aThe objective of this study was to compare different methods of evaluating intramuscular fat (IMF) in pork and test the accuracy of using a computer vision system (CVS) on different locations of the loin. Whole pork loins (n = 1,400) were obtained from 6 pork processing plants. Subjective marbling scores and CVS IMF percentage (CVS IMF%) were assessed on the ventral lean surface of the whole loin and the 3rd (A) and 10th (B) rib chops. Additionally, the A and B chops were evaluated for crude fat percentage (CF%) using ether extract. The CF% of the whole loin was represented by using the average CF% of A and B chops. A combination of the bootstrap method and stepwise regression models was used to increase prediction and robustness for CF% prediction. To better understand whether plants played an effect, models for individual plants and using all plants together were built, tested, and compared. Results were that subjective marbling score had stronger correlations with CF% compared to CVS IMF% for the whole loin (0.70 vs. 0.58), A chop (0.79 vs.0.62), and B chop (0.74 vs. 0.61). When using the stepwise regression models to predict CF%, B chop (71.8%) had the highest prediction accuracy (estimates within 0.5% residual compared to CF% were considered accurate) followed by A chop (58.1%) and whole loin (48.2%). When comparing individual plant models and overall models, the overall accuracy improved; however, this improvement in accuracy was not consistent through every single plant. In conclusion, CVS has shown potential to estimate pork IMF on all locations, especially the posterior pork chop.https://www.iastatedigitalpress.com/mmb/article/id/11127/pork loinpork qualityintramuscular fatpork chopcomputer vision system |
| spellingShingle | David Newman Jeng-Hung Liu Jennifer M. Young Xin (Rex) Sun Prediction of Whole Pork Loin and Individual Chops’ Intramuscular Fat Using Computer Vision System Technology Meat and Muscle Biology pork loin pork quality intramuscular fat pork chop computer vision system |
| title | Prediction of Whole Pork Loin and Individual Chops’ Intramuscular Fat Using Computer Vision System Technology |
| title_full | Prediction of Whole Pork Loin and Individual Chops’ Intramuscular Fat Using Computer Vision System Technology |
| title_fullStr | Prediction of Whole Pork Loin and Individual Chops’ Intramuscular Fat Using Computer Vision System Technology |
| title_full_unstemmed | Prediction of Whole Pork Loin and Individual Chops’ Intramuscular Fat Using Computer Vision System Technology |
| title_short | Prediction of Whole Pork Loin and Individual Chops’ Intramuscular Fat Using Computer Vision System Technology |
| title_sort | prediction of whole pork loin and individual chops intramuscular fat using computer vision system technology |
| topic | pork loin pork quality intramuscular fat pork chop computer vision system |
| url | https://www.iastatedigitalpress.com/mmb/article/id/11127/ |
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