These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

116 related articles for article (PubMed ID: 33984801)

  • 1. An image analysis approach to identification and measurement of marbling in the intact pork loin.
    Uttaro B; Zawadski S; Larsen I; Juárez M
    Meat Sci; 2021 Sep; 179():108549. PubMed ID: 33984801
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Characterizing the amount and variability of intramuscular fat deposition throughout pork loins using barrows and gilts from two sire lines.
    Redifer JD; Beever JE; Stahl CA; Boler DD; Dilger AC
    J Anim Sci; 2020 Sep; 98(9):. PubMed ID: 32845331
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Prediction of pork loin quality using online computer vision system and artificial intelligence model.
    Sun X; Young J; Liu JH; Newman D
    Meat Sci; 2018 Jun; 140():72-77. PubMed ID: 29533814
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Determining the relationship between early postmortem loin quality attributes and aged loin quality attributes using meta-analyses techniques.
    Harsh BN; Boler DD; Shackelford SD; Dilger AC
    J Anim Sci; 2018 Jul; 96(8):3161-3172. PubMed ID: 29762689
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Relationships among early postmortem loin quality and aged loin and pork chop quality characteristics between barrows and gilts.
    Lowell JE; Overholt MF; Harsh BN; Stahl CA; Dilger AC; Boler DD
    Transl Anim Sci; 2017 Dec; 1(4):607-619. PubMed ID: 32704683
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Association between visual marbling score and chemical intramuscular fat with camera marbling percentage in Australian beef carcasses.
    Stewart SM; Gardner GE; Williams A; Pethick DW; McGilchrist P; Kuchida K
    Meat Sci; 2021 Nov; 181():108369. PubMed ID: 33261986
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Prediction of pork fat attributes using NIR Images of frozen and thawed pork.
    Huang H; Liu L; Ngadi MO
    Meat Sci; 2016 Sep; 119():51-61. PubMed ID: 27132204
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Accurate prediction and genome-wide association analysis of digital intramuscular fat content in longissimus muscle of pigs.
    Xie L; Qin J; Rao L; Tang X; Cui D; Chen L; Xu W; Xiao S; Zhang Z; Huang L
    Anim Genet; 2021 Oct; 52(5):633-644. PubMed ID: 34291482
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Do all the consumers accept marbling in the same way? The relationship between eating and visual acceptability of pork with different intramuscular fat content.
    Font-i-Furnols M; Tous N; Esteve-Garcia E; Gispert M
    Meat Sci; 2012 Aug; 91(4):448-53. PubMed ID: 22429803
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Marbling-Net: A Novel Intelligent Framework for Pork Marbling Segmentation Using Images from Smartphones.
    Zhang S; Chen Y; Liu W; Liu B; Zhou X
    Sensors (Basel); 2023 May; 23(11):. PubMed ID: 37299862
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Assessment of muscle Longissimus thoracis et lumborum marbling by image analysis and relationships between meat quality parameters.
    Giaretta E; Mordenti AL; Canestrari G; Brogna N; Palmonari A; Formigoni A
    PLoS One; 2018; 13(8):e0202535. PubMed ID: 30133495
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Evaluation of the changes in composition of pork chops during cooking.
    Gaffield KN; Schunke ED; Lowell JE; Dilger AC; Harsh BN
    Transl Anim Sci; 2020 Jul; 4(3):txaa154. PubMed ID: 32904975
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Intramuscular fat content has little influence on the eating quality of fresh pork loin chops.
    Rincker PJ; Killefer J; Ellis M; Brewer MS; McKeith FK
    J Anim Sci; 2008 Mar; 86(3):730-7. PubMed ID: 18156359
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Effect of dietary conjugated linoleic acid on marbling and intramuscular adipocytes in pork.
    Barnes KM; Winslow NR; Shelton AG; Hlusko KC; Azain MJ
    J Anim Sci; 2012 Apr; 90(4):1142-9. PubMed ID: 22079992
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Predicting pork loin intramuscular fat using computer vision system.
    Liu JH; Sun X; Young JM; Bachmeier LA; Newman DJ
    Meat Sci; 2018 Sep; 143():18-23. PubMed ID: 29684840
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Combining computer vision score and conventional meat quality traits to estimate the intramuscular fat content using machine learning in pigs.
    Chen D; Wu P; Wang K; Wang S; Ji X; Shen Q; Yu Y; Qiu X; Xu X; Liu Y; Tang G
    Meat Sci; 2022 Mar; 185():108727. PubMed ID: 34971942
    [TBL] [Abstract][Full Text] [Related]  

  • 17. The effects of instrumental color and extractable lipid content on sensory characteristics of pork loin chops cooked to a medium-rare degree of doneness.
    Wilson KB; Overholt MF; Shull CM; Schwab C; Dilger AC; Boler DD
    J Anim Sci; 2017 May; 95(5):2052-2060. PubMed ID: 28726999
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Comparison of variability in pork carcass composition and quality between barrows and gilts.
    Overholt MF; Arkfeld EK; Mohrhauser DA; King DA; Wheeler TL; Dilger AC; Shackelford SD; Boler DD
    J Anim Sci; 2016 Oct; 94(10):4415-4426. PubMed ID: 27898864
    [TBL] [Abstract][Full Text] [Related]  

  • 19. The influence of ultimate pH and intramuscular fat content on pork tenderness and tenderization.
    van Laack RL; Stevens SG; Stalder KJ
    J Anim Sci; 2001 Feb; 79(2):392-7. PubMed ID: 11219448
    [TBL] [Abstract][Full Text] [Related]  

  • 20. An open-access computer image analysis (CIA) method to predict meat and fat content from an android smartphone-derived picture of the bovine 5th-6th rib.
    Meunier B; Normand J; Albouy-Kissi B; Micol D; El Jabri M; Bonnet M
    Methods; 2021 Feb; 186():79-89. PubMed ID: 32649989
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 6.