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Published (Version of Record)CC BY V4.0, Open Access
Journal article
Fresh Pork Quality Assessment by NIRS and NMR: Predicting Eating Quality and Elucidating Relationships with Key Chemical Components
Animals (Basel), Vol.15(20), 2973
2025
Abstract
The Australian pork industry has been seeking a rapid and non-destructive way to predict pork chemical components and eating quality. In this study, near-infrared spectroscopy (NIRS) and nuclear magnetic resonance (NMR) were applied to fresh pork Longissimus thoracis et lumborum (LTL) and Semimembranosus (SM) with the aim to build prediction models for intramuscular fat (IMF) content, collagen content and solubility, pH, and sensory attributes, namely tenderness, juiciness, liking of flavor and overall liking as well as investigate the effects of chemical components on pork eating quality. Results showed that the NIRS output, which was a predicted IMF content calibrated for the IMF of lamb, correlated with the chemically analyzed IMF content across both muscles. In LTL, NMR parameter p2f was weakly correlated with IMF and pH. For the LTL, NMR parameters p21 and p22 were related to sensory tenderness, while T22 was correlated with the liking of flavor. In both muscles, the collagen content and pH were related to all sensory attributes, and IMF was related to the liking of flavor. The chemical properties of SM were weakly correlated with those of LTL. The NIRS and NMR weakly predicted the pork chemical components and sensory properties, but more studies are required to improve the accuracy.
Details
- Title
- Fresh Pork Quality Assessment by NIRS and NMR: Predicting Eating Quality and Elucidating Relationships with Key Chemical Components
- Authors/Creators
- Xiying Li - The University of MelbourneMelindee Hastie - The University of MelbourneMinh Ha - Myer FoundationRobyn D. Warner - The University of MelbourneCameron C. Steel - University of New EnglandPeter McGilchrist - University of New EnglandEvan McCarneyDarryl N. D’SouzaRobert J. E. HewittDavid W. Pethick - Murdoch UniversityMaddison T. Corlett - Murdoch UniversitySarah M. Stewart - Murdoch UniversityFrank R. Dunshea - University of Leeds
- Publication Details
- Animals (Basel), Vol.15(20), 2973
- Publisher
- MDPI
- Identifiers
- 991005823093107891
- Copyright
- © 2025 by the authors.
- Murdoch Affiliation
- School of Agricultural Sciences; Food Futures Institute
- Language
- English
- Resource Type
- Journal article
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