Decoding the spectrum of meat quality: advances in hyperspectral imaging for multi-attribute analysis.
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| Titel: | Decoding the spectrum of meat quality: advances in hyperspectral imaging for multi-attribute analysis. |
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| Autoren: | Yi X; College of Animal Science, Northwest A&F University, Yangling, Shaanxi 712100, PR China. Electronic address: yiyi2845655967@gmail.com., Li W; College of Animal Engineering, Shaanxi A&F Technology University, Yangling, Shaanxi 712100, PR China; Innovative Team for Livestock and Poultry Gut Health and Efficient Farming Technologies, Yangling, Shaanxi 712100, PR China., Li Y; College of Animal Engineering, Shaanxi A&F Technology University, Yangling, Shaanxi 712100, PR China; Key Laboratory for Efficient Ruminant Breeding Technology of Higher Education Institutions, Yangling, Shaanxi 712100, PR China., Ren J; College of Animal Engineering, Shaanxi A&F Technology University, Yangling, Shaanxi 712100, PR China., Zhang J; College of Animal Engineering, Shaanxi A&F Technology University, Yangling, Shaanxi 712100, PR China., Li B; College of Animal Engineering, Shaanxi A&F Technology University, Yangling, Shaanxi 712100, PR China; Key Laboratory for Efficient Ruminant Breeding Technology of Higher Education Institutions, Yangling, Shaanxi 712100, PR China., Li L; College of Animal Engineering, Shaanxi A&F Technology University, Yangling, Shaanxi 712100, PR China; Innovative Team for Livestock and Poultry Gut Health and Efficient Farming Technologies, Yangling, Shaanxi 712100, PR China., Liu W; College of Animal Engineering, Shaanxi A&F Technology University, Yangling, Shaanxi 712100, PR China., Lian F; College of Animal Engineering, Shaanxi A&F Technology University, Yangling, Shaanxi 712100, PR China., Xiao J; Shaanxi Shiyang Agricultural Science and Technology Co., Ltd, Weinan, Shaanxi 715500, PR China. Electronic address: xxxiaojy@163.com., Zhang W; College of Animal Engineering, Shaanxi A&F Technology University, Yangling, Shaanxi 712100, PR China; Key Laboratory for Efficient Ruminant Breeding Technology of Higher Education Institutions, Yangling, Shaanxi 712100, PR China. Electronic address: zwryz666@163.com. |
| Quelle: | Food chemistry [Food Chem] 2025 Dec 25; Vol. 496 (Pt 3), pp. 146912. Date of Electronic Publication: 2025 Nov 01. |
| Publikationsart: | Journal Article; Review |
| Sprache: | English |
| Info zur Zeitschrift: | Publisher: Elsevier Applied Science Publishers Country of Publication: England NLM ID: 7702639 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1873-7072 (Electronic) Linking ISSN: 03088146 NLM ISO Abbreviation: Food Chem Subsets: MEDLINE |
| Imprint Name(s): | Publication: Barking : Elsevier Applied Science Publishers Original Publication: Barking, Eng., Applied Science Publishers. |
| MeSH-Schlagworte: | Meat*/analysis , Hyperspectral Imaging*/methods , Hyperspectral Imaging*/instrumentation, Animals ; Cattle ; Poultry ; Swine ; Food Quality |
| Abstract: | Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Hyperspectral imaging (HSI) has emerged as a powerful non-destructive technique for evaluating fresh meat quality across multiple attributes simultaneously. This review critically examines recent advances in HSI applications for fresh beef, pork, and poultry, highlighting how HSI decodes key quality parameters such as freshness, intramuscular fat (IMF) content, adulteration, microbial contamination, nutritional composition, and other traits including tenderness, pH, and water-holding capacity. We also cover the fundamental principles and instrumentation of HSI systems. Finally, cutting-edge developments in data analysis, including the integration of artificial intelligence, deep learning, and data fusion, are also discussed in terms of their role in enhancing prediction reliability and enabling real-world implementation. This review provides a comprehensive overview of how HSI is revolutionizing fresh meat quality evaluation and outlines the challenges and opportunities ahead on the path toward industrial adoption. (Copyright © 2025 Elsevier Ltd. All rights reserved.) |
| Contributed Indexing: | Keywords: Beef; Hyperspectral imaging; Meat quality; Pork |
| Entry Date(s): | Date Created: 20251106 Date Completed: 20251125 Latest Revision: 20251125 |
| Update Code: | 20251125 |
| DOI: | 10.1016/j.foodchem.2025.146912 |
| PMID: | 41197306 |
| Datenbank: | MEDLINE |
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Nájsť tento článok vo Web of Science | Abstract: | Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.<br />Hyperspectral imaging (HSI) has emerged as a powerful non-destructive technique for evaluating fresh meat quality across multiple attributes simultaneously. This review critically examines recent advances in HSI applications for fresh beef, pork, and poultry, highlighting how HSI decodes key quality parameters such as freshness, intramuscular fat (IMF) content, adulteration, microbial contamination, nutritional composition, and other traits including tenderness, pH, and water-holding capacity. We also cover the fundamental principles and instrumentation of HSI systems. Finally, cutting-edge developments in data analysis, including the integration of artificial intelligence, deep learning, and data fusion, are also discussed in terms of their role in enhancing prediction reliability and enabling real-world implementation. This review provides a comprehensive overview of how HSI is revolutionizing fresh meat quality evaluation and outlines the challenges and opportunities ahead on the path toward industrial adoption.<br /> (Copyright © 2025 Elsevier Ltd. All rights reserved.) |
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| ISSN: | 1873-7072 |
| DOI: | 10.1016/j.foodchem.2025.146912 |