Evaluating the Texture, Physical and Chemical Properties, and Sensory Characteristics of Livestock and Poultry Meat

A special issue of Foods (ISSN 2304-8158). This special issue belongs to the section "Meat".

Deadline for manuscript submissions: 31 May 2026 | Viewed by 1220

Special Issue Editors


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Guest Editor
Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Key Laboratory of Agro-products Quality and Safety Control in Storage and Transport Process, Ministry of Agriculture and Rural Affairs, Beijing 100193, China
Interests: digital characterization technology for the quality of livestock and poultry

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Guest Editor
Key Laboratory of Agro-Products Processing, Ministry of Agriculture and Rural Affairs, Institute of Food Science and Technology, Chinese Academy of Agricultural Sciences, Beijing 100193, China
Interests: meat

Special Issue Information

Dear Colleagues,

The quality characteristics of meat (such as its physicochemical properties, texture, and sensory attributes) determine its processing suitability and final product quality. In recent years, with advancements in food science, materials science, artificial intelligence, and data science, traditional meat quality evaluation methods have increasingly integrated cutting-edge detection and analysis technologies. These approaches not only enhance the accuracy of meat quality assessment but also provide new insights for optimizing processing techniques. This Special Issue aims to bring together the latest research findings, exploring key factors influencing meat quality, scientific evaluation methods for processing suitability, and the application of intelligent data analysis in meat quality prediction and optimization.

Dr. Li Chen
Dr. Xiaochun Zheng
Guest Editors

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Keywords

  • meat quality
  • physicochemical properties
  • texture profile
  • sensory evaluation
  • processing suitability
  • smart sensory evaluation
  • machine learning applications
  • food big data

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Published Papers (1 paper)

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Research

18 pages, 5387 KB  
Article
Random Forest-Assisted Widely Targeted Lipidomic Reveals Differences in Tan Lamb Meat Quality in Different Regions
by Qi Yang, Chongxin Liu, Muxuan Xu, Minghui Gu, Le Xu, Shaobo Li, Xiaochun Zheng, Dequan Zhang and Li Chen
Foods 2025, 14(23), 4046; https://doi.org/10.3390/foods14234046 - 26 Nov 2025
Viewed by 876
Abstract
This study aims to elucidate the quality differences among Tan lamb from three major production regions and investigate the influence and regulation of lipids on regional sheep meat quality. The Ningxia Tan lamb exhibited higher pH values, lower lightness and yellowness, better water-holding [...] Read more.
This study aims to elucidate the quality differences among Tan lamb from three major production regions and investigate the influence and regulation of lipids on regional sheep meat quality. The Ningxia Tan lamb exhibited higher pH values, lower lightness and yellowness, better water-holding capacity and more polyunsaturated fatty acids compared to the other regions. GC-IMS revealed different flavor profiles of Tan lamb from different regions. A total of 1080 lipids across 41 lipid subclasses were identified, with 10 lipid molecules, including PC (16:0_16:1), Carnitine C3:0 and Carnitine C5:1, serving as key differentiators among the regions, as determined by the Random Forest method. Correlation analysis revealed strong associations between acyl lipid characteristics and pH, lightness and centrifugal loss, while glycerophospholipid characteristics were significantly correlated with basic nutritional indices. Lipid metabolic pathway analysis indicated that thermogenesis, glycerophospholipid metabolism and metabolic pathways as crucial for Tan lamb growth, serving as major pathways for distinguishing different regional Tan lamb. These findings indicate that origin influences lamb quality and lipid composition and that a relationship may exist between lamb quality and lipid variations. This provides a comprehensive understanding of how lamb quality is formed and contributes to future identification of lamb origins, as well as control and enhancement of meat quality. Full article
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