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Updated: Jan 9, 2026

Species Determination and Quantitation in Mixtures Using MRM Mass Spectrometry of Peptides Applied to Meat Authentication
Published on: September 20, 2016
Recent Advances in Spectroscopy and Imaging Techniques for Nondestructive Detection of Meat Quality and Safety
Yushan Jiang1, Dachen Wang2,3,4, Zijie Wang4
1College of Engineering Huazhong Agricultural University Wuhan China.
Abstract:
Meat is one of the most important foods in the human diet and is a major source of animal protein. It is essential to detect meat quality and safety for ensuring that high-quality foods are delivered to consumers. Advanced spectroscopic techniques (near-infrared spectroscopy, Raman spectroscopy, fluorescence spectroscopy, and terahertz spectroscopy) and imaging techniques (hyperspectral imaging, multispectral imaging, X-ray imaging, and thermal imaging) provide feasible means for testing organoleptic properties, chemical composition, physicochemical properties, and safety indicators of meat. This review aimed to summarize the latest developments of spectroscopic and imaging techniques for meat quality and safety detection. The principles, multi-scenario applications, advantages, disadvantages, and future prospects of these techniques are discussed. Spectroscopic techniques have been demonstrated to accurately detect changes in the chemical constituents and physical properties of meat, but can only perceive localized sample information. Imaging techniques provide visual information on the spatial distribution as well as physical and chemical characteristics of meat, but have a slower detection rate. Despite the remarkable outcomes attained by spectroscopy and imaging techniques in laboratory settings, their industrial applications remain encumbered by challenges, including substantial expenses and intricate data analysis procedures. In order to improve the comprehensiveness and accuracy of detection, future research directions might focus on the integration of multiple techniques combined with deep learning algorithms.
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