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低场核磁共振二维指纹谱技术在肉松种类快速检测中的应用研究

Application of low-field nuclear magnetic resonance 2D fingerprint spectroscopy technology in rapid quality detection of pork floss products

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【作者】 胡艺骞; 徐成; 胡涛; 周希韵; 胡文涛; 王雪璐; 姚叶锋;

【Author】 HU Yi-Qian;XU Cheng;HU Tao;ZHOU Xi-Yun;HU Wen-Tao;WANG Xue-Lu;YAO Ye-Feng;Shanghai Key Laboratory of Magnetic Resonance,College of Physics and Electronic Science,East China Normal University;Suzhou Institute for Food Control;Institute of Magnetic Resonance and Molecular Imaging in Medicine,East China Normal University;

【通讯作者】 王雪璐;姚叶锋;

【机构】 上海市磁共振重点实验室,华东师范大学物理与电子科学学院; 苏州市食品检验检测中心; 华东师范大学医学磁共振与分子影像技术研究院;

【摘要】 目的 利用低场核磁共振技术实现对市面上常见肉松种类的快速无损检测与识别。方法 本研究开发了一种适用于肉松制品种类快速检测的低场核磁共振二维弛豫指纹谱方法,基于指纹谱色度差异区分肉松种类。结果 基于研发的二维弛豫指纹谱技术方法,可对市面上常见的猪肉、鸡肉、牛肉、鱼肉及其混合肉松进行快速无损区分。随着肉松中不同成分比例的变化,指纹谱展现出明显的定性变化趋势,能够有效反映肉松中各类肉类的比例变化,证实了该技术的精确性。结论 本研究方法可以快速无损并精确地区分市面上大部分肉松种类,能够满足食品行业和政府检测机构的需求,是一种具有巨大前景的新型检测手段。

【Abstract】 Objective To achieve the identification and rapid detection of commonly found types of meat floss on the market via low-field nuclear magnetic resonance. Methods This study developed a low-field nuclear magnetic resonance two-dimensional relaxation fingerprinting technique suitable for the rapid detection of meat floss product types. Based on the colour discrepancy, different types of meat floss products can be distinguished. Results The developed two-dimensional relaxation fingerprinting technique can quickly and non-destructively distinguish between commonly available pork, chicken, beef, fish, and their mixed meat floss products.With the change in the proportion of different components in meat floss, the fingerprint spectrum shows a significant qualitative trend,effectively reflecting the changes in the proportion of various meats in meat floss, which proves the accuracy of this technology. Conclusion This research method can rapidly, non-destructively and accurately differentiate most types of meat floss on the market, meeting the needs of the food industry and government testing institutions, making it a promising new detection tool with great potential.

  • 【文献出处】 食品安全质量检测学报 ,Journal of Food Safety & Quality , 编辑部邮箱 ,2025年12期
  • 【分类号】TS251.63;O657.2
  • 【下载频次】44
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