食品科学 ›› 2023, Vol. 44 ›› Issue (15): 351-367.doi: 10.7506/spkx1002-6630-20220704-025

• 专题论述 • 上一篇    

光谱学技术应用于肉类腐败检测的研究进展

刘庆森,罗欣,董鹏程,郝剑刚,毛衍伟,成海建,张一敏   

  1. (1.山东农业大学食品科学与工程学院,山东 泰安 271018;2.国家肉牛牦牛产业技术体系乌拉盖试验站,内蒙古 乌拉盖 026321;3.山东省农业科学院畜牧兽医研究所,山东 济南 250000)
  • 发布日期:2023-09-01
  • 基金资助:
    山东省生猪产业技术体系项目(SDAIT-08-10);现代农业产业技术体系建设专项(CARS-37); “十三五”国家重点研发计划政府间国际科技创新合作专项(2019YFE0103800)

Research Progress on the Application of Spectroscopy in Meat Spoilage Detection

LIU Qingsen, LUO Xin, DONG Pengcheng, HAO Jiangang, MAO Yanwei, CHENG Haijian, ZHANG Yimin   

  1. (1. College of Food Science and Engineering, Shandong Agricultural University, Tai’an 271018, China;2. National Beef Cattle Industrial Technology System, Wulagai Station, Wulagai 026321, China; 3. Institute of Animal Science and Veterinary Medicine, Shandong Academy of Agricultural Sciences, Jinan 250000, China)
  • Published:2023-09-01

摘要: 微生物的生长代谢是导致肉类腐败的主要原因,肉中微生物的快速、无损检测技术已受到越来越多的关注。其中以拉曼光谱、红外光谱和光谱成像为主的光谱学技术在快速、无损检测等方面表现出较大的优势,但是其在肉类腐败检测中的应用情况却未得到及时总结。因此,本文首先基于肉在不同贮藏条件下发生腐败的优势菌群及微生物代谢活动,简述肉类腐败能够进行光谱学预测的物质基础;然后在了解光谱技术建立预测模型方法的基础上,依次总结拉曼光谱、红外光谱和光谱成像技术在预测肉货架期方面的应用研究进展,并重点阐述以菌落总数或总挥发性盐基氮含量为指标建模进行预测的效果及其存在的问题,以期为利用快速无损检测技术对肉类腐败鉴定的研究提供思路和理论指导。

关键词: 快速检测;腐败微生物;拉曼光谱;红外光谱;光谱成像

Abstract: The growth and metabolism of microorganisms is the main cause of meat spoilage. The rapid and nondestructive techniques for detecting microorganisms in meat have attracted more and more attentions. Spectroscopic techniques such as Raman spectroscopy, infrared spectroscopy and spectral imaging show great advantages in rapid and non-destructive detection, but their application in meat spoilage detection has not been timely summarized. Based on an overview of the dominant spoilage organisms and microbial metabolism in meat under different storage conditions, this paper briefly describes the material basis for spectroscopic prediction of meat spoilage. Then, the application of Raman spectroscopy, infrared spectroscopy and spectral imaging technology in predicting the shelf life of meat is summarized. The efficiency of predictive modeling of meat shelf life based on total bacterial count or total volatile basic nitrogen (TVB-N) content and problems existing in this field are highlighted. We anticipate that this review will provide new ideas and theoretical guidance for the development and application of rapid and nondestructive techniques for meat spoilage identification.

Key words: rapid detection; spoilage microorganisms; Raman spectroscopy; infrared spectroscopy; spectral imaging

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