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Spectral Detection Techniques for Non-Destructively Monitoring the Quality, Safety, and Classification of Fresh Red Meat

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Abstract

Red meat is an important source of nutrients and plays a significant role in human diet. With the development of people’s living standard and relative change of dietary structure in recent years, people propose more requirements for meat. Quality, safety, and classification are three crucial themes related with meat and they are important issues for consumers, retailers, as well as the whole meat industry. However, most of the traditional analytical methods for meat evaluation are time-consuming, laborious, tedious, and destructive, which make them inappropriate for fast analysis and early detection, especially under fast-paced production and processing environment. In contrast to conventional approaches, spectral techniques including near infrared spectroscopy (NIRS), hyperspectral imaging (HSI), and Raman spectroscopy (RS) have emerged and considered as promising tools for meat assessment. The innovative optical sensing techniques can facilitate simple, fast, accurate, and simultaneous measurements of multiple meat attributes. Recently, these techniques have achieved rapid development and attracted more attention of the public. Hence, the goal of this article is to give an overview of the current progress of the spectral techniques for evaluation of fresh red meat (pork, beef, and lamb). The spectral techniques are described in terms of their basic working principle, fundamental configurations, analysis process, as well as applications on meat inspection. In addition, the problems to be tackled and future potential trends of these spectral methods are also discussed in this paper.

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Funding

This study was supported by the National Key Research and Development Program (Project No. 2016YFD0101205) and major projects of the National Agricultural Products Quality and Safety Risk Assessment (Project No. GJFP201701504).

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Correspondence to Yankun Peng.

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Wenxiu Wang declares that she has no conflict of interest. Yankun Peng declares that he has no conflict of interest. Hongwei Sun declares that he has no conflict of interest. Xiaochun Zheng declares that he has no conflict of interest. Wensong Wei declares that he has no conflict of interest.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Wang, W., Peng, Y., Sun, H. et al. Spectral Detection Techniques for Non-Destructively Monitoring the Quality, Safety, and Classification of Fresh Red Meat. Food Anal. Methods 11, 2707–2730 (2018). https://doi.org/10.1007/s12161-018-1256-4

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  • DOI: https://doi.org/10.1007/s12161-018-1256-4

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