a Department of Bioresource Engineering , McGill University , Ste-Anne-de-Bellevue , Quebec , Canada.
Crit Rev Food Sci Nutr. 2018 Jun 13;58(9):1565-1593. doi: 10.1080/10408398.2016.1261332. Epub 2017 Jul 5.
Conventional methods for determining fat content and fatty acids (FAs) composition are generally based on the solvent extraction and gas chromatography techniques, respectively, which are time consuming, laborious, destructive to samples and require use of hazard solvents. These disadvantages make them impossible for large-scale detection or being applied to the production line of meat factories. In this context, the great necessity of developing rapid and nondestructive techniques for fat and FAs analyses has been highlighted. Measurement techniques based on near-infrared spectroscopy, Raman spectroscopy, nuclear magnetic resonance and hyperspectral imaging have provided interesting and promising results for fat and FAs prediction in varieties of foods. Thus, the goal of this article is to give an overview of the current research progress in application of the four important techniques for fat and FAs analyses of muscle foods, which consist of pork, beef, lamb, chicken meat, fish and fish oil. The measurement techniques are described in terms of their working principles, features, and application advantages. Research advances for these techniques for specific food are summarized in detail and the factors influencing their modeling results are discussed. Perspectives on the current situation, future trends and challenges associated with the measurement techniques are also discussed.
传统的脂肪含量和脂肪酸（FA）组成的测定方法通常分别基于溶剂萃取和气相色谱技术，这些方法耗时、费力、对样品具有破坏性并且需要使用危险溶剂。这些缺点使得它们不可能进行大规模检测或应用于肉类工厂的生产线。在这种情况下，对于快速和非破坏性的脂肪和 FA 分析技术的开发提出了强烈的需求。基于近红外光谱、拉曼光谱、核磁共振和高光谱成像的测量技术为各种食品中的脂肪和 FA 预测提供了有趣且有前景的结果。因此，本文的目的是概述当前应用于肌肉食品中脂肪和 FA 分析的四种重要技术的研究进展，包括猪肉、牛肉、羊肉、鸡肉、鱼肉和鱼油。这些技术的测量技术根据其工作原理、特点和应用优势进行了描述。详细总结了这些技术在特定食品中的研究进展，并讨论了影响其建模结果的因素。还讨论了与测量技术相关的当前情况、未来趋势和挑战的观点。
