Abstract Food frauds are a critical issue in the field of food safety and quality. Given the high added value, and the complexity of the matrix, processed meat products are among those most susceptible of adulteration. Despite all the efforts made by the official control authorities and by the food industry to counteract these frauds, the undeclared replacement of meat species with cheaper ones is still widespread. The meat species allowed for food consumption are many, and their specific and accurate detection in highly processed food products requires very sensitive and selective analytical methods. In this work, a LC-MS method was developed to identify and quantify eight different meat species (duck, rabbit, chicken, turkey, buffalo, equine, deer and sheep) in a complex food matrix, such as Bolognese sauce. After protein extraction and trypsin digestion, a species-specific peptide marker for each species was chosen for qualification and quantification. The method was validated on real Bolognese sauce samples prepared in an industrial environment, showing a good sensitivity (LOD 0.2–0.8% on whole finished product) and the possibility, using specifically defined calibration lines, to quantify the amount of meat present coming from different species.

中文翻译：

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用于肉类真实性评估的物种特异性标记肽：适用于肉酱酱的多物种定量方法

摘要 食品造假是食品安全和质量领域的一个关键问题。鉴于高附加值和复杂的基质，加工肉制品是最容易掺假的产品之一。尽管官方控制当局和食品行业为打击这些欺诈做出了一切努力，但未申报的用更便宜的肉类替代肉类的情况仍然普遍存在。允许食用的肉类种类很多，它们在高度加工食品中的特异性和准确检测需要非常灵敏和选择性的分析方法。在这项工作中，开发了一种 LC-MS 方法来识别和量化复杂食物基质（例如肉酱）中的八种不同肉类（鸭、兔、鸡、火鸡、水牛、马、鹿和羊）。在蛋白质提取和胰蛋白酶消化后，选择每个物种的物种特异性肽标记物进行定性和定量。该方法在工业环境中制备的真实肉酱样品上进行了验证，显示出良好的灵敏度（整个成品的 LOD 0.2–0.8%），并且可以使用专门定义的校准线来量化来自不同部位的肉量。物种。