牛肉作为高价值食用肉类一直是肉制品造假的重灾区,构建一种高通量、快速、经济的牛肉鉴别方法势在必行。该研究在简单、快速地完成生、熟牛鸡鸭猪4种肉的蛋白质提取后,利用具有高通量、操作简便优势的基质辅助激光解析电离飞行时间质谱,采集蛋白质质谱数据,共获得生肉的129个离子峰和熟肉的151个离子峰,经数据预处理后,采用随机森林算法筛选到11个能区分4种肉的特征蛋白质,再结合主成分分析数据降维与数据可视化的优势,构建牛肉掺假鉴别模型,最后通过完成对掺假牛肉样本的检测以验证模型。结果表明,4种肉均能通过该方法得到较好的区分,且生熟状态下的掺假牛肉均能得到鉴别,证明该方法能准确、简便地完成生熟牛肉掺假初筛的目标。
Beef, a kind of high-value edible meat, is always adulterated with low price meats in daily life. Therefore, the development of a reliable, high throughput, and economic method for beef identification is necessary. In this study, proteins of fresh and cooked chicken, duck, pork, and beef meats were extracted and then characterized with matrix-assisted laser desorption/ionization time of flight mass spectrometry. Totally, 129 ion peaks of fresh meats and 151 ion peaks of cooked meats were obtained. Among them, 11 characteristic proteins which enabled the differentiation of the 4 specifics of meat were discovered by random forest. Using the in-house prepared adulterated beef samples as the target samples, the capability of the 11 characteristic proteins for beef authentication was assessed with principal component analysis. Results showed that this method allowed the authentication of beef simply and reliably.
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