Validation of rapid evaporative ionization mass spectrometry (REIMS) for prediction of beef tenderness

快速蒸发电离质谱法（REIMS）是人类医学领域出现的一项新技术，它是从iKnife发展而来的，iKnife是一种医疗切割工具，在切割时可以烧灼组织。在烧灼过程中，生物挥发物被释放并吸入REIMS系统，使用飞行时间（TOF）质谱法鉴定和定量挥发物分子。基于reims的组织分析通常只需要几秒钟，可以提供90-98%的准确率的组织学组织鉴定。REIMS分析通过实时电离生物样品提供原位分子信息，无需任何样品制备，操作员可在几秒钟内获得高精度的质谱。利用已知成分样品的质谱，可以建立模型来预测和分类感兴趣的组织。近年来，REIMS在肉类工业中的应用包括物种认证、风味预测和残留检测。产生的分子特征可以用来预测牛肉的成分、食用质量和新鲜度。本研究将检验该技术预测牛肉胶原蛋白特性和最终牛肉嫩度的能力，作为开发在线工厂内系统的一部分，将牛肉分类，反映加工和食用质量的切实差异。这项研究的结果是，像嘉吉这样的牛肉加工商将能够将牛肉分配到适当的价值，从而使其价值最大化，从而使产品收入最大化。

Rapid evaporative ionization mass spectrometry (REIMS) is a new technology emerging from human medicine that was developed from the iKnife, a medical cutting tool that cauterizes tissue as it cuts. During cauterization, biological volatiles are released and drawn into the REIMS system, with volatile molecules identified and quantified using time of flight (TOF) mass spectrometry. REIMS-based tissue analysis generally takes only a few seconds and can provide histological tissue identification with 90-98% accuracy. REIMS profiling provides in situ molecular information by ionizing biological samples in real-time without any sample preparation and the operator is provided with a highly accurate mass spectrum within seconds. Using mass spectra from samples of known composition, models can be developed to predict and classify the tissue of interest. Recent application of REIMS in the meat industry include species authentication, flavour prediction, and residue testing. The molecular signatures produced potentially can be used to predict beef composition, eating quality, and freshness. This research will examine the ability of this technology to predict beef collagen characteristics and ultimately beef tenderness as part of developing an on-line in-plant system to sort beef into categories reflecting tangible differences in processing and eating quality. As a result of this research, beef processors such as Cargill will be able to allocate beef to the appropriate value so that it is optimally valued, thus maximising product revenue.