PTR-TOF-MS and data-mining methods for rapid characterisation of agro-industrial samples: influence of milk storage conditions on the volatile compounds profile of Trentingrana cheese
PTR-TOF-MS and data-mining methods for rapid characterisation of agro-industrial samples: influence of milk storage conditions on the volatile compounds profile of Trentingrana cheese
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DOI：
10.1002/jms.1797
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发表时间：
2010-09-01
影响因子：
2.3
通讯作者：
Endrizzi, Isabella
中科院分区：
文献类型：
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作者：
Fabris, Alessandra;Biasioli, Franco;Endrizzi, Isabella
质子转移反应质谱 (PTR-MS) 是一种基于有效实施化学电离的直接注射质谱技术，可对挥发性有机化合物 (VOC) 进行快速、高灵敏度的监测。 PTR-MS 的首次实施基于四极杆质量分析仪 (PTR-Quad-MS)，仅提供测量离子的标称质量，因此几乎没有化学信息。为了部分克服这些限制并提高该技术的分析能力，质子转移反应电离与飞行时间质量分析器的耦合最近已实现并商业化（PTR-TOF-MS）。在这里，我们讨论这种新仪器在农业工业问题，特别是乳制品科学中的首次应用。作为案例研究，我们在此展示快速 PTR-TOF-MS 指纹识别与数据挖掘方法相结合可以快速验证牛奶的储存条件是否影响奶酪的最终质量，并且与之前的 PTR-MS 实施相比，我们提供了更好的化合物识别的相关示例。特别是，在冬季和夏季生产的情况下，对通过四种不同的牛奶储存程序生产的“Trentingrana”奶酪进行了比较。确实可以设置预测误差较低的分类模型，并确定用于分类的离子峰的化学式，从而证明这种新颖的光谱技术可以在基础和应用农工业主题中发挥作用。版权所有 (C) 2010 约翰·威利父子有限公司
Proton transfer reaction-mass spectrometry (PTR-MS), a direct injection mass spectrometric technique based on an efficient implementation of chemical ionisation, allows for fast and high-sensitivity monitoring of volatile organic compounds (VOCs). The first implementations of PTR-MS, based on quadrupole mass analyzers (PTR-Quad-MS), provided only the nominal mass of the ions measured and thus little chemical information. To partially overcome these limitations and improve the analytical capability of this technique, the coupling of proton transfer reaction ionisation with a time-of-flight mass analyser has been recently realised and commercialised (PTR-TOF-MS). Here we discuss the very first application of this new instrument to agro-industrial problems and dairy science in particular. As a case study, we show here that the rapid PTR-TOF-MS fingerprinting coupled with data-mining methods can quickly verify whether the storage condition of the milk affects the final quality of cheese and we provide relevant examples of better compound identification in comparison with the previous PTR-MS implementations. In particular, 'Trentingrana' cheese produced by four different procedures for milk storage are compared both in the case of winter and summer production. It is indeed possible to set classification models with low prediction errors and to identify the chemical formula of the ion peaks used for classification, providing evidence of the role that this novel spectrometric technique can play for fundamental and applied agro-industrial themes. Copyright (C) 2010 John Wiley & Sons, Ltd.