Department of Civil, Environmental, Land, Building Engineering and Chemistry (DICATECh), Polytechnic University of Bari, Via Orabona, 4, I-70125 Bari, Italy.
Istituto Superiore di Sanità, Core Facilities Istituto Superiore Di Sanità, Viale Regina Elena, 299, I-00161 Roma, Italy.
Molecules. 2024 Sep 19;29(18):4441. doi: 10.3390/molecules29184441.
Non-targeted NMR is widely accepted as a powerful and robust analytical tool for food control. Nevertheless, standardized procedures based on validated methods are still needed when a non-targeted approach is adopted. Interlaboratory comparisons carried out in recent years have demonstrated the statistical equivalence of spectra generated by different instruments when the sample was prepared by the same operator. The present study focused on assessing the reproducibility of NMR spectra of the same matrix when different operators performed individually both the sample preparation and the measurements using their spectrometer. For this purpose, two independent laboratories prepared 63 tomato samples according to a previously optimized procedure and recorded the corresponding 1D H NMR spectra. A classification model was built using the spectroscopic fingerprint data delivered by the two laboratories to assess the geographical origin of the tomato samples. The performance of the optimized statistical model was satisfactory, with a 97.62% correct sample classification rate. The results of this work support the suitability of NMR techniques in food control routines even when samples are prepared by different operators by using their equipment in independent laboratories.
非靶向 NMR 广泛应用于食品控制，被认为是一种强大而稳健的分析工具。然而，当采用非靶向方法时，仍需要基于经过验证的方法制定标准化程序。近年来进行的实验室间比较证明，当由同一操作人员制备样品时，不同仪器生成的光谱在统计学上是等效的。本研究重点评估了当不同操作人员分别使用各自的仪器进行样品制备和测量时，同一基质的 NMR 光谱的重现性。为此，两个独立的实验室根据先前优化的程序制备了 63 个番茄样品，并记录了相应的 1D H NMR 光谱。使用两个实验室提供的光谱指纹数据构建了分类模型，以评估番茄样品的地理来源。优化统计模型的性能令人满意，样品分类准确率为 97.62%。这项工作的结果支持了 NMR 技术在食品控制常规中的适用性，即使在不同操作人员使用其在独立实验室中的设备进行样品制备的情况下也是如此。
