In general, data fusion can improve the classification performance of the model, but little attention is paid to the influence of the data fusion on the spatial distribution of the modeling samples. In this paper, the effect of data fusion on sample spatial distribution was studied through integrating NIR data and UHPLC-HRMS data for sulfur-fumigated Chinese herb medicine. Twelve samples collected from four different geographical origins were sulfur fumigated in the lab, and then metabolomics analysis was conducted using NIR and UHPLC-LTQ-Orbitrap mass spectrometer. First of all, the discriminating power of each technique was respectively examined based on PCA analysis. Secondly, combining NIR and UHPLC-HRMS data sets together with or without variable selection was parallelly compared. The results demonstrated that the discriminable ability was remarkably improved after data fusion, indicating data fusion could visualize variable selection and enhance group separation. Samples in the margin between two classes of samples may increase the experience error but has positive effect on the separation direction. Besides, an interesting feature extraction could obtain better discriminable effect than common data fusion. This study firstly provided a new path to employ a comprehensive analytical approach for discriminating SF Chinese herb medicines to simultaneously benefit from the advantages of several technologies.

通常，数据融合可以提高模型的分类性能，但是很少关注数据融合对建模样本空间分布的影响。本文结合硫熏蒸中草药的近红外光谱数据和超高效液相色谱-HRMS数据，研究了数据融合对样品空间分布的影响。在实验室中对从四个不同地理来源收集的十二个样品进行了硫熏蒸，然后使用NIR和UHPLC-LTQ-Orbitrap质谱仪进行了代谢组学分析。首先，基于PCA分析分别检查了每种技术的辨别力。其次，将NIR和UHPLC-HRMS数据集组合在一起（有或没有变量选择）进行了并行比较。结果表明，数据融合后可分辨能力得到显着提高，表明数据融合可以可视化变量选择并增强组分离。两类样本之间的空白处的样本可能会增加体验误差，但会对分离方向产生积极影响。此外，与普通数据融合相比，有趣的特征提取可以获得更好的可分辨效果。这项研究首先提供了一条新途径，可以采用一种综合分析方法来区分SF中草药，从而同时受益于多种技术的优势。两类样本之间的空白处的样本可能会增加体验误差，但会对分离方向产生积极影响。此外，与普通数据融合相比，有趣的特征提取可以获得更好的可分辨效果。这项研究首先提供了一条新途径，可以采用一种综合分析方法来区分SF中草药，从而同时受益于多种技术的优势。两类样本之间的空白处的样本可能会增加体验误差，但会对分离方向产生积极影响。此外，与普通数据融合相比，有趣的特征提取可以获得更好的可分辨效果。这项研究首先提供了一条新途径，可以采用一种综合分析方法来区分SF中草药，从而同时受益于多种技术的优势。