Identification of raffinose family oligosaccharides in processed Rehmannia glutinosa Libosch using matrix‐assisted laser desorption/ionization mass spectrometry image combined with machine learning

Rationale Currently, research on oligosaccharides primarily focuses on the physiological activity and function, with a few studies elaborating on the spatial distribution characterization and variation in the processing of Rehmannia glutinosa Libosch. Thus, imaging the spatial distributions and dynamic changes in oligosaccharides during the steaming process is significant for characterizing the metabolic networks of R. glutinosa . It will be beneficial to characterize the impact of steaming on the active ingredients and distribution patterns in different parts of the plant. Methods A highly sensitive matrix‐assisted laser desorption/ionization mass spectrometry image (MALDI‐MSI) method was used to visualize the spatial distribution of oligosaccharides in processed R. glutinosa . Furthermore, machine learning was used to distinguish the processed R. glutinosa samples obtained under different steaming conditions. Results Imaging results showed that the oligosaccharides in the fresh R. glutinosa were mainly distributed in the cortex and xylem. As steaming progressed, the tetra‐ and pentasaccharides were hydrolyzed and diffused gradually into the tissue section. MALDI‐MS profiling combined with machine learning was used to identify the processed R. glutinosa samples accurately at different steaming intervals. Eight algorithms were used to build classification machine learning models, which were evaluated for accuracy, precision, recall, and F1 score. The linear discriminant analysis and random forest models performed the best, with prediction accuracies of 0.98 and 0.97, respectively, and thus can be considered for identifying the steaming durations of R. glutinosa . Conclusions MALDI‐MSI combined with machine learning can be used to visualize the distribution of oligosaccharides and identify the processed samples after steaming for different durations. This can enhance our understanding of the metabolic changes that occur during the steaming process of R. glutinosa ; meanwhile, it is expected to provide a theoretical reference for the standardization and modernization of processing in the field of medicinal plants.