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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. [ABSTRACT FROM AUTHOR]

We conducted an 8-week feeding trial to investigate the effect of mixed functional oligosaccharides (chitosan oligosaccharide, fructooligosaccharide, and xylooligosaccharide) extracted from wheat straw on the growth, feeding, physiology, histology, muscle texture, and gut microbiota of Micropterus salmoides. Six diets were formulated by incrementally adding mixed functional oligosaccharides (0.1, 0.5, 1.0, 1.5, and 2.0 mg/kg) to the control diet. 30 individuals with initial body weight of 25.1 ± 3.5 g were randomly allocated to 6 triplicate tanks and fed to apparent satiation twice daily. The fish fed 1.0 mg/kg additives displayed maximum growth, and the feed conversion ratio decreased with the increase in additives from 0 to 1.0 mg/kg (P < 0.05) but did not decline further with the addition of more than 1.0 mg/kg (P > 0.05). The villus height and width were significantly higher in the supplementation groups than in the control group, while the gut and liver structures presented abnormalities with excessive supplementation above 1.5 mg/kg. There were significant differences in muscle texture indices for M. salmoides over the fed additive gradient, and the hardness, gumminess, and chewiness were highest in the 1.0 mg/kg group. High oligosaccharide levels, such as 2.0 mg/kg, decreased the LZM level, while there were no significant differences in the SOD and MDA levels. Gut microbiome analysis revealed no significant differences in richness and diversity for groups fed the functional oligosaccharide gradient; however, the PCoA results showed that the microbial community composition changed markedly in response to different addition levels, and the 0.5 and 1.0 mg/kg supplementation groups were far apart from the lower and higher supplementation groups. The relative abundance of Proteobacteria was lower in the 0.5 and 1.0 mg/kg addition groups, while that of the phyla Fusobacteria and Firmicutes were higher in these two groups. Functional classification showed that microbes related to carbohydrate metabolism were more abundant in the 0.5 and 1.5 mg/kg groups than in the other groups. [ABSTRACT FROM AUTHOR]