This study aimed to investigate the composition and differences in phytochemicals between the phloem and xylem of Rehmanniae Radix (RR). The metabolic profiles of two tissues were comprehensively characterized using untargeted metabolomics, and the relative abundance of metabolites was analyzed. Subsequently, the primary differential components, identified as glycosides, were quantified in two tissues using ultra-high-performance liquid chromatography (UHPLC). Using the untargeted metabolomic approach, 3854 metabolites were identified in two tissues, categorized into 21 classes including glycolipids, heterocyclic compounds, terpenoids, phenolic acids, and amino acids and derivatives. Principal component analysis (PCA) revealed significant differences in the metabolite profiles between two tissues of RR, and 1279 different metabolites were screened, of which 1098 were up-regulated and 181 were down-regulated. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that these differential metabolites were involved in 72 metabolic pathways, with the majority being associated with plant metabolism. Quantification analysis of glycosides resulted in the identification of 5 iridoid glycosides and 6 phenylethanoid glycosides in two tissues of RR, with the total glycosides content found to be higher in the phloem. The key components differentiating the quality of the phloem and xylem were the iridoid glycosides catalpol and the phenylethanoid glycosides acteoside and echinacoside. Collectively, these findings elucidate the similarities and differences in chemical constituents between the phloem and xylem of RR, thereby providing the scientific foundation for its quality evaluation and the selection of superior cultivars.

IntroductionThe geo-authenticity of medicinal plants, exemplified by Rehmannia glutinosa, is largely attributed to environmentally driven variation in bioactive compounds; yet, the underlying systemic molecular mechanisms remain elusive. MethodsThis study employed an integrated approach combining targeted quantitative analysis, transcriptomics, and metabolomics to dissect how geographical origin shapes the medicinal quality of Rehmannia glutinosa, using two cultivars ('Wen 85-5' and 'Jin Jiu') sourced from two distinct production regions (Henan and Hebei).ResultsTargeted quantification confirmed origin-specific accumulation patterns of key bioactive compounds, most notably a significantly higher acteoside content in roots from the Henan origin. Multi-omics profiling revealed a conserved core molecular response to geographical origin, involving 894 common differentially expressed genes and 443 common differentially abundant metabolites enriched in hormone signaling, primary metabolism, and specialized biosynthesis pathways. While the response amplitude was genotype-dependent (stronger in 'Wen 85-5'), its fundamental architecture was consistent. Crucially, we identified a coordinated upregulation of the entire acteoside biosynthetic network in Henan-sourced roots. This was evidenced by the concerted induction of key structural genes (PAL, C4H, 4CL, TyDC, UGT) across both phenylpropanoid and tyrosine-derived branches, coupled with elevated levels of pathway intermediates.ConclusionThis study elucidates that the geo-authenticity of Rehmannia glutinosa arises from an origin-triggered, systemic reconfiguration of interconnected transcriptional and metabolic networks. The identified core regulatory network provides a mechanistic framework for understanding quality formation and paves the way for molecular-assisted cultivation and breeding strategies.

In this study, high-throughput sequencing technology was employed to conduct transcriptome sequencing of the nodular and non-nodular tissues of Rehmannia glutinosa (R. glutinosa). Employing LC-MS technology, we conducted qualitative and quantitative analysis of plant hormones, as well as investigations into their synthetic accumulation patterns. Transcriptome-metabolome correlation analysis provided preliminary insights into the mechanisms underlying phenotypic differences between the two tissues. Transcriptome analysis showed that 4583 differentially expressed genes (DEGs) were identified. Up-regulated genes were primarily enriched in cell division, microtubule motility terms, and starch/sucrose metabolism pathways, while down-regulated genes were mainly enriched in substance transport terms and diterpenoid biosynthesis pathways. Targeted Metabolomic analysis showed that the accumulation of plant hormones was tissue-specific, with Abscisic acid (ABA) significantly accumulating in nodular characteristics, while Auxin, Cytokinin (CK) and Gibberellin (GA) significantly accumulating in non-nodular tissue. The formation of nodular characteristics in R. glutinosa was regulated by the interplay of multiple hormones and gene expression regulation. Auxin (Indole) and CK (cZ9G) exhibited synergistic effects, while ABA and GA demonstrated antagonistic interactions, jointly regulating nodular characteristics development. This study provides a theoretical basis for the selection of R. glutinosa germplasm resources and the evaluation of the geo-authentic properties of Huai R. glutinosa.

To analyze the difference of overall metabolites in cultivated and wild Rehmannia glutinosa,this study used cultivated and wild R.glutinosa from different locations as research objects.Their metabolites were detected using liquid chromatography-mass spectrometry(LC-MS),and multivariate statistical analysis was adopted to analyze metabolites.Differential metabolites were identified,and differential metabolic pathways were determined based on the Kyoto Encyclopedia of Genes and Genomes(KEGG)database.The results showcased that 1 802 metabolites were detected,and the metabolites of cultivated and wild R.glutinosa were similar,including 13 kinds of compounds such as terpenoids,phenolic acids,lipids,and alkaloids.Overall,the relative content of metabolites of wild R.glutinosa was higher than that of cultivated R.glutinosa.There were 665 differential metabolites between cultivated and wild R.glutinosa.A total of 157 differential metabolites were up-regulated,and 508 differential metabolites were down-regulated.According to the KEGG database,93 metabolites with significant differences were annotated,with phenolic acids representing the highest proportion.There were a total of 55 metabolic pathways corresponding to differential metabolites,which were divided into three categories:metabolism,genetic information processing,and environmental information processing.Significantly different pathways included flavonoid biosynthesis(ko00941),phenylpropane biosynthesis(ko00940),and pyrimidine metabolism(ko00240),all of which were associated with plant metabolism.The study found that the metabolite species of wild and cultivated R.glutinosa were consistent,whereas the overall metabolite content of wild R.glutinosa was higher than that of cultivated R.glutinosa,and the difference in their pharmacological effects remained to be further investigated.

Rehmannia chingii (2n = 2x = 28) is an important folk medicinal plant with high therapeutic value, particularly due to its richness in iridoid glycosides. However, research on its evolution and gene functional identification has been hindered by the lack of a high-quality genome. Here, we present the 1.169 Gb telomere-to-telomere (T2T) genome sequence of R. chingii. Phylogenetic analysis confirms that Rehmannia belongs to the Orobanchaceae family. We find that structural genes of the 2-C-methyl-d-erythritol-4-phosphate (MEP) pathway and the iridoid pathway are predominantly expressed in R. chingii leaves. Further analyses reveal a cytochrome P450 gene cluster localized on chromosome 8, and identify RcCYP72H7 within this cluster as an aucubin epoxidase, capable of catalyzing aucubin epoxidation to form catalpol. The genome offers valuable resources for studying iridoid glycoside biosynthesis and the evolutionary history of Rehmannia, and will help to faciliate genetic improvement of R. chingii for pharmaceutical and health-related applications.

The classic formula Yiguanjian consists of 6 herbs: Rehmannia glutinosa Libosch, Angelica sinensis (Oliv.) Diels, Glehnia littoralis Fr. Schmindt ex Miq, Lyciumbarbarum L, Ophiopogon japonicus (L. f) Ker-Gawl, Melia toosendan Sieb. et Zucc are effective in nourishing the liver and kidneys and de-stressing the liver and Qi. Infrared spectroscopy has the advantage of being fast and non-destructive. Infrared spectroscopy provides complete information from different batches of Yiguanjian benchmark samples. The infrared spectra of the samples were collected using a Fourier transform infrared spectrometer. The raw spectra were pre-processed to obtain relative peak heights and to attribute shared peaks. The infrared spectral data were evaluated using HCA, PCA and OPLS-DA. The results showed that the sugar skeleton stretching vibration absorption peaks in the 868, 822 and 779 cm(-1) bands of the 15 batches of Yiguanjian benchmark samples were mostly contributed by Lyciumbarbarum L and a few at the 815 cm 1 band were contributed by Ophiopogon japonicus (L. f) Ker-Gawl. The single decoction of Rehmannia glutinosa Libosch at 1 148 cm(-1) band, the single decoction of Glehnia littoralis Fr. Schmindt ex Miq at 1 158, 1 082, 1 019 cm(-1) band and the single decoction of Angelica sinensis (Oily.) Diels at 993 cm(-1) band all contributed to the glycosidic composition. The absorption peak of soluble lipid glycosides in the 1 746 cm(-1) band of the single decoction of Melia toosendan Sieb. et Zucc is obvious, but the absorption peak is not obvious in Yiguanjian benchmark samples. It may have changed chemically during decoction. The HCA results showed that S1, S2, S15 clustered into one group, S9, S11, S12, S13, S14 clustered into one group, S3, S4, S5, S6, S7, S8, S10 clustered into one group when the distance between groups=10. Indicating that there was some variation in the internal quality of different batches of consistent decoctions. It indicates some variation in the internal quality of the 15 batches of Yiguanjian benchmark samples. The PCA classification results were in general agreement with the HCA results, and the combined principal component scores were calculated for different batches, with batch No. 3 Yiguanjian being the best quality decoction and batch No. 1 being the worst. Analysis of the load scatter plots yielded 1 104, 1 142, 1 412, 1 260, and 868 cm(-1) band peaks contributing more to principal component 1; 777, 2936, 923, 1 721, 818, and 637 cm(-1) band peaks contributing more to principal component 2. OPLS-DA results are consistent with HCA and PCA results. Using VIP>1 as a criterion, seven bands that led to differences between samples were screened, 777, 637, 923, 2 936, 1 260, 1 412 and 1 630 cm(-1), respectively, and the results were generally consistent with the importance weighting variables looked for in the PCA loading diagram. The established method of infrared fingerprinting of Yiguanjian is simple and accurate, which can be used for the rapid identification and analysis of the classical formulae and provide a reference for the quality control and evaluation of the classical formulae of Yiguanjian.

The continuous improvement of deep learning technology has led to its deeper application in related fields, especially in the detection of antimicrobial resistance in the medical field. In drug resistance detection, the CNN-ATT-TChan model based on the fusion of CNN algorithm and attention mechanism can classify and organize a large amount of antimicrobial resistance data, achieving standardized processing. Based on mature chemical analysis and testing methods, drug resistance test data was obtained, and the training duration and classification accuracy F of the model were discussed in combination with the test data. At the same time, based on relevant research literature, the changes in ROC curves and AUC values between different models were compared. The results showed that the CNN algorithm using fusion attention mechanism can improve the training time of the model and also improve the classification accuracy of the model. Therefore, the application of CNN-ATT-TChan model combined with attention mechanism in the detection of antimicrobial resistance provides more support for the development of antimicrobial resistance testing.

Objective To establish a qualitative discrimination model for the type and degree of processing of Niuxi(Achyranthes bidentata,AB)using infrared spectroscopy and machine learning algorithms.Methods The infrared spectra of AB with different processing types and degree was collected,and various machine learning algorithms,including back propagation neural network(BPNN),genetic algorithm-optimized BP neural network(GA-BP),random forest(RF),radial basis function network(RBFN),and convolutional neural networks(CNN)were used to establish a qualitative discrimination model for the type and degree of processed products of AB.The near-infrared spectra(NIRS)of AB with different processing types and degree was collected,and TQ Analyst software was used to establish a qualitative analysis model for the type and degree of processed products of AB.Results The results of the machine learning algorithm models showed that the CNN discriminative model was superior,the BPNN,RF and RBFN had similar performance,and the GA-BP model had relatively poor performance.The three NIRS qualitative models had validation accuracies of 100％,indicating that they could accurately predict the type and degree of processed products of AB.Conclusion The qualitative analysis model developed in this study by infrared spectroscopy can be used as a means to identify the type and degree of processed products of AB.It also provides a rapid and non-destructive means of testing and a reliable method for data analysis,with view to providing a new method of reference for the accurate identification of the type and degree of preparation of Chinese herbal processed products.

The Rehmannia glutinosa ‘Wen 85-5’ cultivar was used to analyze the effects of spraying salicylic acid（SA） on the leaf surface on acteoside content and molecular regulation characteristics. The plants were grown for 180 days, then sprayed with SA（100 μmol/L）. The leaves and tuberous roots of R. glutinosa were collected at 0, 1, 3, and 6 h after treatment to determine the content of acteoside. Transcriptome sequencing of the tuberous roots at different times after SA treatment was also performed. Results showed that, compared with the controls, acteoside content in the leaves and tuberous roots increased by 11.2%-19.3%,and0.9-1.4 times, respectively, after SA treatment. Transcriptome analysis showed that most differentially expressed genes（DEGs） were obtained 3 h after SA treatment, with more down-regulated genes than up-regulated genes. Most DEGs were significantly enriched in the phenylpropanoid biosynthesis pathway, while several catalytic enzyme genes of the acteoside synthesis pathway, such as ALDH, UGT, and PPO, were up-regulated in the tuberous roots. Many AP2-EREBP, WRKY, and MYB transcription factor genes were differentially expressed after SA treatment. This study provides theoretical support for the use of elicitors to treat R. glutinosa plants in the field to increase acteoside content.

在仪器分析课程中设计混合教学模式,包含前端分析、课前线上学习、线上线下联结、线下课堂教学、课后指导、学习评价.以"气相色谱分析法"为例,通过全面分析学情、梳理教学内容、设计线上线下教学过程、突出过程性学习评价,充分探究混合教学模式在仪器分析课程中的实践运用.通过教学反思,探讨混合教学模式的应用优势及存在问题.

Engineering anthocyanin biosynthesis in herbs could provide health-promoting foods for improving human health. Rehmannia glutinosa is a popular medicinal herb in Asia, and was a health food for the emperors of the Han Dynasty (59 B.C.). In this study, we revealed the differences in anthocyanin composition and content between three Rehmannia species. On the 250, 235 and 206 identified MYBs in the respective species, six could regulate anthocyanin biosynthesis by activating the ANTHOCYANIDIN SYNTHASE (ANS) gene expression. Permanent overexpression of the Rehmannia MYB genes in tobacco strongly promoted anthocyanin content and expression levels of NtANS and other genes. A red appearance of leaves and tuberous/roots was observed, and the total anthocyanin content and the cyanidin-3-O-glucoside content were significantly higher in the lines overexpressing RgMYB41, RgMYB42, and RgMYB43 from R. glutinosa, as well as RcMYB1 and RcMYB3 in R. chingii and RhMYB1 from R. henryi plants. Knocking out of RcMYB3 by CRISPR/Cas9 gene editing resulted in the discoloration of the R. chingii corolla lobes, and decreased the content of anthocyanin. R. glutinosa overexpressing RcMYB3 displayed a distinct purple color in the whole plants, and the antioxidant activity of the transgenic plants was significantly enhanced compared to WT. These results indicate that Rehmannia MYBs can be used to engineer anthocyanin biosynthesis in herbs to improve their additional value, such as increased antioxidant contents.

目的 建立香附饮片、清炒香附、香附炭的HPLC指纹图谱,结合化学模式识别筛选差异标志物,并测定6种主要成分的含量,为进一步完善香附质量标准提供参考.方法 采用《中药色谱指纹图谱相似度评价系统(2012版)》建立21批香附样品的HPLC指纹图谱,进行相似度评价,确定共有峰个数;采用SIMCA14.1软件进行层次聚类分析(hierarchical cluster analysis,HCA)、主成分分析(principal component analysis,PCA)、正交偏最小二乘-判别分析(orthogonal partial least squares-discriminant analysis,OPLS-DA),以变量重要性投影(variable importance in projection,VIP)＞1 为标准筛选出差异标志物;测定5-羟基甲基糠醛(5-hydroxymethylfurfural,5-HMF)、对香豆酸、阿魏酸、木犀草素、香附烯酮、α-香附酮的含量.结果 21批HPLC指纹图谱的相似度均不小于0.934,共标定23个共有峰,指认3、10、11、17、21、23号峰分别为5-HMF、对香豆酸、阿魏酸、木犀草素、香附烯酮、α-香附酮;PCA结果、OPLS-DA结果与HCA结果一致,均可将21批香附样品分为3类;通过VIP筛选出2、23(α-香附酮)、17(木犀草素)、10(对香豆酸)、11(阿魏酸)号峰为导致样品差异的主要标志色谱峰;5-HMF的含量在香附炭中最高.对香豆酸、阿魏酸的含量在香附饮片、清炒香附、香附炭中逐渐增加.木犀草素在清炒香附中含量最高.α-香附酮含量经炒后略有增加.香附烯酮含量在香附饮片、清炒香附、香附炭中含量逐渐减少.结论 筛选出未知成分2号峰与已知成分α-香附酮、木犀草素、对香豆酸、阿魏酸为差异标志物;所建立的清炒香附的HPLC指纹图谱存在一定差异,且HPLC指纹图谱与含量测定方法操作简单、准确,能够为清炒香附药效物质基础研究提供实验依据,可为进一步完善香附质量标准提供参考.

为探讨盾叶薯蓣在低磷胁迫下的生理变化、甾体皂苷类成分代谢及基因表达的响应特征,本研究选取河南南阳产盾叶薯蓣进行模拟低磷胁迫实验,在不同时期对根际基质中的磷含量(全磷、速效磷、磷酸铝盐、磷酸铁盐、磷酸钙盐)和土壤酸性磷酸酶(soil acid phosphatase,S-ACP)活性、植株根系发育特征(总根长、总投影面积、总表面积),各部位过氧化物酶(peroxidase,POD)、超氧化物歧化酶(superoxide dismutase,SOD)活性及甾体皂苷类成分含量等指标进行分析,确定盾叶薯蓣响应低磷胁迫的关键时期,并利用RNA-Seq测序对关键时期盾叶薯蓣根茎、叶片、地上茎3个部位中的基因表达特征进行分析.研究发现低磷胁迫处理后盾叶薯蓣根际基质中易吸收态磷含量显著降低,其抗氧化酶(POD、SOD)与酸性磷酸酶活性均显著升高,根系发育受阻;低磷胁迫可明显影响盾叶薯蓣中甾体皂苷的合成与积累,且不同部位响应特征不同;胁迫初期为盾叶薯蓣响应低磷胁迫的关键时期;响应低磷胁迫关键时期的盾叶薯蓣基因表达存在明显的组织特异性,对三个处理组不同部位基因表达量与代谢通路进行分析,分别从盾叶薯蓣根茎、叶片、地上茎3个部位中挖掘到239、211、237个差异基因,涉及萜类骨架、有机酸、肌醇的生物合成等多个代谢通路.上述研究结果说明盾叶薯蓣通过改变基因表达水平对表型性状和生理代谢过程进行调节来响应低磷胁迫,本研究为研究盾叶薯蓣响应低磷胁迫的分子机制提供理论依据.

脂肪酸囊泡具有封闭双层膜结构,可包埋活性分子.以油酸(OA)为模型脂肪酸,依据pH滴定曲线和目视观察法划分胶束、囊泡、乳液或油水分相等相区,确定了OA在氢氧化胆碱(ChOH)中囊泡化的pH窗口为7.5～9.1,用动态光散射、相差显微镜结合透射电子显微镜技术进一步表征了OA/ChOH囊泡的尺寸和形貌,呈现尺度多分散性.为进一步改善OA/ChOH囊泡形成pH范围窄且远离人体生理条件的缺陷,加入阴离子表面活性剂十二烷基硫酸钠(SDS),结果表明SDS摩尔分数(x)为0.1时即可将囊泡化pH窗口向酸性迁移至生理pH条件附近;随x增加,复合囊泡pH窗口呈现向酸性拓宽的趋势,甚至可达到强酸性条件.复合囊泡形成的主要原因是SDS与OA分子间的氢键作用,在较低pH范围内可代替"酸-皂"二聚体间的氢键作用.复合囊泡作为包埋体时,具有较高的包封率和载药量以及良好的缓释效果.

以"酸碱滴定分析法"为例,依托自建药学专业SPOC课程资源,构建和实践了包含前端分析、教学过程和考核评价的线上线下混合教学模式.通过全面分析教学内容、教学目标、学情和学习环境等,设计了线上课前预习、线下课堂教学、线上课后拓展等3个步骤相衔接的教学过程,建立了线上线下相结合、突出过程性评价的综合考核方式.通过反思整个教学过程,对线上线下混合教学模式的主要优势和问题进行了讨论.

制药工程是一个化学、药学和工程学交叉的工科类专业,药物分析是制药工程专业的重要专业课.本文以药物分析课程中的教学内容——"砷盐的检查"为例,以药物分析课程中的教学内容——"砷盐的检查"为例,探索课堂派、微信公众号等移动互联网技术在制药工程专业药物分析教学中的应用.利用"课堂派"进行课堂教学,包括考勤、授课、互动、测验和布置作业,课堂派可以让整个教学过程变的信息化、可追溯化;利用微信公众号对教学内容进行总结,如发布精选笔记、练习题和相关的拓展知识,课堂派和微信公众号等移动互联网技术不仅增加了课堂容量,还可以帮助学生们利用碎片化的时间,增加课后学习时间,提高学习效率.但在使用课堂派和微信公众号进行药物分析教学的过程中也发现一些问题,因此,在教学过程中要合理、适度地使用移动互联网技术.

目的:探讨盾叶薯蓣须根在低磷胁迫下的代谢产物及基因表达特征.方法:设置重度胁迫组、中度胁迫组与正常组模拟盾叶薯蓣低磷胁迫实验,在胁迫初期采取盾叶薯蓣须根,分别利用气相色谱-质谱联用技术(GC-MS)衍生化及RNA-seq技术对其代谢产物和转录组特征进行分析,通过对不同处理代谢产物的多元统计分析、差异表达基因的功能分析及数据挖掘,筛选低磷胁迫下盾叶薯蓣须根产生的代谢标志物,分析差异表达基因的代谢通路特征.结果:从盾叶薯蓣须根中共检测到116个GC-MS代谢产物,不同低磷处理下盾叶薯蓣须根的代谢特征存在明显差异,利用正交偏最小二乘判别分析(OPLS-DA)模型从不同处理须根的代谢产物中筛选到6个差异代谢物,主要为糖类、醇类等成分,这些物质可能是盾叶薯蓣须根响应低磷胁迫的代谢标志物;重度胁迫组与正常组中筛选到的差异基因主要富集到过氧化物酶途径、磷酸盐和次磷酸盐代谢途径,重度胁迫组与中度胁迫组中筛选到的差异基因主要富集到谷胱甘肽代谢途径及磷酸戊糖途径;从须根中筛选出177个潜在响应低磷胁迫的差异基因,涉及萜类骨架、肌醇生物合成等多个途径,这与盾叶薯蓣须根部位响应低磷胁迫的代谢差异物多为糖类与肌醇等物质相吻合.结论:低磷胁迫下盾叶薯蓣须根部位的代谢产物及基因表达均发生了相应的应答,差异代谢物与差异表达基因具有密切的关系,该研究为盾叶薯蓣响应低磷胁迫的分子机制提供理论依据.

探讨桑叶生物碱(mulberry leaf alkaloids,MLA)对酒精性肝损伤小鼠的改善作用.建立酒精性肝损伤小鼠模型,以MLA(40、80、160 mg/kg·day)干预4周,计算肝脏指数,检测血清甘油三酯(TG)、总胆固醇(TC)、谷丙转氨酶(ALT)、谷草转氨酶(AST)和肝脏中过氧化氢酶(CAT)、谷胱甘肽过氧化物酶(GSH-Px)、总超氧化物歧化酶(SOD)、丙二醛(MDA)、肿瘤坏死因子α(TNF-α)、白细胞介素1β(IL-1β)、白细胞介素6(IL-6)的含量.与模型组相比,MLA中剂量组小鼠的肝脏指数、血清TG、TC、ALT、AST和肝脏MDA、IL-1β、IL-6、TNF-α水平分别降低11.18％、22.78％、19.19％、28.08％、16.16％、25.07％、23.51％、18.61％、11.78％,肝脏SOD、CAT、GSH-Px活力分别提高27.47％、15.36％、27.83％;MLA高剂量组小鼠的肝脏指数、血清TG、TC、ALT、AST和肝脏MDA、IL-1β、IL-6、TNF-α水平分别降低15.17％、32.65％、23.16％、30.58％、16.41％、31.97％、27.19％、25.41％、29.59％,肝脏SOD、CAT、GSH-Px活力分别提高38.38％、19.09％、31.09％;MLA中、高剂量组肝脏组织结构损伤明显改善.MLA可以改善小鼠酒精性肝损伤,其作用机制可能与改善肝脏氧化应激和抑制炎症反应有关.

目的 建立不同产地牛膝药材的红外指纹图谱,并进行多元统计分析.方法 采用Spectrum for Window 3.02和OMNIC 9.2软件建立61批牛膝药材样品的红外指纹图谱;以红外指纹图谱共有峰的相对峰高为变量,采用Excel 2016软件进行正态分布分析,采用SPSS 22.0软件进行聚类分析和主成分分析并计算综合得分,采用SIMCA 14.1软件进行正交偏最小二乘法-判别分析,以变量重要性投影(VIP)>1为标准,筛选影响牛膝药材成分质量的标志性波数.结果 61批牛膝药材样品红外光谱图的相关系数为0.9672～0.9977;共有13个共有峰.正态分布分析结果显示,河南产与河北产牛膝药材共有峰相对峰高的正态分布曲线未有交叉,河南产与内蒙古产牛膝药材的正态分布曲线存在交叉.聚类分析结果显示,当组间距离为15时,61批牛膝药材样品可聚为3类,其中N1～N12聚为一类,N13～N45聚为一类,N46～N61聚为一类.主成分分析结果显示,前3个主成分的累计方差贡献率为91.121％;河南省焦作市驾步村产牛膝药材(编号N40)的综合评分最高(2.39),河北省安国市新安村产牛膝(编号N4)的综合评分最低(-2.89).正交偏最小二乘法-判别分析结果显示,61批牛膝药材样品可分为3类,其中N1～N12为一类,N13～N28为一类,N29～N61为一类;共筛选出7个影响药材样品质量的标志性波数,其VIP值从大到小对应的波数依次为1059、927、2933、813、1732、1128、3367 cm-1,其中1732 cm-1处为皂苷类成分的特征吸收峰,1059、1128、927 cm-1处为糖苷类成分的特征吸收峰.结论 红外指纹图谱结合正态分布分析、聚类分析、主成分分析和正交偏最小二乘法-判别分析可用于鉴别不同产地牛膝药材.