植物标准物质的差异:流式进样质谱法分析裸子植物的相似性

James Harnly, Roy Upton
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摘要

背景:植物学参考材料(BRMs)一般会考虑物种、栽培品种、收获年份和地点,这些因素会导致化学成分的变化,而使用化学计量学方法可能会导致统计学上的显著差异:使用化学计量学方法和选定的预处理方法,比较 5 种 Actaea 根 BRMs、4 种草本来源的 A. racemosa 根 BRMs 和 A. racemosa BRMS 以及商业根和补充剂的化学成分:采用流动注射质谱法(FIMS)、主成分分析法(PCA)和因子多元方差分析法(mANOVA)对样品进行分析:结果表明:3 个属(白花蛇舌草属、三七属和银杏属)、5 种白花蛇舌草(A. racemosa、A. cimicifuga、A. dahurica、A. pachypoda 和 A. rubra)根 BRMs、4 种草本来源的白花蛇舌草根 BRMs 以及白花蛇舌草 BRMS 和商品根及补充剂之间的成分差异具有统计学意义(p = 0.05)。结果发现,6% 的 BRM 变量在数量上保持不变,并减少了 4 种来源的根 BRM 之间的成分差异。技术重复、预处理方法、变量选择和置信区间的选择等方面的变化影响了A. racemosa 和其他 Actaea BRMs 的成分重叠。在测试的预处理方案中,灵敏度在 94% 到 97% 之间,特异性在 21% 到 89% 之间:结论:环境、遗传和化学计量因素会影响物种和真实植物参考材料之间的鉴别:亮点:通过类比软独立建模得出的频率分布图为了解实验因素的影响提供了极好的方法。
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Variation in Botanical Reference Materials: Similarity of Actaea Racemosa Analyzed by Flow Injection Mass Spectrometry.

Background: Botanical reference materials (BRMs) generally account for the species, cultivar, and year and location of harvest that result in variability in the chemical composition that may lead to statistically significant differences using chemometric methods.

Objective: To compare the chemical composition of five species of Actaea root BRMs, four herbal sources of A. racemosa root BRMs, and A. racemosa BRMS, and commercial roots and supplements using chemometric methods and selected pre-processing approaches.

Method: Samples were analyzed by flow injection mass spectrometry (FIMS), principal component analysis (PCA), and factorial multivariate analysis of variance (mANOVA).

Results: Statistically significant (P = 0.05) compositional differences were found between three genera (Actaea, Panax, and Ginkgo), five species of Actaea (A. racemosa, A. cimicifuga, A. dahurica, A. pachypoda, and A. rubra) root BRMs, four herbal sources of A. racemosa root BRMs, and A. racemosa BRMS and commercial roots and supplements. The variability of 6% of the BRM variables was found to be quantitatively conserved and reduced the compositional differences between the four sources of root BRMs. Compositional overlap of A. racemosa and other Actaea BRMs was influenced by variation in technical repeats, pre-processing methods, selection of variables, and selection of confidence limits. Sensitivity ranged from 94 to 97% and specificity ranged from 21 to 89% for the pre-processing protocols tested.

Conclusions: Environmental, genetic, and chemometric factors can influence discrimination between species and authentic botanical reference materials.

Highlights: Frequency distribution plots derived from soft independent modeling of class analogy provide excellent means for understanding the impact of experimental factors.

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