PDF(Pubmed)
Abstract：
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.
METHODS: 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.
CONCLUSIONS: Frequency distribution plots derived from soft independent modeling of class analogy provide excellent means for understanding the impact of experimental factors.
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.
METHODS: 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.
CONCLUSIONS: Frequency distribution plots derived from soft independent modeling of class analogy provide excellent means for understanding the impact of experimental factors.
摘要：
背景：植物学参考材料（BRM）通常占物种的比例，栽培品种,以及收获的年份和位置会导致化学成分的变化，这可能会导致使用化学计量学方法的统计学差异。
目的：比较5种猕猴桃根BRM的化学成分，4个草药来源的A.racemosa根BRM，和A.racemosaBRMS，以及使用化学计量学方法和选定的预处理方法的商业根和补充剂。
方法：通过流动注射质谱法（FIMS）分析样品，主成分分析(PCA)，和阶乘多变量方差分析(mANOVA)。
结果：在3个属之间发现了统计学上的显着（p=0.05）组成差异（Actaea，Panax,和银杏)，5种Actaea（A.消旋体,A.cimicifuga,A.达胡丽卡，A.pachypoda，和A.rubra)根BRM，4个草药来源的A.racemosa根BRM，和A.racemosaBRMS和商业根和补充剂。发现6％的BRM变量的变异性在数量上是保守的，并减少了4种根BRM来源之间的成分差异。A.racemosa和其他ActaeaBRM的成分重叠受技术重复变化的影响，预处理方法，变量的选择，和置信区间的选择。对于测试的预处理方案,灵敏度范围为94%至97%,特异性范围为21%至89%。
结论：环境，遗传,化学计量学因素会影响物种和真正的植物参考材料之间的区别。
结论：从类类比的软独立建模得出的频率分布图为理解实验因素的影响提供了极好的手段。
目的：比较5种猕猴桃根BRM的化学成分，4个草药来源的A.racemosa根BRM，和A.racemosaBRMS，以及使用化学计量学方法和选定的预处理方法的商业根和补充剂。
方法：通过流动注射质谱法（FIMS）分析样品，主成分分析(PCA)，和阶乘多变量方差分析(mANOVA)。
结果：在3个属之间发现了统计学上的显着（p=0.05）组成差异（Actaea，Panax,和银杏)，5种Actaea（A.消旋体,A.cimicifuga,A.达胡丽卡，A.pachypoda，和A.rubra)根BRM，4个草药来源的A.racemosa根BRM，和A.racemosaBRMS和商业根和补充剂。发现6％的BRM变量的变异性在数量上是保守的，并减少了4种根BRM来源之间的成分差异。A.racemosa和其他ActaeaBRM的成分重叠受技术重复变化的影响，预处理方法，变量的选择，和置信区间的选择。对于测试的预处理方案,灵敏度范围为94%至97%,特异性范围为21%至89%。
结论：环境，遗传,化学计量学因素会影响物种和真正的植物参考材料之间的区别。
结论：从类类比的软独立建模得出的频率分布图为理解实验因素的影响提供了极好的手段。
