Harnly James
Methods and Applications Food Composition Lab, Beltsville Human Nutrition Research Center, Agricultural Research Service, U.S. Department of Agriculture, Beltsville, MD, United States.
Front Pharmacol. 2025 Mar 27;16:1504230. doi: 10.3389/fphar.2025.1504230. eCollection 2025.
One-class modeling is a supervised multivariate botanical identification method based on principal component analysis (PCA) that constructs a model based only on the characteristics of the reference samples and uses the Q statistic as a combined metric. Test samples are judged to be similar (authentic) if their combined metric falls within the model limits or different (adulterated or contaminated) if the metric falls outside the model limits. This review initially considers three major factors affecting identification: the number of variables (univariate versus multivariate), the number of classes (one-class versus multi-class), and the type of analysis (quantitative versus qualitative). Multivariate analysis is commonly used for identification, providing a broader coverage of the identity specifications of the samples. With a combined metric, multivariate methods are analogous to univariate methods. One-class modeling and multi-class modeling employ different approaches for identification with one-class modeling being more flexible. While most methods to date have had a quantitative basis, qualitative methods are possible. This review focuses on multivariate, one-class modeling based on PCA. Examples are presented for the application of one-class modeling to identification of American ginseng (), , Black Cohosh (), and Maca (). These examples demonstrate the utility and flexibility of one-class modeling.
单类建模是一种基于主成分分析（PCA）的有监督多变量植物鉴定方法，该方法仅基于参考样本的特征构建模型，并使用Q统计量作为综合度量。如果测试样本的综合度量落在模型范围内，则判断其为相似（真实）样本；如果该度量超出模型范围，则判断其为不同（掺假或污染）样本。本综述首先考虑影响鉴定的三个主要因素：变量数量（单变量与多变量）、类别数量（单类与多类）以及分析类型（定量与定性）。多变量分析常用于鉴定，能更广泛地涵盖样本的身份特征。通过综合度量，多变量方法类似于单变量方法。单类建模和多类建模采用不同的鉴定方法，单类建模更灵活。虽然迄今为止大多数方法都有定量基础，但定性方法也是可行的。本综述重点关注基于PCA的多变量单类建模。文中给出了单类建模在西洋参、黑升麻和玛咖鉴定中的应用实例。这些实例展示了单类建模的实用性和灵活性。
