Rapid Identification of the Quality of Eucommiae Cortex During the Whole Process of Salt Processing Based on Chromaticity and Near-Infrared Spectroscopy.

IF 2.9 3区 生物学 Q2 BIOCHEMICAL RESEARCH METHODS
Phytochemical Analysis Pub Date : 2026-08-01 Epub Date: 2026-06-23 DOI:10.1002/pca.70079
Keer Fang, Rui Tang, Hangsha Wu, Lei Chen, Yu Ye, Bing Zhu, Yu Tian Chen, Weihong Ge, Weifeng Du
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引用次数: 0

Abstract

Background: As one of the traditional Chinese medicines, Eucommiae Cortex (EC) was often prepared with salt in the clinic to enhance its efficacy. However, its processing degree had always been judged by "experience," and the quality of EC decoction pieces after processing could not be accurately controlled.

Objectives: This study aims to establish a qualitative model and a quantitative model in the salting process of EC, which could quickly determine its processing degree and internal quality.

Materials and methods: First, determine the chromaticity values and the contents of geniposidic acid, chlorogenic acid, geniposide, pinoresinol diglucoside, and hyperoside in 123 batches of differently processed EC, and analyze their correlations. The results showed that the chromaticity values had different degrees of correlation with the components. The orthogonal partial least squares discriminant analysis (OPLS-DA) method was used to establish the chromaticity qualitative discriminant model and the near-infrared (NIR) qualitative discriminant model. The two qualitative models well distinguished the samples of four categories: raw EC, processing less, salt eucommia, processing too much, and the model verification results were good. Finally, an NIR quantitative model was established by using the partial least squares (PLS) method, combined with chroma value, content, and NIR spectroscopy.

Results: There were different degrees of correlation between the chromaticity values and the components. The qualitative and quantitative discriminant models established were good enough to distinguish the four types of samples: raw eucommia, insufficient processing, salt eucommia, and excessive processing, and the model verification results were good.

Conclusions: The intrinsic characteristic component content and chroma value of EC in the salting process could be predicted simultaneously by the model, which provided a rapid determination method for the quality control of EC in the processing process.

基于色度法和近红外光谱的杜仲皮质盐加工全过程质量快速鉴别
背景:杜仲皮作为中药之一,临床常与盐一起配制,以提高其疗效。但其炮制程度一直以“经验”来判断,炮制后的中药饮片质量无法准确控制。目的:本研究旨在建立EC腌制过程的定性模型和定量模型,以快速确定其加工程度和内在质量。材料与方法:首先,测定123批不同炮制方法EC中京尼平苷酸、绿原酸、京尼平苷、松脂醇二糖苷、金丝桃苷的色度值和含量,并分析其相关性。结果表明,色度值与各组分有不同程度的相关性。采用正交偏最小二乘判别分析(OPLS-DA)方法建立了色度定性判别模型和近红外定性判别模型。两个定性模型对原料杜仲、加工少、盐杜仲、加工多四类样品进行了较好的区分,模型验证结果良好。最后,结合色度值、含量和近红外光谱,利用偏最小二乘(PLS)方法建立了近红外定量模型。结果:色度值与各成分之间存在不同程度的相关性。所建立的定性和定量判别模型足以区分生杜仲、未加工杜仲、盐杜仲和过度加工杜仲四种样品,模型验证结果良好。结论:该模型可同时预测盐化过程中EC的内在特征成分含量和色度值,为盐化过程中EC的质量控制提供了一种快速测定方法。
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来源期刊
Phytochemical Analysis
Phytochemical Analysis 生物-分析化学
CiteScore
6.00
自引率
6.10%
发文量
88
审稿时长
1.7 months
期刊介绍: Phytochemical Analysis is devoted to the publication of original articles concerning the development, improvement, validation and/or extension of application of analytical methodology in the plant sciences. The spectrum of coverage is broad, encompassing methods and techniques relevant to the detection (including bio-screening), extraction, separation, purification, identification and quantification of compounds in plant biochemistry, plant cellular and molecular biology, plant biotechnology, the food sciences, agriculture and horticulture. The Journal publishes papers describing significant novelty in the analysis of whole plants (including algae), plant cells, tissues and organs, plant-derived extracts and plant products (including those which have been partially or completely refined for use in the food, agrochemical, pharmaceutical and related industries). All forms of physical, chemical, biochemical, spectroscopic, radiometric, electrometric, chromatographic, metabolomic and chemometric investigations of plant products (monomeric species as well as polymeric molecules such as nucleic acids, proteins, lipids and carbohydrates) are included within the remit of the Journal. Papers dealing with novel methods relating to areas such as data handling/ data mining in plant sciences will also be welcomed.
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