Quantitative fingerprint and antioxidative properties of Artemisia argyi leaves combined with chemometrics

Quantitative fingerprint and differences of Artemisia argyi from different varieties, picking time, aging year, and origins were analyzed combing with chemometrics. The antioxidant activity was determined and antioxidant markers of Artemisia argyi were screened. Variety WA3 was significantly different from that of the other varieties. Fingerprint peak response and antioxidant activity of A. argyi picked in December were lower than samples collected in May and August. Fresh A. argyi leaves were significantly superior to withered leaves and stems. Artemisia argyi aging 1–5 years presented a classification trend. Antioxidant activity of A. argyi produced in Nanyang was generally superior to others origins. Peak 9, isochlorogenic acid A, and 6-methoxyluteolin contributed greatly for classification of A. argyi from different variety, picking time, aging year, and origin. Isochlorogenic acid A, isochlorogenic acid C, 6-methoxyluteolin, and chlorogenic acid were selected as antioxidant marker of A. argyi. The method based on quantitative fingerprint, antioxidant activity evaluation, and chemometrics was reliable to analyze the differences of A. argyi samples from different sources.     

UHPLC–MS/MS quantification combined with chemometrics for the comparative analysis of different batches of raw and wine‐processed Dipsacus asper

A rapid and sensitive ultra‐high performance liquid chromatography with tandem mass spectrometry approach was established for the simultaneous determination of 4‐caffeoylquinic acid, loganic acid, chlorogenic acid, loganin, 3,5‐dicaffeoylquinic acid, dipsacoside B, asperosaponin VI, and sweroside in raw and wine‐processed Dipsacus asper . Chloramphenicol and glycyrrhetinic acid were employed as internal standards. The proposed approach was fully validated in terms of linearity, sensitivity, precision, repeatability as well as recovery. Intra‐ and interassay variability for all analytes were 2.8–4.9 and 1.7–4.8%, respectively. The standard addition method determined recovery rates for each analytes (96.8–104.6%). In addition, the developed approach was applied to 20 batches of raw and wine‐processed samples of Dipsacus asper . Principle component analysis and partial least squares‐discriminate analysis revealed a clear separation between the raw group and wine‐processed group. After wine‐processing, the contents of loganic acid, chlorogenic acid, dipsacoside B, and asperosaponin VI were upregulated, while the contents of 3,5‐dicaffeoylquinic acid, 4‐caffeoylquinic acid, loganin, and sweroside were downregulated. Our results demonstrated that ultra‐high performance liquid chromatography with tandem mass spectrometry quantification combined with chemometrics is a viable method for quality evaluation of the raw Dipsacus asper and its wine‐processed products.     

The diversity in the applications of partial least squares: an overview

Advances in technology make it happen to have massive amount of information in the form of multiple variables per object. The use of multivariate approaches for modeling the real‐life phenomena is natural in such situation. There are numerous multivariate approaches in the literature, and its a challenge to stay updated on the possibilities. Partial least squares (PLSs) are one of the many modeling approaches for high‐throughput data, and its use in different fields to address the variety of problems has been increased in recent years. We therefore present an overview of PLS's applications. The objective of this paper is to give a comprehensive overview on the advances in PLS algorithm together with its applications for regression, classification, variable selection, and survival analysis problems covering genomics, chemometrics, neuroinformatics, process control, computer vision, econometric, environmental studies, and so on. We have mainly presented different PLS approaches and their applications, so that the reader can easily get an understanding of possibility to use PLS for their own field. For further reading, literature references together with software availability are provided. Copyright © 2015 John Wiley & Sons, Ltd.     

化学计量学方法在光谱解析中的应用进展

本文对近20年来化学计量学在光谱分析测试中的应用进行了评述。指出了化学计量学在光谱分析中的重要性和应用前景。引用文献共129篇。     

Metabolites profiling of Chrysanthemum pacificum Nakai parts using UPLC-PDA-MS coupled to chemometrics

Methanol-soluble constituents from the flowers, non-flowering aerial parts and roots of Chrysanthemum pacificum Nakai were analysed via high resolution UPLC-PDA-qTOF-MS followed by chemometrics. Forty-seven chromatographic peaks belonging to various metabolite classes were detected. Most metabolite classes showed qualitative and quantitative differences across parts, with luteolin conjugates being mostly enriched in flowers whereas non-flowering aerial parts contained mostly quercetin and methoxylated flavone conjugates. Root sample ranked the lowest for all flavones and dicaffeoylquinic acids. In contrast, 1,5-di-caffeoylquinic acid levels were found at high levels in flowers and aerial parts reaching 3145 and 1390 μg/g, respectively, suggesting that C. pacificum could serve as a natural resource of this well-recognised anti-hepatotoxic phenolic. Principal component analysis was further used for organs classification in an untargeted manner. This study provides the first map of secondary metabolites distribution in C. pacificum Nakai organs.     

The use of infrared spectroscopy in combination with chemometrics for quality control and authentication of edible fats and oils: A review

Edible fats and oils provide a significant contribution in our diet and daily life, as cooking or frying oil, or as components used in food, pharmaceutical, and cosmetics products. Fats and oils are characterized by specific values, including acid value, saponification value, iodine value, and peroxide value, as well as the oxidation products which occur during storage due to oxidative and hydrolytic deterioration. Currently, due to the high price of edible fats and oils, some unethical producers adulterate high-value edible oils like olive oil with low-priced oils like palm and corn oils; therefore the authentication analysis of edible fats and oils must be assured by introducing reliable and fast methods like infrared spectroscopy. Fourier transform infrared (FTIR) spectroscopy is an ideal technique for monitoring the quality control of fats and oils due to its property as a “fingerprint spectra technique,” which allows analysts to differentiate among fats and oils. FTIR spectra signals of fats and oils are very complex. Fortunately, a statistical technique called chemometrics can be used to handle the complex FTIR spectral data. Chemometrics in combination with FTIR spectroscopy has been widely used in many aspects of monitoring quality control of edible fats and oils including their authenticity.     

Being Uncertain in Chromatographic Calibration—Some Unobvious Details in Experimental Design

This is an introductory tutorial and review about the uncertainty problem in chromatographic calibration. It emphasizes some unobvious, but important details influencing errors in the calibration curve estimation, uncertainty in prediction, as well as the connections and dependences between them, all from various perspectives of uncertainty measurement. Nonuniform D-optimal designs coming from Fedorov theorem are computed and presented. As an example, all possible designs of 24 calibration samples (3–8, 4–6, 6–4, 8–3 and 12–2, both uniform and D-optimal) are compared in context of many optimality criteria. It can be concluded that there are only two independent (orthogonal, but slightly complex) trends in optimality of these designs. The conclusions are important, as the uniform designs with many concentrations are not the best choices, contrary to some intuitive perception. Nonuniform designs are visibly better alternative in most calibration cases.     

化学计量学在锕系元素分析中的应用

锕系元素的化学性质相似,各元素的分离和分析都很困难,用传统的数据解析手段,难以实现各元素的同时、快速分析。化学计量学是一种高效、功能强大的数据解析方法,对于样品复杂,基体干扰严重以及多组分样品的分析具有独特优势。将化学计量学应用于锕系元素的分析中,利用数学分离代替化学分离,可直接对样品进行测定。化学计量学方法也可用来指导试样的科学采集,进行实验设计、仪器分析操作条件选择等。从吸收光谱、ICP–AES及放射性测量3个方面综述了化学计量学在锕系元素分析中的应用,阐明了化学计量学在锕系元素分析中的应用难点及发展前景。     

世界采样大会的由来与Pierre Gy采样理论的发展

简单介绍了世界采样大会的由来与Pierre Gy采样理论的产生与发展。重点阐述了Pierre Gy公式和采样理论的涵义与应用,以及化学计量学对采样理论发展的推动和促进作用。同时,采样理论的发展也推动了过程分析技术的应用以及各类先进采样、制样和混样设备的研制和应用。中国作为全球最大的大宗商品进口国和消费国,对采样理论和实践应用有着迫切的需求,将第九届世界采样与混样大会引入中国,必将促进和提升我国采样理论的研究和实践水平,使其更好地为我国大宗商品交易和检验检测市场服务。     

Artificial neural networks versus partial least squares and multivariate resolution-alternating least squares approaches for the assay of ascorbic acid,rutin, and hesperidin in an antioxidant formulation

Abstract

This study was concerned with the assay of ascorbic acid (ASC), rutin, and hesperidin (HES) in their combined formulation using a multivariate approach. Three chemometric-assisted spectrophotometric models namely: partial least squares, multivariate curve resolution-alternating least squares, and artificial neural networks were developed and validated. The quantitative analyses of all the proposed models were assessed by percentage recoveries, root mean square error of prediction, and standard error of prediction. The proposed models were used in the range of 10.0–70.0, 2.0–10.0, and 2.0–10.0?µg mL^?1 for ASC, rutin, and HES, respectively. In addition, correlation coefficients between the pure and estimated spectral profiles were used for the qualitative analysis of a multivariate curve resolution-alternating least squares model. Artificial neural networks showed higher speed and methodological simplicity over the other two models. These models presented powerful multivariate statistical tools that were applied to the analysis of the combined dosage form in the Australian market. They have the ability to overcome difficulties such as colinearity and spectral overlaps. Statistical comparison between the proposed and reported methods showed no significant difference. The proposed methods can be used for the routine analysis of the studied drugs in quality control laboratories.