Coffee aroma—Statistical analysis of compositional data

Solid-phase microextraction in headspace mode coupled with gas chromatography-mass spectrometry was applied to the determination of volatile compounds in 30 commercially available coffee samples. In order to differentiate and characterize Arabica and Robusta coffee, six major volatile compounds (acetic acid, 2-methylpyrazine, furfural, 2-furfuryl alcohol, 2,6-dimethylpyrazine, 5-methylfurfural) were chosen as the most relevant markers. Cluster analysis and principal component analysis (PCA) were applied to the raw chromatographic data and data processed by centred logratio transformation.     

Statistical analysis of thermoanalytical experimental data

A statistical technique based on the Wilcockson criterion is suggested for estimation of the reproducibility of thermoanalytical experiments. Reduction of the whole physicochemical process to a quasi-one-stage process is described.This work was carried out partially with the aid of International Science Foundation (Programme Students and Post-Graduate Students).     

Analytical artifacts, sample handling and preservation methods of environmental samples of synthetic pyrethroids

Sample handling and preservation methods of environmental samples of synthetic pyrethroids (SPs) are very important and must be controlled to maintain sample integrity during analytical determinations. However, published literature has treated this issue only partly, and, in many instances, with contradictory conclusions.The tendency of SPs to adsorb - to varying degrees under different conditions - to surfaces and solid particulates with which they come in contact may be responsible for this situation. It has become evident that SPs discharged to water bodies are present mainly in the adsorbed state, and that affects their bioavailability and the reliability of analytical results. Refrigeration and storage in the dark are prerequisites for stabilization of SPs in environmental samples.Several other factors that contribute to SPs instability include:(1) matrix composition;(2) container material; and,(3) sample acidity.Sample agitation prior to analysis may be useful to reduce losses due to adsorption. There are several chemical reagents that inhibit the degradative processes of SPs, but the efficiency of preservation depends - to a large extent - on the characteristics of sample matrix.This article reviews various aspects related to preservation of SPs and puts forward a preliminary guideline for proper practice during sampling, storage and sample preparation of SPs.     

Multiple factor analysis in environmental chemistry

In environmental chemistry studies, it may be necessary to analyze data sets constituted by different blocks of variables, possibly of different types, measured on the same samples. Multiple factor analysis (MFA) is presented as a tool for exploring such data. The most important features of MFA are shown on a real environmental data set, consisting of two blocks of data, namely heavy metals and polycyclic aromatic hydrocarbons, measured for sediment samples. They are discussed and compared to principal component analysis (PCA). The usefulness of the weighting scheme used in MFA as a preprocessing step for other chemometric methods, such as clustering, is also highlighted.     

微萃取技术在环境分析中的应用

微萃取技术是近年来出现的绿色样品前处理技术。它具有操作简便、环境友好等优点,并且在环境、医药及食品等领域得到广泛的应用。本文仅就固相微萃取和液相微萃取在环境分析中的应用作一简要综述。     

Recovering incomplete data using Statistical Multiple Imputations (SMI): a case study in environmental chemistry

This paper presents a statistical technique that can be applied to environmental chemistry data where missing values and limit of detection levels prevent the application of statistics. A working example is taken from an environmental leaching study that was set up to determine if there were significant differences in levels of leached arsenic (As), chromium (Cr) and copper (Cu) between lysimeters containing preservative treated wood waste and those containing untreated wood. Fourteen lysimeters were setup and left in natural conditions for 21 weeks. The resultant leachate was analysed by ICP-OES to determine the As, Cr and Cu concentrations. However, due to the variation inherent in each lysimeter combined with the limits of detection offered by ICP-OES, the collected quantitative data was somewhat incomplete. Initial data analysis was hampered by the number of ‘missing values’ in the data. To recover the dataset, the statistical tool of Statistical Multiple Imputation (SMI) was applied, and the data was re-analysed successfully. It was demonstrated that using SMI did not affect the variance in the data, but facilitated analysis of the complete dataset.     

Microwave-assisted micro-solid-phase extraction for analysis of tetracycline antibiotics in environmental samples

In this study, a novel solid-liquid-solid extraction approach, which was termed ‘microwave-assisted micro-solid-phase extraction’ (MAE-μ-SPE), was developed. Target analytes were extracted from the sample into extraction solvent enhanced by microwave field, following adsorption by the adsorbent in the micro-solid-phase extraction device. Without any clean-up steps, the extracts were analysed by high performance liquid chromatography coupled with ultra-violet detector. The MAE-μ-SPE approach was developed for the extraction of four tetracycline antibiotics residues in environmental soil, sludge and atmospheric particulate matters. Variables affecting extraction procedures were systematically investigated. Low detection limits of 0.1–6.3 ng/g and low quantification limits of 0.33–20.7 ng/g were achieved under optimised conditions. The recoveries of antibiotics ranged from 70.6% to 110.5% with relative standard deviation of less than 15.1%. The predominance was showed when compared to conventional MAE and μ-SPE method. According to the results, MAE-μ-SPE was proved to be a simple and effective sample preparation method for the analysis of trace organic contaminants in environmental samples.     

The role of thermal analysis in environmental protection

In the past industry has developed chemicals and products, optimized for the best suitable properties concerning different application fields. Now, ideas of environmental precaution are arising, on the one hand looking for reduction of materials flow to avoid or minimize the waste, on the other hand following the idea of process and product integrated environmental protection. That means to develop processes and products which are safer and more tolerant regarding the environment and its organisms.In this connection thermal analysis is a very successful tool for predicting the risk of burning processes or fire accidents. Thermal analysis in this context means the classical thermal analysis methods like DTA, TG, DSC and its couplings with gas analysis methods as well as the simulation of burning processes in different kind of furnaces with identification and quantification of the evolved gases.     

直观推导式演进特征投影法对环境样本中多环芳烃的定性定量分析

基于新近发展的直观推导式演进特征投影法(HELP), 本文提出了一个对二维数据进行同时定性定量的分析方法, 并将其成功地用于环境样本中多环芳烃化合物定量解析。对于一维色谱难以定量的重叠峰, HELP方法充分利用色谱、光谱两方面的选择性信息, 得到了具有真实物理意义的唯一解。在定性分辨结果的基础上, 本文还提出了三种可能的定量方法。这种二维数据的解析新方法, 能大幅度地降低对色谱分离条件的要求, 可直接用于复杂实际样本的定性定量分析。     

Clustering of time-course gene expression data using functional data analysis

Clustering of gene expression data collected across time is receiving growing attention in the biological literature since time-course experiments allow one to understand dynamic biological processes and identify genes governed by the same processes. It is believed that genes demonstrating similar expression profiles over time might give an informative insight into how underlying biological mechanisms work. In this paper, we propose a method based on functional data analysis (FNDA) to cluster time-dependent gene expression profiles. Consideration of clustering problems using the FNDA setting provides ways to take time dependency into account by using basis function expansion to describe the partially observed curves. We also discuss how to choose the number of bases in the basis function expansion in FNDA. A synthetic cycle data and a real data are used to demonstrate the proposed method and some comparisons between the proposed and existing approaches using the adjusted Rand indices are made.     

亲水作用色谱及其在环境分析中的应用进展

亲水作用色谱(HILIC)是一种分离极性和亲水性化合物的液相色谱模式,其作为反相液相色谱(RPLC)的重要补充,近年来越来越受到各个领域的关注和重视。这不只是因为强极性化合物的分离问题在各个领域引起了重视,而且因为与RPLC比较,HILIC具有流动相组成黏度低、色谱柱渗透性好、与质谱联用的灵敏度高及反压较低等优势。本文简要概述了HILIC的发展历程、特点及保留机理,重点介绍了HILIC用于环境分析的最新进展,评述了HILIC及RPLC用于污染物分析的优缺点,并指出了HILIC用于环境分析的未来发展趋势。     

Explorative data analysis of two-dimensional electrophoresis gels

Methods for classification of two-dimensional (2-DE) electrophoresis gels based on multivariate data analysis are demonstrated. Two-dimensional gels of ten wheat varieties are analyzed and it is demonstrated how to classify the wheat varieties in two qualities and a method for initial screening of gels is presented. First, an approach is demonstrated in which no prior knowledge of the separated proteins is used. Alignment of the gels followed by a simple transformation of data makes it possible to analyze the gels in an automated explorative manner by principal component analysis, to determine if the gels should be further analyzed. A more detailed approach is done by analyzing spot volume lists by principal components analysis and partial least square regression. The use of spot volume data offers a mean to investigate the spot pattern and link the classified protein patterns to distinct spots on the gels for further investigation. The explorative approach in analysis of 2-D gels makes it possible, in a fast and convenient way, to screen many gels in order to determine the protein patterns that form clusters and could be selected for further examination.     

Recommendations for reporting thermal analysis data

Recommendations for reporting of thermal analysis data relating to differential thermal analysis, differential scanning calorimetry, thermogravimetry and thermomechanical analysis were developed some two decades ago. Since that time there have been significant changes in the techniques, as well as a greater understanding of the effect of experimental variables on the results obtained from thermonalytical experiments. This paper reports on a preliminary review of the Recommendations by the Task Group established by the ICTAC Committee on Standardization to undertake their revision. Particular attention has been paid to the properties of the sample; control of the instrument variables; and the data acquisition and manipulation by computers.     

大体积进样技术在环境分析中的应用

在毛细管气相色谱法(CGC)中,采用大体积进样技术(LVI),即使用能够容纳大体积样品的进样装置以及增加可控时间的溶剂蒸汽放空装置,可以满足环境样品中超痕量组分的分析要求,简化样品浓缩步骤以及实现液相色谱(LC)与CGC的在线联用。针对分析物的性质、毛细管柱的规格和分析的目的已发展了多种LVI。本文总结了几种常见的LVI,包括柱头进样(OCI)和程序升温进样(PTV),以及近年来发展的一些新技术,如在柱同时溶剂浓缩进样、样品直接引入进样/复杂基质进样和同时溶剂冷凝无分流进样,阐述了各种进样技术的基本原理及其与样品提取、LC纯化在线联用的方法在环境分析应用中的一些最新研究进展。     

Potential applications of functional data analysis in chemometrics

In spectroscopy the measured spectra are typically plotted as a function of the wavelength (or wavenumber), but analysed with multivariate data analysis techniques (multiple linear regression (MLR), principal components regression (PCR), partial least squares (PLS)) which consider the spectrum as a set of m different variables. From a physical point of view it could be more informative to describe the spectrum as a function rather than as a set of points, hereby taking into account the physical background of the spectrum, being a sum of absorption peaks for the different chemical components, where the absorbance at two wavelengths close to each other is highly correlated. In a first part of this contribution, a motivating example for this functional approach is given. In a second part, the potential of functional data analysis is discussed in the field of chemometrics and compared to the ubiquitous PLS regression technique using two practical data sets. It is shown that for spectral data, the use of B-splines proves to be an appealing basis to accurately describe the data. By applying both functional data analysis and PLS on the data sets the predictive ability of functional data analysis is found to be comparable to that of PLS. Moreover, many chemometric datasets have some specific structure (e.g. replicate measurements, on the same object or objects that are grouped), but the structure is often removed before analysis (e.g. by averaging the replicates). In the second part of this contribution, we suggest a method to adapt traditional analysis of variance (ANOVA) methods to datasets with spectroscopic data. In particular, the possibilities to explore and interpret sources of variation, such as variations in sample and ambient temperature, are examined. Copyright © 2008 John Wiley & Sons, Ltd.     

Statistically rigorous analysis of imaging SIMS data in the presence of detector saturation

We present a new strategy for analyzing imaging time‐of‐flight SIMS data sets affected by detector saturation. Rather than attempt to correct the measured data to remove saturation, we incorporate the detector behavior into the statistical basis of the analysis. This is performed within the framework of maximum a posteriori reconstruction. The proposed approach has several advantages over previous techniques. No approximations are involved other than the assumed model of the detector. The method performs well even when applied to highly saturated and/or single‐scan data sets. It is statistically rigorous, correctly treating the underlying statistical distribution of the data. It is also compatible with Bayesian methods for incorporating prior knowledge about sample properties. An efficient iterative scheme for solving the proposed equations is presented for the case of the bilinear model commonly used in analyses of SIMS data. The correctness of the approach and its efficacy are demonstrated on synthetic data sets. The method is found to perform better than a widely‐used data‐correction method used in combination with alternating‐least‐squares Multivariate Curve Resolution analysis. Copyright © 2015 John Wiley & Sons, Ltd.     

Gravitation-driven stress-reduced cell handling

We present a simple lab-on-chip device for handling small samples of delicate cells, e.g. stem cells. It uses a combination of sedimentation and dielectrophoresis. The transport of cells is driven by gravitation. Dielectrophoresis uses radio-frequency electric fields for generating particle-selective forces dependent on size and polarisability. Electrodes along the channels hold particles and/or cells in a defined position and deflect them towards different outlets. The absence of external pumping and the integration of injection and sampling ports allow the processing of tiny sample volumes. Various functions are demonstrated, such as contact-free cell trapping and cell/particle sorting. Pairs of human cells and antibody-coated beads, as they are formed for T cell activation, are separated from unbound beads. The cells experience only low stress levels compared with the stress levels in dielectrophoresis systems, where transport depends on external pumping. Our device is a versatile yet simple tool that finds applications in cellular biotechnology, in particular when an economic solution is required. Figure A simple gravitation-driven lab-on-chip device for the separation of mixed populations of microparticles or cells by negative dielectrophoresis.     

Observation‐based missing data methods for exploratory data analysis to unveil the connection between observations and variables in latent subspace models

This paper introduces a class of methods to infer the relationship between observations and variables in latent subspace models. The approach is a modification of the recently proposed missing data methods for exploratory data analysis (MEDA). MEDA is useful to identify the structure in the data and also to interpret the contribution of each latent variable. In this paper, MEDA is augmented with dummy variables to find the data variables related to a given deviation detected among observations, for instance, the difference between one cluster of observations and the bulk of the data. The MEDA extension, referred to as observation‐based MEDA or oMEDA, can be performed in several ways, one of which is theoretically shown to be equivalent to a comparison of means between groups. The use of the proposed approach is demonstrated with a number of examples with simulated data and a real data set of archeological artifacts. Copyright © 2011 John Wiley & Sons, Ltd.     

Immunosorbents: A new tool for pesticide sample handling in environmental analysis

 Immunoaffinity techniques have been widely used for the determination of different analytes in the medical field. However the use of antibodies immobilized in an appropriate support material to preconcentrate pesticides from environmental samples is only recent. The production of antibodies, election of supports, antibody immobilization procedures, elution of analytes from immunosorbents and the more recent applications in the field of pesticide analysis are reviewed. The present review concludes that immunosorbents have great potential and discusses the present limitations and expected future trends. Received: 29 July 1996 / Accepted: 14 August 1996     

SPME in environmental analysis

Recent advances in the use of solid-phase microextraction (SPME) in environmental analysis, including fiber coatings, derivatization techniques, and in-tube SPME, are reviewed in this article. Several calibration methods for SPME, including traditional calibration methods, the equilibrium extraction method, the exhaustive extraction method, and several diffusion-based calibration methods, are presented. Recent developed SPME devices for on-site sampling and several applications of SPME in environmental analysis are also introduced.