Analytical chemistry studies and uses instruments and methods to separate, identify, and quantify matter. In practice, separation, identification or quantification may constitute the entire analysis or be combined with another method. Separation isolates analytes. Qualitative analysis identifies analytes, while quantitative analysis determines the numerical amount or concentration.
Multivariate statistics is a subdivision of statistics encompassing the simultaneous observation and analysis of more than one outcome variable, i.e., multivariate random variables. Multivariate statistics concerns understanding the different aims and background of each of the different forms of multivariate analysis, and how they relate to each other. The practical application of multivariate statistics to a particular problem may involve several types of univariate and multivariate analyses in order to understand the relationships between variables and their relevance to the problem being studied.
Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data preprocessing.
Chemometrics is the science of extracting information from chemical systems by data-driven means. Chemometrics is inherently interdisciplinary, using methods frequently employed in core data-analytic disciplines such as multivariate statistics, applied mathematics, and computer science, in order to address problems in chemistry, biochemistry, medicine, biology and chemical engineering. In this way, it mirrors other interdisciplinary fields, such as psychometrics and econometrics.
Near-infrared spectroscopy (NIRS) is a spectroscopic method that uses the near-infrared region of the electromagnetic spectrum. Typical applications include medical and physiological diagnostics and research including blood sugar, pulse oximetry, functional neuroimaging, sports medicine, elite sports training, ergonomics, rehabilitation, neonatal research, brain computer interface, urology, and neurology. There are also applications in other areas as well such as pharmaceutical, food and agrochemical quality control, atmospheric chemistry, combustion research and knowledge.
Metabolomics is the scientific study of chemical processes involving metabolites, the small molecule substrates, intermediates, and products of cell metabolism. Specifically, metabolomics is the "systematic study of the unique chemical fingerprints that specific cellular processes leave behind", the study of their small-molecule metabolite profiles. The metabolome represents the complete set of metabolites in a biological cell, tissue, organ, or organism, which are the end products of cellular processes. Messenger RNA (mRNA), gene expression data, and proteomic analyses reveal the set of gene products being produced in the cell, data that represents one aspect of cellular function. Conversely, metabolic profiling can give an instantaneous snapshot of the physiology of that cell, and thus, metabolomics provides a direct "functional readout of the physiological state" of an organism. There are indeed quantifiable correlations between the metabolome and the other cellular ensembles, which can be used to predict metabolite abundances in biological samples from, for example mRNA abundances. One of the ultimate challenges of systems biology is to integrate metabolomics with all other -omics information to provide a better understanding of cellular biology.
Partial least squares regression is a statistical method that bears some relation to principal components regression; instead of finding hyperplanes of maximum variance between the response and independent variables, it finds a linear regression model by projecting the predicted variables and the observable variables to a new space. Because both the X and Y data are projected to new spaces, the PLS family of methods are known as bilinear factor models. Partial least squares discriminant analysis (PLS-DA) is a variant used when the Y is categorical.
Process analytical technology (PAT) has been defined by the United States Food and Drug Administration (FDA) as a mechanism to design, analyze, and control pharmaceutical manufacturing processes through the measurement of critical process parameters (CPP) which affect the critical quality attributes (CQA).
Chemical imaging is the analytical capability to create a visual image of components distribution from simultaneous measurement of spectra and spatial, time information. Hyperspectral imaging measures contiguous spectral bands, as opposed to multispectral imaging which measures spaced spectral bands.
Multivariate optical computing, also known as molecular factor computing, is an approach to the development of compressed sensing spectroscopic instruments, particularly for industrial applications such as process analytical support. "Conventional" spectroscopic methods often employ multivariate and chemometric methods, such as multivariate calibration, pattern recognition, and classification, to extract analytical information from data collected at many different wavelengths. Multivariate optical computing uses an optical computer to analyze the data as it is collected. The goal of this approach is to produce instruments which are simple and rugged, yet retain the benefits of multivariate techniques for the accuracy and precision of the result.
In computational biology and bioinformatics, analysis of variance – simultaneous component analysis is a method that partitions variation and enables interpretation of these partitions by SCA, a method that is similar to principal components analysis (PCA). Analysis of variance (ANOVA) is a collection of statistical models and their associated estimation procedures used to analyze differences. Statistical coupling analysis (SCA) is a technique used in bioinformatics to measure covariation between pairs of amino acids in a protein multiple sequence alignment (MSA).
Transmission Raman spectroscopy (TRS) is a variant of Raman spectroscopy which is advantageous in probing bulk content of diffusely scattering samples. Although it was demonstrated in the early days of Raman spectroscopy it was not exploited in practical settings until much later, probably due to limitations of technology at the time. It was rediscovered in 2006, where the authors showed that it was capable of allowing Raman spectroscopy through many millimetres of tabletted or powdered samples. In addition, this research has also identified several highly beneficial analytical properties of this approach, including the ability to probe bulk content of powders and tissue in the absence of subsampling and to reject Raman and fluorescence components originating from the surface of the sample.
Jerome J. Workman Jr. is an American analytical spectroscopist, author, editor, and inventor born on August 6, 1952, in Northfield, Minnesota. Jerry Workman, Jerry Workman, Jr., and J.J. Workman are also names he uses for publishing.
Paul J. Gemperline is an American analytical chemist and chemometrician. He is a Distinguished Professor of Chemistry at East Carolina University (ECU) located in Greenville, North Carolina and has been the recipient of several scientific awards, including the 2003 Eastern Analytical Symposium Award in Chemometrics. He is author of more than 60 publications in the field of chemometrics. Dr. Gemperline served as Dean of the Graduate School at ECU from 2008 to 2022. He retired from ECU June 30, 2022 and is now professor emeritus.
Dr. Agnar Höskuldsson is a Danish scientist who specializes in the field of chemometrics. He was formerly an associate professor at the Technical University of Denmark. He was awarded the Herman Wold gold medal for his contribution to chemometrics in 1997 and over the span of his career he has published over 30 scientific papers and is credited with over 2000 scientific citations.
SmartPLS is a software with graphical user interface for variance-based structural equation modeling (SEM) using the partial least squares (PLS) path modeling method. Users can estimate models with their data by using basic PLS-SEM, weighted PLS-SEM (WPLS), consistent PLS-SEM (PLSc-SEM), and sumscores regression algorithms. The software computes standard results assessment criteria and it supports additional statistical analyses . Since SmartPLS is programmed in Java, it can be executed and run on different computer operating systems such as Windows and Mac.
Olive oil contains small amounts of free fatty acids. Free acidity is an important parameter that defines the quality of olive oil. It is usually expressed as a percentage of oleic acid in the oil. As defined by the European Commission regulation No. 2568/91 and subsequent amendments, the highest quality olive oil must feature a free acidity lower than 0.8%. Virgin olive oil is characterized by acidity between 0.8% and 2%, while lampante olive oil features a free acidity higher than 2%. The increase of free acidity in olive oil is due to free fatty acids that are released from triglycerides.
Raman Tool Set is a free software package for processing and analysis of Raman spectroscopy datasets. It has been developed mainly aiming to Raman spectra analysis, but since it works with 2-columns datafiles it can deal with the results of many spectroscopy techniques.
Tormod Næs is a Norwegian statistician working in chemometrics and sensometrics. He studies multivariate statistical analysis, spectroscopy, food science, and sensory science. His impact on chemometrics is exemplified by the over 8,000 citations to his most well-known book, Multivariate Calibration, and the awards in chemometrics that he has received.
