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Using formal descriptions, graphical illustrations, practical examples, and R software tools, Introduction to Multivariate Statistical Analysis in Chemometrics presents simple yet thorough explanations of the most important multivariate statistical methods for analyzing chemical data. It includes discussions of various statistical methods, such as
Comprehensive Chemometrics, Second Edition, Four Volume Set features expanded and updated coverage, along with new content that covers advances in the field since the previous edition published in 2009. Subject of note include updates in the fields of multidimensional and megavariate data analysis, omics data analysis, big chemical and biochemical data analysis, data fusion and sparse methods. The book follows a similar structure to the previous edition, using the same section titles to frame articles. Many chapters from the previous edition are updated, but there are also many new chapters on the latest developments. Presents integrated reviews of each chemical and biological method, examining their merits and limitations through practical examples and extensive visuals Bridges a gap in knowledge, covering developments in the field since the first edition published in 2009 Meticulously organized, with articles split into 4 sections and 12 sub-sections on key topics to allow students, researchers and professionals to find relevant information quickly and easily Written by academics and practitioners from various fields and regions to ensure that the knowledge within is easily understood and applicable to a large audience Presents integrated reviews of each chemical and biological method, examining their merits and limitations through practical examples and extensive visuals Bridges a gap in knowledge, covering developments in the field since the first edition published in 2009 Meticulously organized, with articles split into 4 sections and 12 sub-sections on key topics to allow students, researchers and professionals to find relevant information quickly and easily Written by academics and practitioners from various fields and regions to ensure that the knowledge within is easily understood and applicable to a large audience
The limited coverage of data analysis and statistics offered in most undergraduate and graduate analytical chemistry courses is usually focused on practical aspects of univariate methods. Drawing in real-world examples, Practical Guide to Chemometrics, Second Edition offers an accessible introduction to application-oriented multivariate meth
A new, full-color, completely updated edition of the key practical guide to chemometrics This new edition of this practical guide on chemometrics, emphasizes the principles and applications behind the main ideas in the field using numerical and graphical examples, which can then be applied to a wide variety of problems in chemistry, biology, chemical engineering, and allied disciplines. Presented in full color, it features expansion of the principal component analysis, classification, multivariate evolutionary signal and statistical distributions sections, and new case studies in metabolomics, as well as extensive updates throughout. Aimed at the large number of users of chemometrics, it includes extensive worked problems and chapters explaining how to analyze datasets, in addition to updated descriptions of how to apply Excel and Matlab for chemometrics. Chemometrics: Data Driven Extraction for Science, Second Edition offers chapters covering: experimental design, signal processing, pattern recognition, calibration, and evolutionary data. The pattern recognition chapter from the first edition is divided into two separate ones: Principal Component Analysis/Cluster Analysis, and Classification. It also includes new descriptions of Alternating Least Squares (ALS) and Iterative Target Transformation Factor Analysis (ITTFA). Updated descriptions of wavelets and Bayesian methods are included. Includes updated chapters of the classic chemometric methods (e.g. experimental design, signal processing, etc.) Introduces metabolomics-type examples alongside those from analytical chemistry Features problems at the end of each chapter to illustrate the broad applicability of the methods in different fields Supplemented with data sets and solutions to the problems on a dedicated website, www.booksupport.wiley.com Chemometrics: Data Driven Extraction for Science, Second Edition is recommended for post-graduate students of chemometrics as well as applied scientists (e.g. chemists, biochemists, engineers, statisticians) working in all areas of data analysis.
The third edition of the Encyclopedia of Analytical Science, Ten Volume Set is a definitive collection of articles covering the latest technologies in application areas such as medicine, environmental science, food science and geology. Meticulously organized, clearly written and fully interdisciplinary, the Encyclopedia of Analytical Science, Ten Volume Set provides foundational knowledge across the scope of modern analytical chemistry, linking fundamental topics with the latest methodologies. Articles will cover three broad areas: analytical techniques (e.g., mass spectrometry, liquid chromatography, atomic spectrometry); areas of application (e.g., forensic, environmental and clinical); and analytes (e.g., arsenic, nucleic acids and polycyclic aromatic hydrocarbons), providing a one-stop resource for analytical scientists. Offers readers a one-stop resource with access to information across the entire scope of modern analytical science Presents articles split into three broad areas: analytical techniques, areas of application and and analytes, creating an ideal resource for students, researchers and professionals Provides concise and accessible information that is ideal for non-specialists and readers from undergraduate levels and higher
Given the inherent complexity of food products, most instrumental techniques employed for quality and authenticity evaluation (e.g., chromatographic methods) are time demanding, expensive, and involve a considerable amount of manual labor. Therefore, there has been an increasing interest in simpler, faster, and reliable analytical methods for assessing food quality attributes. Spectroscopic Methods in Food Analysis presents the basic concepts of spectroscopic methods, together with a discussion on the most important applications in food analysis. The determination of product quality and authenticity and the detection of adulteration are major issues in the food industry, causing concern among consumers and special attention among food manufacturers. As such, this book explains why spectroscopic methods have been extensively employed to the analysis of food products as they often require minimal or no sample preparation, provide rapid and on-line analysis, and have the potential to run multiple tests on a single sample (i.e., non-destructive). This book consists of concepts related to food quality and authenticity, that are quite broad, given the different demands of the manufacturer, the consumer, the surveillance and the legislative bodies that ultimately provide healthy and safe products.
The book introduces most of the basic tools of chemometrics including experimental design, signal analysis, statistical methods for analytical chemistry and multivariate methods. It then discusses a number of important applications including food chemistry, biological pattern recognition, reaction monitoring, optimisation of processes, medical applications. The book arises from a series of short articles that have been developed over four years on Chemweb (www.chemweb.com).
To understand the world around us, as well as ourselves, we need to measure many things, many variables, many properties of the systems and processes we investigate. Hence, data collected in science, technology, and almost everywhere else are multivariate, a data table with multiple variables measured on multiple observations (cases, samples, items, process time points, experiments). This book describes a remarkably simple minimalistic and practical approach to the analysis of data tables (multivariate data). The approach is based on projection methods, which are PCA (principal components analysis), and PLS (projection to latent structures) and the book shows how this works in science and technology for a wide variety of applications. In particular, it is shown how the great information content in well collected multivariate data can be expressed in terms of simple but illuminating plots, facilitating the understanding and interpretation of the data. The projection approach applies to a variety of data-analytical objectives, i.e., (i) summarizing and visualizing a data set, (ii) multivariate classification and discriminant analysis, and (iii) finding quantitative relationships among the variables. This works with any shape of data table, with many or few variables (columns), many or few observations (rows), and complete or incomplete data tables (missing data). In particular, projections handle data matrices with more variables than observations very well, and the data can be noisy and highly collinear. Authors: The five authors are all connected to the Umetrics company (www.umetrics.com) which has developed and sold software for multivariate analysis since 1987, as well as supports customers with training and consultations. Umetrics' customers include most large and medium sized companies in the pharmaceutical, biopharm, chemical, and semiconductor sectors.
This volume discusses the sustainability of Egypt’s agriculture and the challenges involved. It provides a comprehensive review and the latest research findings, and covers a variety of topics under the following themes: · Integrated natural resources management for sustainable production · Integrated biopesticides and biofertilizers for sustainable agriculture · Integrated plant and animal production for a sustainable food supply · Policies for sustainable agriculture in Egypt The volume closes with a summary of the key conclusions and recommendations from all chapters. Together with the companion volume Sustainability of Agricultural Environment in Egypt: Part I, it offers an essential source of information for postgraduate students, researchers, and stakeholders alike.