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Chemometrics in Food Chemistry

Chemometrics in Food Chemistry Author
ISBN-10 9780444595294
Release 2013-06-08
Pages 512
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The issues related to food science and authentication are of particular importance for researchers, consumers and regulatory entities. The need to guarantee quality foodstuff – where the word "quality" encompasses many different meanings, including e.g. nutritional value, safety of use, absence of alteration and adulterations, genuineness, typicalness, etc. – has led researchers to look for increasingly effective tools to investigate and deal with food chemistry problems. As even the simplest food is a complex matrix, the way to investigate its chemistry cannot be other than multivariate. Therefore, chemometrics is a necessary and powerful tool for the field of food analysis and control. For food science in general and food analysis and control in particular, there are several problems for which chemometrics are of utmost importance. Traceability, i.e. the possibility of verifying the animal/botanical, geographical and/or productive origin of a foodstuff, is, for instance, one area where the use of chemometric techniques is not only recommended but essential: indeed, at present no specific chemical and/or physico-chemical markers have been identified that can be univocally linked to the origin of a foodstuff and the only way of obtaining reliable traceability is by means of multivariate classification applied to experimental fingerprinting results. Another area where chemometrics is of particular importance is in building the bridge between consumer preferences, sensory attributes and molecular profiling of food: by identifying latent structures among the data tables, bilinear modeling techniques (such as PCA, MCR, PLS and its various evolutions) can provide an interpretable and reliable connection among these domains. Other problems include process control and monitoring, the possibility of using RGB or hyperspectral imaging techniques to nondestructively check food quality, calibration of multidimensional or hyphenated instruments etc.



Chemometrics in Food Chemistry

Chemometrics in Food Chemistry Author Marta Bevilacqua
ISBN-10 9780128083260
Release 2013-06-08
Pages 512
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This chapter describes the basic theory about classification, starting from a general description of the different approaches to classification and then illustrating in detail the principal methods which are used in the framework of assessment of food quality. Examples of application of the methods to different data sets are also provided.



Statistical Design Chemometrics

Statistical Design   Chemometrics Author Roy E Bruns
ISBN-10 0080462138
Release 2006-01-27
Pages 422
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Statistical Design-Chemometrics is applicable to researchers and professionals who wish to perform experiments in chemometrics and carry out analysis of the data in the most efficient way possible. The language is clear, direct and oriented towards real applications. The book provides 106 exercises with answers to accompany the study of theoretical principles. Forty two cases studies with real data are presented showing designs and the complete statistical analyses for problems in the areas chromatography, electroanalytical and electrochemistry, calibration, polymers, gas adsorption, semiconductors, food technology, biotechnology, photochemistry, catalysis, detergents and ceramics. These studies serve as a guide that the reader can use to perform correct data analyses. -Provides 42 case studies containing step-by-step descriptions of calculational procedures that can be applied to most real optimization problems -Contains 106 theoretical exercises to test individual learning and to provide classroom exercises and material for written tests and exams -Written in a language that facilitates learning for physical and biological scientists and engineers -Takes a practical approach for those involved in industrial optimization problems



Chemometrics in Food Chemistry

Chemometrics in Food Chemistry Author Anna de Juan
ISBN-10 9780128083277
Release 2013-06-08
Pages 512
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The term multivariate curve resolution (MCR) designates a family of methods devoted to solving the mixture analysis problem in multicomponent samples. MCR provides the qualitative and quantitative contribution (profile) of each of the compounds in a sample from the sole information of the raw experimental data acquired. Food analysis is about knowing the qualitative and quantitative composition of foodstuffs and, hence, MCR fits very well in this scenario. Typical problems related to food analysis that can be solved by MCR are the identification and analytical determination of target compounds in the presence of unknown interferences/compounds, obtaining food fingerprint information to be used for authentication, adulteration or other purposes, and the interpretation of food processes. All these situations can be solved by handling measurements as simple as a data table with one spectrum (response) per sample or as complex as flexible multiset structures formed by several data tables (e.g. excitation/emission spectra, hyphenated separation techniques: high-performance liquid chromatography with diode array detection, liquid chromatography or gas chromatography–mass spectrometry, etc.), each of them related to a sample or to a particular food condition.



Food Authentication

Food Authentication Author Contantinos A. Georgiou
ISBN-10 9781118810262
Release 2017-05-08
Pages 568
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The determination of food authenticity is a vital component of quality control. Its importance has been highlighted in recent years by high-profile cases in the global supply chain such as the European horsemeat and the Chinese melamine scandals, the latter of which led to six fatalities and the hospitalization of thousands of infants. As well as being a safety concern, authenticity is also a quality criterion for food and food ingredients. Consumers and retailers demand that the products they purchase and sell are what they purport to be. This book covers the most advanced techniques used for the authentication of a vast number of products around the world. The reader will be informed about the latest pertinent analytical techniques. Chapters focus on the novel techniques and markers that have emerged in recent years. An introductory section presents the concepts of food authentication, while the second section examines in detail the analytical techniques for the detection of fraud relating to geographical, botanical, species, and processing origin and production methods of food materials and ingredients. Finally, the third section looks at consumer attitudes towards food authenticity, the application of bioinformatics to this field, and the Editor's conclusions and future outlook. Beyond being a reference for researchers working in food authentication, this book will serve as an essential resource for analytical scientists interested in the field and food scientists aiming to appreciate analytical approaches. This book will be a companion to under- and postgraduate students in their studies in food authentication, and will be useful to researchers in universities and research institutions.



Chemometrics in Food Chemistry

Chemometrics in Food Chemistry Author Ivana Stanimirova
ISBN-10 9780128083291
Release 2013-06-08
Pages 512
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In this chapter, foundations of robust statistics are introduced, including classic and robust estimators as well as their statistical properties (breakdown point, efficiency, influence function and equivariance property). Then, some robust methods that have gained popularity in recent years are presented. The major benefit of using robust methods stems from the fact that they help providing stable estimates for data containing outliers (food samples that have considerably different compositions in comparison with the majority of samples). Regardless of reasons for their uniqueness, outliers strongly affect data interpretation when any method with the least-squares cost function is used. Therefore, robust methods are more suitable to explore and model data containing natural samples when outliers are expected. In addition to exploration and modeling of multivariate data, processing of incomplete multivariate data that contain outliers is also discussed.



Chemometrics in Food Chemistry

Chemometrics in Food Chemistry Author Alberta Tomassini
ISBN-10 9780128083321
Release 2013-06-08
Pages 512
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In this chapter, we report the NMR-based metabolomic approach in food analysis and display its more instructive applications in quality control in order to illustrate the set of problems related to the peculiar data source, the potentiality, and the development features of main interest for chemometricians in this field.



Chemometrics in Food Chemistry

Chemometrics in Food Chemistry Author Lucia Bertacchini
ISBN-10 9780128083314
Release 2013-06-08
Pages 512
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In the last decades, mankind has become totally aware about the importance of food quality: nowadays authentication and traceability are words of general use. Food authentication verifies how much a food is in accordance with its label description and law and it could be considered a further guarantee for the quality and safety of a foodstuff. The traceability of food could be considered an essential element in ensuring safety and high quality of food. The synergistic use of instrumental analytical techniques and chemometrics represents a promising way to obtain trustworthy results in the development of authenticity and traceability models. This chapter deals with the potentialities of chemometrics tools in resolving some real issues related to food traceability and authenticity. Particular attention will be paid to the use of some exploratory, classification, and discrimination techniques. In the first part of this chapter, a briefly description of European regulations (Authenticity and Traceability: the European Union point of view), and traceability and authenticity markers (Authenticity and Traceability: a scientific point of view) is reported. The second part is split into two sections: namely Food Authenticity and Food Traceability applications, where the main features and advantages of some chemometrics approaches are presented.



Design and Optimization in Organic Synthesis

Design and Optimization in Organic Synthesis Author Rolf Carlson
ISBN-10 9780080455273
Release 2005-04-08
Pages 596
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Revised, and updated Design and Optimization in Organic Synthesis presents strategies to explore experimental conditions and methodologies for systematic studies of entire reaction systems (substrates, reagent(s), catalyst(s), and solvents). Chemical phenomena are not usually the result of a single factor and this book describes how statistically designed methods can be used to analyse and evaluate synthetic procedures. The methodology is based on multivariate statistical techniques. The accompanying CD contains data tables and programmes. This book is essential reading for anyone working in process design and development in fine chemicals or the pharmaceutical industry, and is suitable for those with no experience in the field. * Contains recalculated models and redrawn figures, as well as new chapters on for example, the design of combinatorial libraries * Presents strategies to explore experimental conditions and methodologies * Enables the analysis and prediction of the best synthetic procedures



Nature inspired Methods in Chemometrics Genetic Algorithms and Artificial Neural Networks

Nature inspired Methods in Chemometrics  Genetic Algorithms and Artificial Neural Networks Author Riccardo Leardi
ISBN-10 0080522629
Release 2003-12-03
Pages 402
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In recent years Genetic Algorithms (GA) and Artificial Neural Networks (ANN) have progressively increased in importance amongst the techniques routinely used in chemometrics. This book contains contributions from experts in the field is divided in two sections (GA and ANN). In each part, tutorial chapters are included in which the theoretical bases of each technique are expertly (but simply) described. These are followed by application chapters in which special emphasis will be given to the advantages of the application of GA or ANN to that specific problem, compared to classical techniques, and to the risks connected with its misuse. This book is of use to all those who are using or are interested in GA and ANN. Beginners can focus their attentions on the tutorials, whilst the most advanced readers will be more interested in looking at the applications of the techniques. It is also suitable as a reference book for students. Subject matter is steadily increasing in importance Comparison of Genetic Algorithms (GA) and Artificial Neural Networks (ANN) with the classical techniques Suitable for both beginners and advanced researchers



Chemometrics in Food Chemistry

Chemometrics in Food Chemistry Author Frank Westad
ISBN-10 9780128083253
Release 2013-06-08
Pages 512
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In this chapter, a survey of the theory behind the main chemometric methods used for multivariate calibration is presented. Ordinary least squares, multiple linear regression, principal component regression, partial least squares regression and principal covariate regression are discussed in detail. Tools for model diagnostics and model interpretation are presented, together with strategies for variable selection.



Chemometrics in Food Chemistry

Chemometrics in Food Chemistry Author José Manuel Amigo
ISBN-10 9780128083307
Release 2013-06-08
Pages 512
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Computer vision systems have become typical tools of increasing importance to control manufacturing processes and product quality in a non-destructive manner in food industrial processing. During the past several years, we have heard about how hyperspectral imaging, joined with chemometrics, could offer a set of possibilities that may help to increase the control of the final quality assessment in production lines. This chapter will not review the main applications of HSI and chemometrics for food quality assessment, since this has already been extensively covered in several reviews. Instead, we will discuss the application and feasibility of the main chemometric techniques applied to different foodstuffs. The reader will be provided with a detailed overview of how to use chemometrics in hyperspectral data, along with a critical discussion on their respective advantages and potential pitfalls. The examples that we will use for this purpose are the detection of water in cheese, classification of bitterness in almonds in a set of samples, detection and classification of contaminants in cheese, and hydration of chickpeas during soaking.



Chemometrics in Food Chemistry

Chemometrics in Food Chemistry Author Francesco Savorani
ISBN-10 9780128083338
Release 2013-06-08
Pages 512
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In classical empirical research a model requires that the number of variables must be less than the number of observations, but developments in chemometrics and modern analytical platforms have pushed people beyond the classical model. Typical “omics” data sets will include 100–1000 samples and often more than 10,000 variables and the advantage of using chemometrics to large data structures is the ability to efficiently deal with collinear data sets with many more variables than samples. However, the trend with ever more variables also pushes the chemometric tools to the limit as they will also increase the extent of spurious correlations and interferences. This chapter advocates for a systematic breakdown of the variable space in intervals in order to improve the interpretability and performance of chemometric methods. The term “i-chemometrics” is here introduced to encompass the whole class of interval-based chemometric methods. This chapter will describe the advantages of using the generic i-chemometric methods for data preprocessing, data exploration, regression, and sample classification/discrimination using examples from NMR foodomics. The main advantages are more parsimonious models, improved interpretability and, in many cases, improved performance.



Handbook of Chemometrics and Qualimetrics

Handbook of Chemometrics and Qualimetrics Author
ISBN-10 0080551904
Release 1997-12-12
Pages 886
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Handbook of Chemometrics and Qualimetrics



The Data Analysis Handbook

The Data Analysis Handbook Author I.E. Frank
ISBN-10 008086841X
Release 1994-09-30
Pages 364
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Analyzing observed or measured data is an important step in applied sciences. The recent increase in computer capacity has resulted in a revolution both in data collection and data analysis. An increasing number of scientists, researchers and students are venturing into statistical data analysis; hence the need for more guidance in this field, which was previously dominated mainly by statisticians. This handbook fills the gap in the range of textbooks on data analysis. Written in a dictionary format, it will serve as a comprehensive reference book in a rapidly growing field. However, this book is more structured than an ordinary dictionary, where each entry is a separate, self-contained entity. The authors provide not only definitions and short descriptions, but also offer an overview of the different topics. Therefore, the handbook can also be used as a companion to textbooks for undergraduate or graduate courses. 1700 entries are given in alphabetical order grouped into 20 topics and each topic is organized in a hierarchical fashion. Additional specific entries on a topic can be easily found by following the cross-references in a top-down manner. Several figures and tables are provided to enhance the comprehension of the topics and a list of acronyms helps to locate the full terminologies. The bibliography offers suggestions for further reading.



Resolving Spectral Mixtures

Resolving Spectral Mixtures Author
ISBN-10 9780444636447
Release 2016-08-13
Pages 674
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Resolving Spectral Mixtures: With Applications from Ultrafast Time-Resolved Spectroscopy to Superresolution Imaging offers a comprehensive look into the most important models and frameworks essential to resolving the spectral unmixing problem—from multivariate curve resolution and multi-way analysis to Bayesian positive source separation and nonlinear unmixing. Unravelling total spectral data into the contributions from individual unknown components with limited prior information is a complex problem that has attracted continuous interest for almost four decades. Spectral unmixing is a topic of interest in statistics, chemometrics, signal processing, and image analysis. For decades, researchers from these fields were often unaware of the work in other disciplines due to their different scientific and technical backgrounds and interest in different objects or samples. This led to the development of quite different approaches to solving the same problem. This multi-authored book will bridge the gap between disciplines with contributions from a number of well-known and strongly active chemometric and signal processing research groups. Among chemists, multivariate curve resolution methods are preferred to extract information about the nature, amount, and location in time (process) and space (imaging and microscopy) of chemical constituents in complex samples. In signal processing, assumptions are usually around statistical independence of the extracted components. However, the chapters include the complexity of the spectral data to be unmixed as well as dimensionality and size of the data sets. Advanced spectroscopy is the key thread linking the different chapters. Applications cover a large part of the electromagnetic spectrum. Time-resolution ranges from femtosecond to second in process spectroscopy and spatial resolution covers the submicronic to macroscopic scale in hyperspectral imaging. Demonstrates how and why data analysis, signal processing, and chemometrics are essential to the spectral unmixing problem Guides the reader through the fundamentals and details of the different methods Presents extensive plots, graphical representations, and illustrations to help readers understand the features of different techniques and to interpret results Bridges the gap between disciplines with contributions from a number of well-known and highly active chemometric and signal processing research groups



Comprehensive Chemometrics

Comprehensive Chemometrics Author Steven D. Brown
ISBN-10 044452701X
Release 2009-03-09
Pages 2896
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Designed to serve as the first point of reference on the subject, Comprehensive Chemometrics presents an integrated summary of the present state of chemical and biochemical data analysis and manipulation. The work covers all major areas ranging from statistics to data acquisition, analysis, and applications. This major reference work provides broad-ranging, validated summaries of the major topics in chemometrics—with chapter introductions and advanced reviews for each area. The level of material is appropriate for graduate students as well as active researchers seeking a ready reference on obtaining and analyzing scientific data. Features the contributions of leading experts from 21 countries, under the guidance of the Editors-in-Chief and a team of specialist Section Editors: L. Buydens; D. Coomans; P. Van Espen; A. De Juan; J.H. Kalivas; B.K. Lavine; R. Leardi; R. Phan-Tan-Luu; L.A. Sarabia; and J. Trygg Examines the merits and limitations of each technique through practical examples and extensive visuals: 368 tables and more than 1,300 illustrations (750 in full color) Integrates coverage of chemical and biological methods, allowing readers to consider and test a range of techniques Consists of 2,200 pages and more than 90 review articles, making it the most comprehensive work of its kind Offers print and online purchase options, the latter of which delivers flexibility, accessibility, and usability through the search tools and other productivity-enhancing features of ScienceDirect