Chemometrics in Food Chemistry

Produk Detail:
  • Author : Federico Marini
  • Publisher : Elsevier Inc. Chapters
  • Pages : 512 pages
  • ISBN : 0128083220
  • Rating : /5 from reviews
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Download or Read online Chemometrics in Food Chemistry full in PDF, ePub and kindle. this book written by Federico Marini and published by Elsevier Inc. Chapters which was released on 08 June 2013 with total page 512 pages. We cannot guarantee that Chemometrics in Food Chemistry book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. The chapter describes the motivation behind the book and introduces the role of chemometrics in food quality control and authentication. A brief description of the structure of the monograph is also provided.

Chemometrics in Food Chemistry

Chemometrics in Food Chemistry
  • Author : Lucia Bertacchini,Marina Cocchi,Mario Li Vigni,Andrea Marchetti,Elisa Salvatore,Simona Sighinolfi,Michele Silvestri,Caterina Durante
  • Publisher : Elsevier Inc. Chapters
  • Release : 08 June 2013
GET THIS BOOK Chemometrics in Food Chemistry

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

Chemometrics in Food Chemistry

Chemometrics in Food Chemistry
  • Author : Ivana Stanimirova,Michał Daszykowski,Beata Walczak
  • Publisher : Elsevier Inc. Chapters
  • Release : 08 June 2013
GET THIS BOOK Chemometrics in Food Chemistry

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

Chemometrics in Food Chemistry

Chemometrics in Food Chemistry
  • Author : Anna de Juan,Sílvia Mas
  • Publisher : Elsevier Inc. Chapters
  • Release : 08 June 2013
GET THIS BOOK Chemometrics in Food Chemistry

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

Chemometrics in Food Chemistry

Chemometrics in Food Chemistry
  • Author : Frank Westad,Marta Bevilacqua,Federico Marini
  • Publisher : Elsevier Inc. Chapters
  • Release : 08 June 2013
GET THIS BOOK Chemometrics in Food Chemistry

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 : Mario Li Vigni,Caterina Durante,Marina Cocchi
  • Publisher : Elsevier Inc. Chapters
  • Release : 08 June 2013
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In the food research and production field, system complexity is increasing and several new challenges are emerging every day. This implies an urgent necessity to extract information and obtain models capable of inferring the underlying relationships that link all the variability sources which characterize food or its production process (e.g. compositional profile, processing conditions) to very general end properties of foodstuff, such as the healthiness, the consumer perception, the link to a territory and the effect of the production

Chemometrics in Food Chemistry

Chemometrics in Food Chemistry
  • Author : Alberta Tomassini,Giorgio Capuani,Maurizio Delfini,Alfredo Miccheli
  • Publisher : Elsevier Inc. Chapters
  • Release : 08 June 2013
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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 : Francesco Savorani,Morten Arendt Rasmussen,Åsmund Rinnan,Søren Balling Engelsen
  • Publisher : Elsevier Inc. Chapters
  • Release : 08 June 2013
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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

Chemometrics in Food Chemistry

Chemometrics in Food Chemistry
  • Author : José Manuel Amigo,Idoia Martí,Aoife Gowen
  • Publisher : Elsevier Inc. Chapters
  • Release : 08 June 2013
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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

Chemometrics in Food Chemistry

Chemometrics in Food Chemistry
  • Author : José Manuel Amigo,Federico Marini
  • Publisher : Elsevier Inc. Chapters
  • Release : 08 June 2013
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This chapter provides an overview of the main multiway methods used for data decomposition, calibration and pattern recognition. Parallel factor analysis (PARAFAC), PARAFAC2, Tucker3 and other multiway methods are briefly presented, together with a description and discussion of the main properties and steps of their most popular algorithms. The theoretical explanation is accompanied by some illustrative examples of their application in the field of Food Science (classification of vinegars with Excitation-Emission Fluorescence, ripening of apples measured with GC–MS, sensory

Chemometrics in Food Chemistry

Chemometrics in Food Chemistry
  • Author : Marta Bevilacqua,Remo Bucci,Andrea D. Magrì,Antonio L. Magrì,Riccardo Nescatelli,Federico Marini
  • Publisher : Elsevier Inc. Chapters
  • Release : 08 June 2013
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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.

Chemometrics in Food Chemistry

Chemometrics in Food Chemistry
  • Author : Riccardo Leardi
  • Publisher : Elsevier Inc. Chapters
  • Release : 08 June 2013
GET THIS BOOK Chemometrics in Food Chemistry

In this chapter, some of the most commonly used designs (e.g. Full Factorial, Plackett–Burman, Central Composite, Doehlert, D-Optimal, qualitative variables at more than two levels, mixture) will be presented. It will be shown how it is often possible to obtain them by hand, without using any software. How to compute the coefficients of the model and their significance will also be shown. The different designs will be illustrated and commented by means of real examples.