Mathematical and statistical methods in food science and technology / edited by Daniel Granato and Gastón Ares ; Azila Abdul-Aziz [and fifty others], contributors.

Format:

Book

Contributor:

Granato, Daniel.

Ares, Gaston.

Abdul-Aziz, Azila.

Series:

IFT Press series.

IFT Press.

THEi Wiley ebooks.

Language:

English

Subjects (All):

Food--Analysis--Statistical methods.

Food.

Food contamination--Research--Statistical methods.

Food contamination.

Food supply--Mathematics.

Food supply.

Physical Description:

1 online resource (533 pages)

Edition:

First edition.

Place of Publication:

Chichester, England : Wiley-Blackwell, 2014.

Language Note:

English

System Details:

Access using campus network via VPN at home (THEi Users Only).

Summary:

Mathematical and Statistical Approaches in Food Science and Technology offers an accessible guide to applying statistical and mathematical technologies in the food science field whilst also addressing the theoretical foundations. Using clear examples and case-studies by way of practical illustration, the book is more than just a theoretical guide for non-statisticians, and may therefore be used by scientists, students and food industry professionals at different levels and with varying degrees of statistical skill.

Contents:

Mathematical and Statistical Methods in Food Science and Technology; Contents; About the editors; List of contributors; Acknowledgements; Section 1; 1 The use and importance of design of experiments (DOE) in process modelling in food science and technology; ABSTRACT; INTRODUCTION; OVERVIEW OF EXPERIMENTAL DESIGNS; Types of design; Some Considerations; RESPONSE SURFACE METHODOLOGY: A TOOL FOR ANALYSING AND OPTIMIZING PRODUCTS AND PROCESSES; PROCESS OPTIMIZATION; Simultaneous optimization of response variables; RSM application to foods/process development/optimization; STATISTICAL PACKAGES

FINAL REMARKS AND PERSPECTIVES REFERENCES; 2 The use of correlation, association and regression to analyse processes and products; ABSTRACT; INTRODUCTION; PROCESS ANALYSIS; MULTIVARIATE METHODS; OUTLIER DETECTION; MODEL ACCURACY AND VALIDATION; OVERFITTING AND UNDERFITTING; ROUTINE ANALYSES AND APPLICATIONS; SUMMARY; REFERENCES; 3 Case study: Optimization of enzyme-aided extraction of polyphenols from unripe apples by response surface methodology; ABSTRACT; INTRODUCTION; EXPERIMENTS; Materials, chemicals and instruments; Viscozyme L aided polyphenol extraction

Experimental design for the RSM procedure Determination of the optimum conditions and evaluation of the model; Determination of TPC and CAC; Statistical analysis; RESULTS AND DISCUSSION; Modelling of the Viscozyme L aided polyphenol extraction reaction; Effect of Viscozyme L aided hydrolysis variables on TPC; Effect of Viscozyme L aided hydrolysis variables on CAC; Estimation and validation of optimum hydrolysis condition; CONCLUSION; REFERENCES; 4 Case study: Statistical analysis of eurycomanone yield using a full factorial design; ABSTRACT; INTRODUCTION; MATERIALS AND METHODS; Materials

Methods RESULTS AND DISCUSSION; CONCLUSIONS; REFERENCES; Section 2; 5 Applications of principal component analysis (PCA) in food science and technology; ABSTRACT; INTRODUCTION; GOAL; DEFINITION; EFFECTIVE COMPUTATION; SOME PROPERTIES; REPRESENTATION OF THE INDIVIDUALS: A GEOMETRICAL INTERPRETATION; DIMENSIONALITY REDUCTION; COVARIANCE OR CORRELATION MATRIX?; DETERMINING THE NUMBER OF COMPONENTS; SOME PATTERNS IN R OR IN S AND THEIR INTERPRETATION; RELATIONSHIP WITH THE ORTHOGONAL REGRESSION; MULTIPLE REGRESSION ON PRINCIPAL COMPONENTS; REFERENCES

6 Multiple factor analysis: Presentation of the method using sensory data ABSTRACT; INTRODUCTION; DATA; Ten Touraine white wines; Two panels; Pre-processing; Analysis of the table; WEIGHTING TO BALANCE GROUPS OF VARIABLES; Representing wines and descriptors; SUPERIMPOSED REPRESENTATION OF THE WINES ANALYSED BY EACH PANEL; SUPPLEMENTARY CATEGORICAL VARIABLES; REPRESENTING THE DIMENSIONS OF SEPARATE ANALYSES; REPRESENTING GROUPS OF VARIABLES; Measuring the relationship between a variable and a group of variables; Relationship square; Relationship square and projection

Measuring the overall resemblance of shape between two similar clouds: the RV coefficient

Notes:

Description based upon print version of record.

Includes bibliographical references at the end of each chapters and index.

Description based on print version record.

ISBN:

9781118434536

1118434536

9781118434635

1118434633

9781118434567

1118434560

OCLC:

874148351