Statistics For Food Scientists

The practical approached championed in this book have led to increasing the quality on many successful products through providing a better understanding of consumer needs, current product and process performance and a desired future state. In 2009, Frank Rossi and Viktor Mirtchev brought their practical statistical thinking forward and created the course “Statistics for Food Scientists . The intent of the course was to help product and process developers increase the probability of their project’s success through the incorporation of practical statistical thinking in their challenges. The course has since grown and has become the basis of this book. Presents detailed descriptions of statistical concepts and commonly used statistical tools to better analyze data and interpret results Demonstrates thorough examples and specific practical problems of what food scientists face in their work and how the tools of statistics can help them to make more informed decisions Provides information to show how statistical tools are applied to improve research results, enhance product quality, and promote overall product development

Many statistical innovations are linked to applications in food science. For example, the student t-test (a statistical method) was developed to monitor the quality of stout at the Guinness Brewery and multivariate statistical methods are applied widely in the spectroscopic analysis of foods. Nevertheless, statistical methods are most often associated with engineering, mathematics, and the medical sciences, and are rarely thought to be driven by food science. Consequently, there is a dearth of statistical methods aimed specifically at food science, forcing researchers to utilize methods intended for other disciplines. The objective of this Brief will be to highlight the most needed and relevant statistical methods in food science and thus eliminate the need to learn about these methods from other fields. All methods and their applications will be illustrated with examples from research literature. ​

Easy Statistics for Food Science with R presents the application of statistical techniques to assist students and researchers who work in food science and food engineering in choosing the appropriate statistical technique. The book focuses on the use of univariate and multivariate statistical methods in the field of food science. The techniques are presented in a simplified form without relying on complex mathematical proofs. This book was written to help researchers from different fields to analyze their data and make valid decisions. The development of modern statistical packages makes the analysis of data easier than before. The book focuses on the application of statistics and correct methods for the analysis and interpretation of data. R statistical software is used throughout the book to analyze the data. Contains numerous step-by-step tutorials help the reader to learn quickly Covers the theory and application of the statistical techniques Shows how to analyze data using R software Provides R scripts for all examples and figures

The recording and analysis of food data are becoming increasingly sophisticated. Consequently, the food scientist in industry or at study faces the task of using and understanding statistical methods. Statistics is often viewed as a difficult subject and is often avoided because of its complexity and a lack of specific application to the requirements of food science. This situation is changing – there is now much material on multivariate applications for the more advanced reader, but a case exists for a univariate approach aimed at the non-statistician. This second edition of Statistical Methods for Food Science provides a source text on accessible statistical procedures for the food scientist, and is aimed at professionals and students in food laboratories where analytical, instrumental and sensory data are gathered and require some form of summary and analysis before interpretation. It is suitable for the food analyst, the sensory scientist and the product developer, and others who work in food-related disciplines involving consumer survey investigations will also find many sections of use. There is an emphasis on a ‘hands-on’ approach, and worked examples using computer software packages and the minimum of mathematical formulae are included. The book is based on the experience and practice of a scientist engaged for many years in research and teaching of analytical and sensory food science at undergraduate and post-graduate level. This revised and updated second edition is accompanied by a new companion website giving the reader access to the datasets and Excel spreadsheets featured in the book. Check it out now by visiting www.wiley.com/go/bower/statistical or by scanning the QR code below.

As we move further into the 21st Century, sensory and consumer studies continue to develop, playing an important role in food science and industry. These studies are crucial for understanding the relation between food properties on one side and human liking and buying behaviour on the other. This book by a group of established scientists gives a comprehensive, up-to-date overview of the most common statistical methods for handling data from both trained sensory panels and consumer studies of food. It presents the topic in two distinct sections: problem-orientated (Part I) and method orientated (Part II), making it to appropriate for people at different levels with respect to their statistical skills. This book succesfully: Makes a clear distinction between studies using a trained sensory panel and studies using consumers. Concentrates on experimental studies with focus on how sensory assessors or consumers perceive and assess various product properties. Focuses on relationships between methods and techniques and on considering all of them as special cases of more general statistical methodologies It is assumed that the reader has a basic knowledge of statistics and the most important data collection methods within sensory and consumer science. This text is aimed at food scientists and food engineers working in research and industry, as well as food science students at master and PhD level. In addition, applied statisticians with special interest in food science will also find relevant information within the book.

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.

Abstract: An applied statistics text is offered for college students, teachers, research scientists, and those engaged in agriculture and the food industries. The sequence of topic presentation proceeds from data organization and tabulation, through graphing (to obtain the data distribution pattern), to analysis of the pattern (to determine location and dispersion parameters); interpretation of the results and report-writing are the final phases. A comprehensive range of direct statistical tests is covered, along with numerous examples and problems. Mathematical complexities and formula derivations are avoided; a knowledge of high school mathematics is sufficient to underastand and apply the statistical methods covered. (wz).

Statistical Aspects of the Microbiological Examination of Foods, Third Edition, updates some important statistical procedures following intensive collaborative work by many experts in microbiology and statistics, and corrects typographic and other errors present in the previous edition. Following a brief introduction to the subject, basic statistical concepts and procedures are described including both theoretical and actual frequency distributions that are associated with the occurrence of microorganisms in foods. This leads into a discussion of the methods for examination of foods and the sources of statistical and practical errors associated with the methods. Such errors are important in understanding the principles of measurement uncertainty as applied to microbiological data and the approaches to determination of uncertainty. The ways in which the concept of statistical process control developed many years ago to improve commercial manufacturing processes can be applied to microbiological examination in the laboratory. This is important in ensuring that laboratory results reflect, as precisely as possible, the microbiological status of manufactured products through the concept and practice of laboratory accreditation and proficiency testing. The use of properly validated standard methods of testing and the verification of ‘in house’ methods against internationally validated methods is of increasing importance in ensuring that laboratory results are meaningful in relation to development of and compliance with established microbiological criteria for foods. The final chapter of the book reviews the uses of such criteria in relation to the development of and compliance with food safety objectives. Throughout the book the theoretical concepts are illustrated in worked examples using real data obtained in the examination of foods and in research studies concerned with food safety. Includes additional figures and tables together with many worked examples to illustrate the use of specific procedures in the analysis of data obtained in the microbiological examination of foods Offers completely updated chapters and six new chapters Brings the reader up to date and allows easy access to individual topics in one place Corrects typographic and other errors present in the previous edition