Mathematical and Statistical Methods in Food Science and Technology (Institute of Food Technologists Series) - Hardcover
Synopsis
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.
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About the Author
Dr Daniel Granato, Research Fellow, Department of Food Engineering, State University of Ponta Grossa, Paraná, Brazil.
Dr Gastón Ares, Assistant Professor, Department of Food Science and Technology, Facultad de Química, Universidad de la República, Uruguay
From the Back Cover
Statistical and mathematical methodologies are usually perceived by people working in food science as complex and difficult subjects, and most food scientists and professionals receive limited instruction in them. This hinders the implementation of statistical and mathematical methodologies in food science and limits the usability and application of these techniques for research that contains a large quantity of complex data. These statistical techniques are necessary for the development and evaluation of food products and processes. They are also important for studying mechanisms underlying different phenomena that may affect product quality or the unit operations in food development.
Mathematical and Statistical Approaches in Food Science and Technology offers accessible and practical information, suitable for readers across a range of knowledge levels and food-related disciplines, for applying statistical and mathematical technologies in food science. The book's focus is on the application of complex methodologies which have been recently introduced in the field (managing physicochemical, chemical, rheological, nutritional, and sensory data) and have proven to be extremely useful in characterizing new products and processes in the food industries. Theoretical explanations, practical examples and case studies ensure that this is an easy-to-follow and comprehensive text, not just a theoretical guide for non-statisticians. It will therefore be of value to all food science professionals with varying degrees of statistical skill, as well as researchers, undergraduate and graduate students.
From the Inside Flap
Statistical and mathematical methodologies are usually perceived by people working in food science as complex and difficult subjects, and most food scientists and professionals receive limited instruction in them. This hinders the implementation of statistical and mathematical methodologies in food science and limits the usability and application of these techniques for research that contains a large quantity of complex data. These statistical techniques are necessary for the development and evaluation of food products and processes. They are also important for studying mechanisms underlying different phenomena that may affect product quality or the unit operations in food development.
Mathematical and Statistical Approaches in Food Science and Technology offers accessible and practical information, suitable for readers across a range of knowledge levels and food-related disciplines, for applying statistical and mathematical technologies in food science. The book's focus is on the application of complex methodologies which have been recently introduced in the field (managing physicochemical, chemical, rheological, nutritional, and sensory data) and have proven to be extremely useful in characterizing new products and processes in the food industries. Theoretical explanations, practical examples and case studies ensure that this is an easy-to-follow and comprehensive text, not just a theoretical guide for non-statisticians. It will therefore be of value to all food science professionals with varying degrees of statistical skill, as well as researchers, undergraduate and graduate students.
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Mathematical and Statistical Methods in Food Science and Technology
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