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Mathematical and Statistical Applications in Food Engineering de Surajbhan Sevda

Mathematical and Statistical Applications in Food Engineering

Editat de Surajbhan Sevda, Anoop Singh
en Limba Engleză Paperback – 30 sep 2021
Written by experts from all over the world, the book comprises the latest applications of mathematical and models in food engineering and fermentation. It provides the fundamentals on statistical methods to solve standard problems associated with food engineering and fermentation technology. Combining theory with a practical, hands-on approach, this book covers key aspects of food engineering. Presenting cuttingedge information, the book is an essential reference on the fundamental concepts associated with food engineering.
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Specificații

ISBN-13: 9781032175379
ISBN-10: 1032175370
Pagini: 444
Ilustrații: 16 Illustrations, color; 161 Illustrations, black and white
Dimensiuni: 178 x 254 x 24 mm
Greutate: 0.83 kg
Editura: CRC Press

Cuprins

ROLE OF MATHEMATICAL AND STATISTICAL MODELLING IN FOOD ENGINEERING. EVOLUTIONARY OPTIMIZATION TECHNIQUES AS EFFECTIVE TOOLS FOR PROCESS MODELLING IN FOOD PROCESSING. OPTIMIZATION OF FOOD PROCESSES USING MIXTURE EXPERIMENTS SOME APPLICATIONS. MICROORGANISMS AND FOOD PRODUCTS IN FOOD PROCESSING USING FULL FACTORIAL DESIGN. THE USE OF CORRELATION, ASSOCIATION AND REGRESSION TO ANALYZE FOOD PROCESSES AND PRODUCTS. APPLICATION OF CLUSTER ANALYSIS IN FOOD SCIENCE AND TECHNOLOGY. MULTIWAY STATISTICAL METHODS FOR FOOD ENGINEERING AND TECHNOLOGY. APPLICATION OF MULTIVARIATE STATISTICAL ANALYSIS FOR QUALITY CONTROL OF FOOD PRODUCTS. IMPORTANCE OF NORMALITY TESTING, PARAMETRIC AND NON-PARAMETRIC APPROACH, ASSOCIATION, CORRELATION AND LINEAR REGRESSION (MULTIPLE & MULTIVARIATE) OF DATA IN FOOD & BIO-PROCESS ENGINEERING. REGRESSION ANALYSIS METHODS FOR AGRI-FOOD QUALITY AND SAFETY EVALUATIONS USING NEAR-INFRARED (NIR) HYPERSPECTRAL IMAGING. PARTIAL LEAST SQUARE REGRESSION FOR FOOD ANALYSIS: BASIS AND EXAMPLE. MATHEMATICAL MODELLING OF HIGH PRESSURE PROCESS IN FOOD ENGINEERING. FOOD PROCESS MODELING AND OPTIMIZATION BY RESPONSE SURFACE METHODOLOGY (RSM). A MATHEMATICAL APPROACH TO THE MODELING OF THE RHEOLOGICAL PROPERTIES OF SOLID FOODS. MATHEMATICAL MODELS FOR ANALYZING THE MICROBIAL GROWTH IN FOOD. COMPUTATIONAL FLUID DYNAMICS (CFD) SIMULATIONS IN FOOD PROCESSING. APPLICATION OF MULTIVARIATE STATISTICAL ANALYSIS FOR FOOD SAFETY AND QUALITY ASSURANCE. MATHEMATICAL MODELLING IN FOOD SCIENCE THROUGH THE PARADIGM OF EGGPLANT DRYING. USE OF MATHEMATICAL MODELLING OF DOUGH BISCUITS BAKING BEHAVIOUR. APPLICATIONS OF PRINCIPAL COMPONENT ANALYSIS (PCA) FOR FRUIT JUICE RECOVERY　AND QUALITY ANALYSIS. USE OF ARTIFICIAL NEURAL NETWORKS IN OPTIMIZING FOOD PROCESSES. APPLICATION OF NEURAL NETWORKS IN OPTIMIZING DIFFERENT FOOD PROCESSES: CASE STUDY. MATHEMATICAL MODELLING FOR PREDICTING THE TEMPERATURES DURING MICROWAVE HEATING OF SOLID FOODS - A CASE STUDY. MICROWAVE DRYING OF FOOD MATERIALS MODELLED BY THE REACTION ENGINEERING APPROACH (REA) – FRAMEWORK. MODELLING OF HEAT TRANSFER DURING DEEP FAT FRYING OF FOOD.

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Written by experts from all over the world, the book comprises the latest applications of mathematical and models in food engineering and fermentation. It provides the fundamentals on statistical methods to solve standard problems associated with food engineering and fermentation technology.