Several books have been written about the application of mathematical and statistical tools in food engineering, but very few books are actually focused or cover the topic in depth. These tools are essential in food engineering. Mathematical techniques have been used in process analysis, design and optimization from an empirical to a scientific and model-based approach. This book is a source of information on mathematical and statistical methods that can be applied in food engineering. The use of these techniques is also illustrated through case studies, which will make it easier for researcher in terms of development of alternative processes and their optimization in food engineering and technology.
With contributions from leading academics and scientists from all over the world, this book focuses on new areas of mathematical and statistical method for food engineering to help meet the increasing food demand. The book is easy to use. It will help researchers and students to overcome their apathy in using these tools, and to appreciate the usefulness of analytical tools. The book provides valuable resources for students, researchers, teachers and professionals of food engineering.
Key features:
- Provides detailed descriptions on engineering/ design/ modeling/ evaluation aspects of food engineering, from preparation to production to processing to consumption.
- Presents cutting-ege mathematical and statistical methods used for research in food engineering.
- Serves as an essential reference on the fundamental concepts of mathematical and statistical applications associated with food engineering.
- Combines theory with a practical exercise-driven approach, making it accessible to professionals with varying degrees of statistical skill
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| Preface |
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1 Role of Mathematical and Statistical Modelling in Food Engineering |
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1 | (4) |
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2 Evolutionary Optimization Techniques as Effective Tools for Process Modelling in Food Processing |
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5 | (16) |
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3 Optimization of Food Processes Using Mixture Experiments: Some Applications |
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21 | (15) |
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4 Microorganisms and Food Products in Food Processing Using Full Factorial Design |
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36 | (15) |
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Danijela Bursac Kovacevic |
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5 The Use of Correlation, Association and Regression Techniques for Analyzing Processes and Food Products |
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51 | (17) |
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6 Application of Cluster Analysis in Food Science and Technology |
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68 | (6) |
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7 Multiway Statistical Methods for Food Engineering and Technology |
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74 | (24) |
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8 Application of Multivariate Statistical Analysis for Quality Control of Food Products |
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98 | (14) |
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9 Importance of Normality Testing, Parametric and Non-Parametric Approach, Association, Correlation and Linear Regression (Multiple & Multivariate) of Data in Food & Bio-Process Engineering |
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112 | (15) |
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10 Regression Analysis Methods for Agri-Food Quality and Safety Evaluations Using Near-Infrared (NIR) Hyperspectral Imaging |
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127 | (14) |
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11 Partial Least Square Regression for Food Analysis: Basis and Example |
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141 | (20) |
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12 Mathematical Modelling of High Pressure Processing in Food Engineering |
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161 | (20) |
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13 Food Process Modeling and Optimization by Response Surface Methodology (RSM) |
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181 | (23) |
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14 A Mathematical Approach to the Modelling of the Rheological Properties of Solid Foods |
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204 | (20) |
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15 Mathematical Models for Analyzing the Microbial Growth in Food |
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224 | (19) |
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16 Computational Fluid Dynamics (CFD) Simulations in Food Processing |
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243 | (20) |
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17 Application of Multivariate Statistical Analysis for Food Safety and Quality Assurance |
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263 | (13) |
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18 Mathematical Modelling in Food Science through the Paradigm of Eggplant Drying |
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276 | (18) |
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19 Use of Mathematical Modelling of Dough Biscuits Baking Behaviour |
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294 | (13) |
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20 Applications of Principal Component Analysis (PCA) for Fruit Juice Recovery and Quality Analysis |
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307 | (14) |
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21 Use of Artificial Neural Networks in Optimizing Food Processes |
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321 | (25) |
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22 Application of Neural Networks in Optimizing Different Food Processes: Case Study |
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346 | (17) |
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23 Mathematical Modelling for Predicting the Temperatures During Microwave Heating of Solid Foods: A Case Study |
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363 | (26) |
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24 Microwave Drying of Food Materials Modelled by the Reaction Engineering Approach (REA)--Framework |
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389 | (9) |
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25 Modelling of Heat Transfer During Deep Fat Frying of Food |
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398 | (25) |
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| Index |
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423 | (2) |
| Color Section |
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425 | |
Surajbhan Sevda obtained a PhD in Biochemical Engineering & Biotechnology in 2013 from Indian Institute of Technology Delhi, New Delhi, India. He is currently an Assistant Professor at the Department of Biotechnology, National Institute of Technology, Warangal, India. Prior to this, he was a technical officer (research scientist) at IIT Guwahati, India. He has published more than 28 articles in scientific journals and book chapters. He received his Bachelor of Engineering in Biotechnology and Master of Technology in fermentation technology from University of Rajasthan and Institute of Chemical Technology (formerly UDCT), University of Mumbai, India, in 2006 and 2008, respectively. He was a visiting scientist at University of Calgary, Canada, in 2018. His research experience lies in industrial wastewater treatment, biofuels, and bioenergy, life cycle analysis (LCA), metal recovery, biosensor development, green chemistry, and microbial electrosynthesis.
Anoop Singh obtained a PhD in Botany in 2004. He is currently a Scientist at the Department of Scientific and Industrial Research (DSIR), Ministry of Science and Technology, Government of India. Before joining DSIR, he worked at DTU, Denmark; UCC, Ireland; TERI, New Delhi, India; IARI, New Delhi, India; BHU, Varanasi, India; and VBSPU, Jaunpur, India. He has more than fifty articles in scientific journals, has published five books, including two with Springer. He is a member of several scientific communities. His research interests are sustainable agriculture, the utilization of industrial, agricultural and household waste for eco-friendly energy production, and life cycle assessment.
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