Advances in Biopolymers for Food Science and Technology brings together the latest techniques for the preparation of bio-based polymeric materials, for novel food applications.The book begins by introducing biopolymers and their various polysaccharide and protein sources, addressing biopolymers from marine sources in particular. Food design using biopolymers, and their preparation as gels and composites are then discussed in detail. This is followed by in-depth chapters guiding the reader through specific applications, including fat replacement products, delivery systems, food emulsions, micro- and nano-encapsulation, nanovehicles, nanostructures, nanofilms, antimicrobial peptides, food coatings, food packaging, smart monitoring, cryoprotection, and cultured meat production. Finally, the various challenges regarding sustainability of food packaging are addressed.This is a valuable resource for researchers and advanced students across polymer science, food science, chemistry, packaging, nanotechnology, and materials science, as well as industrial scientists and R&D professionals with an interest in biopolymers for advanced applications in food products and packaging.
1. Chapter 1 Introduction - p. 1 2. Chapter 2 Artificial neural network - p. 7 3. Chapter 3 Support vector machines - p. 47 4. Keywords - p. 47 5. 3.1 Introduction - p. 47 6. 3.2 Support vector classification (SVC) - p. 47 7. 3.3 Support vector regression (SVR) - p. 79 8. 3.4 MATLAB coding - p. 92 9. 3.5 Summary - p. 103 10. References - p. 103 11. Chapter 4 Fuzzy logic - p. 105 12. Chapter 5 Rough set - p. 143 13. Chapter 6 Nature-inspired optimization algorithms - p. 171 14. Keywords - p. 171 15. 6.1 Introduction - p. 171 16. 6.2 Genetic algorithm (GA) - p. 171 17. 6.3 Particle swarm optimization (PSO) - p. 200 18. 6.4 Ant colony optimization (ACO) - p. 207 19. 6.5 MATLAB coding - p. 224 20. 6.6 Summary - p. 230 21. References - p. 231 22. Chapter 7 Hybrid artificial intelligence systems - p. 233 23. Keywords - p. 233 24. 7.1 Introduction - p. 233 25. 7.2 ANFIS - p. 233 26. 7.3 GFES - p. 256 27. 7.4 MATLAB coding - p. 276 28. 7.5 Summary - p. 293 29. References - p. 293 30. Index - p. 295
Advances in Biopolymers for Food Science and Technology brings together the latest techniques for the preparation of bio-based polymeric materials, for novel food applications.The book begins by introducing biopolymers and their various polysaccharide and protein sources, addressing biopolymers from marine sources in particular. Food design using biopolymers, and their preparation as gels and composites are then discussed in detail. This is followed by in-depth chapters guiding the reader through specific applications, including fat replacement products, delivery systems, food emulsions, micro- and nano-encapsulation, nanovehicles, nanostructures, nanofilms, antimicrobial peptides, food coatings, food packaging, smart monitoring, cryoprotection, and cultured meat production. Finally, the various challenges regarding sustainability of food packaging are addressed.This is a valuable resource for researchers and advanced students across polymer science, food science, chemistry, packaging, nanotechnology, and materials science, as well as industrial scientists and R&D professionals with an interest in biopolymers for advanced applications in food products and packaging.
1. Chapter 1 Introduction - p. 1 2. Chapter 2 Artificial neural network - p. 7 3. Chapter 3 Support vector machines - p. 47 4. Keywords - p. 47 5. 3.1 Introduction - p. 47 6. 3.2 Support vector classification (SVC) - p. 47 7. 3.3 Support vector regression (SVR) - p. 79 8. 3.4 MATLAB coding - p. 92 9. 3.5 Summary - p. 103 10. References - p. 103 11. Chapter 4 Fuzzy logic - p. 105 12. Chapter 5 Rough set - p. 143 13. Chapter 6 Nature-inspired optimization algorithms - p. 171 14. Keywords - p. 171 15. 6.1 Introduction - p. 171 16. 6.2 Genetic algorithm (GA) - p. 171 17. 6.3 Particle swarm optimization (PSO) - p. 200 18. 6.4 Ant colony optimization (ACO) - p. 207 19. 6.5 MATLAB coding - p. 224 20. 6.6 Summary - p. 230 21. References - p. 231 22. Chapter 7 Hybrid artificial intelligence systems - p. 233 23. Keywords - p. 233 24. 7.1 Introduction - p. 233 25. 7.2 ANFIS - p. 233 26. 7.3 GFES - p. 256 27. 7.4 MATLAB coding - p. 276 28. 7.5 Summary - p. 293 29. References - p. 293 30. Index - p. 295
