Automation for food engineering: food quality quantization and process control

Yanbo Huang, A. Dale Whittaker, Ronald E. Lacey0849322308, 9780849322303

In the past ten years electronics and computer technologies have significantly pushed forward the progress of automation in the food industry. The application of these technologies to automation for food engineering will produce more nutritious, better quality, and safer items for consumers. Automation for Food Engineering: Food Quality Quantization and Process Control explores the usage of advanced methods, such as wavelet analysis and artificial neural networks, to automated food quality evaluation and process control. It introduces novel system prototypes, such as machine vision, elastography, and the electronic nose, for food quality measurement, analysis, and prediction. The book discusses advanced techniques, such as medical imaging, mathematical analysis, and statistical modeling, which have proven successful in food engineering. The authors use the characteristics of food processes to describe concepts, and they employ data from food engineering applications to explain the methods. To aid in the comprehension of technical information, they provide real-world examples and case studies from food engineering projects.The material covers the frameworks, techniques, designs, algorithms, tests and implementation of data acquisition, analysis, modeling, prediction, and control in automation for food engineering. It demonstrates the techniques for automation of food engineering, and helps you in the development of techniques for your own applications. Automation for Food Engineering: Food Quality Quantization and Process Control is the first and only book that gives a systematical study and summary about concepts, principles, methods, and practices in food quality quantization and process control.

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Table of contents :
AUTOMATION for FOOD ENGINEERING: Food Quality Quantization and Process Control……Page 3
Dedication……Page 5
Outline of the Book……Page 6
Acknowledgments……Page 9
About the Authors……Page 10
Contents……Page 11
1.2 Automated evaluation of food quality……Page 15
Table of Contents……Page 0
1.3 Food quality quantization and process control……Page 16
1.4.1 Beef quality evaluation……Page 21
1.4.3 Continuous snack food frying quality process control……Page 22
References……Page 24
2.1 Sampling……Page 25
2.1.1 Example: Sampling for beef grading……Page 27
2.1.2 Example: Sampling for detection of peanut off-flavors……Page 30
2.1.3 Example: Sampling for meat quality evaluation……Page 33
2.1.4 Example: Sampling for snack food eating quality evaluation……Page 34
2.1.5 Example: Sampling for snack food frying quality process control……Page 35
2.2 Concepts and systems for data acquisition……Page 36
2.2.1 Example: Ultrasonic A-mode signal acquisition for beef grading……Page 40
2.2.2 Example: Electronic nose data acquisition for food odor measurement……Page 42
2.2.3 Example: Snack food frying data acquisition for quality process control……Page 45
2.3 Image acquisition……Page 47
2.3.1 Example: Image acquisition for snack food quality evaluation……Page 48
2.3.2 Example: Ultrasonic B-mode imaging for beef grading……Page 50
2.3.3 Example: Elastographic imaging for meat quality evaluation……Page 51
References……Page 57
3.1 Data preprocessing……Page 62
3.2.1 Static data analysis……Page 67
3.2.1.1 Example: Ultrasonic A-mode signal analysis for beef grading……Page 69
3.2.1.2 Example: Electronic nose data analysis for detection of peanut off-flavors……Page 76
3.2.2 Dynamic data analysis……Page 79
3.2.2.1 Example: Dynamic data analysis of the snack food frying process……Page 81
3.3.1 Image segmentation……Page 84
3.3.2 Image feature extraction……Page 87
3.3.2.1 Example: Morphological and Haralick’s statistical textural feature extraction from images………Page 100
3.3.2.2 Example: Feature extraction from ultrasonic B-mode images for beef grading……Page 102
3.3.2.4 Example: Wavelet textural feature extraction from meat elastograms……Page 103
References……Page 110
4.1.1 Theoretical and empirical modeling……Page 112
4.1.2 Static and dynamic modeling……Page 114
4.2 Linear statistical modeling……Page 117
4.2.1 Example: Linear statistical modeling based on ultrasonic A-mode signals for beef grading……Page 126
4.2.2 Example: Linear statistical modeling for food odor pattern recognition by an electronic nose……Page 127
4.2.3 Example: Linear statistical modeling for meat attribute prediction based on textural featur………Page 128
4.2.4 Example: Linear statistical dynamic modeling for snack food frying process control……Page 130
4.3 ANN modeling……Page 134
4.3.1 Example: ANN modeling for beef grading……Page 143
4.3.2 Example: ANN modeling for food odor pattern recognition by an electronic nose……Page 144
4.3.3 Example: ANN modeling for snack food eating quality evaluation……Page 145
4.3.4 Example: ANN modeling for meat attribute prediction……Page 146
4.3.5 Example: ANN modeling for snack food frying process control……Page 150
References……Page 153
5.1 Prediction and classification……Page 155
5.1.1 Example: Sample classification for beef grading based on linear statistical and ANN models……Page 156
5.1.2 Example: Electronic nose data classification for food odor pattern recognition……Page 158
5.1.3 Example: Snack food classification for eating quality evaluation based on linear statistica………Page 160
5.1.4 Example: Meat attribute prediction based on linear statistical and ANN models……Page 161
5.2 One-step-ahead prediction……Page 162
5.2.1 Example: One-step-ahead prediction for snack food frying process control……Page 164
5.3 Multiple-step-ahead prediction……Page 166
5.3.1 Example: Multiple-step-ahead prediction for snack food frying process control……Page 174
References……Page 177
6.1 Process control……Page 179
6.2 Internal model control……Page 180
6.2.1 Example: ANNIMC for the snack food frying process……Page 191
6.3 Predictive control……Page 196
6.3.1 Example: Neuro-fuzzy PDC for snack food frying process……Page 208
References……Page 212
7.1 Food quality quantization systems integration……Page 213
7.2 Food quality process control systems integration……Page 215
7.3 Food quality quantization and process control systems development……Page 219
7.4 Concluding remarks……Page 223
References……Page 224