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Automation for Food Engineering: Food Quality Quantization and Process Control
by: Yanbo Huang
Topics include: food frying process, food quality quantization, food quality process control, ultrasonic elastograms, statistical textural features, carcass maturity, process prediction model, process output vector, snack object, meat quality evaluation, neural network process model, cured peanuts, ith hidden node, textural feature extraction, food quality evaluation, network hidden nodes, setpoint tracking, beef marbling, smoothed component, marbling score, shear probe, snack quality, attribute prediction, percent wet basis, ultrasonic speed
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Illustrates the application of electronics and computer technologies with real-world examples
Contains line drawings, tables, micrographs, and equations that make the information easily accessible
Introduces the frameworks, techniques, design, algorithms, tests, and implementation in data acquisition, analysis, modeling, prediction, and control in automation for food engineering
Demonstrates the techniques for automation of food engineering
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.
Table of Contents
Introduction
Food Quality: A Primary Concern of Food Industry
Automated Evaluation of Food Quality
Food Quality Quantization and Process Control
Typical Problems in Food Quality Evaluation and Process Control
How to Learn the Technologies
Data Acquisition
Sampling
Concepts and Systems for Data Acquisition
Image Acquisition
Data Analysis
Data Pre-Processing
Data Analysis
Image Processing
Modeling
Modeling Strategy
Linear Statistical Modeling
ANN Modeling
Prediction
Prediction and Classification
One-Step-Ahead Prediction
Multiple-Step-Ahead Prediction
Control
Process Control
Internal Model Control
Predictive Control
Systems Integration
Food Quality Quantization Systems Integration
Food Quality Process Control Systems Integration
Food Quality Quantization and Process Control Systems Development
Concluding Remarks
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