This book is composed of 9 chapters，each focusing on a major non-destructive technique，including optical，acoustic and biological methods.The content of each chapter is based on the author's studies and current research developments.
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目录
Contents 1.1 Food Quality and Safety 2 1.2 Method for Food Quality and Safety Assessment 3 1.3 Nondestructive Measurement Technology in Food Science and Technology 4 References and Further Reading 8 2 Machine Vision Online Measurements 11 2.3 Image Processing 19 2.3.2 Image Interpretation and Classification 21 2.4 Applications ofMachine Vision in Food and Agricultural Products 22 2.4.2 0nline Machine VisionApplications 22 2.5 Machine Vision forApples Grading 26 2.5.1 Machine Vision System forApple Shape and Color Grading 26 2.5.2 Apples Defects Detection by Three-Color-Camera System 32 2.6 Machine Vision Online Sorting Maturity ofCherry Tomato 42 2.6.1 Hardware ofthe Detection System 42 2.7 Machine Vision Online Detection Quality of Soft Capsules 45 2.7.1 The Hardware ofSoft Capsule Online Grading System 46 3 NIR Spectroscopy Detection 57 3.2 A BriefReview of Regression Methods in NIR 61 3 .2. 1 Calibration and Validation 61 3.2.2 Multiple linear Regression, Principal Component Regression, and Partial Least-Squares Regression 63 3.3 Variable Selection Methods 66 3.3.1 ManualApproaches: Knowledge-Based Selection 68 3.3.2 Variable Selection by Single-Term Linear Regression and Multiterm Regression 69 3.3.3 Successive ProjectionsAlgorithm and Uninformative Variable Elimination 71 3.3.4 Simulated Annealing, Artificial Neural Networks 75 3.3.5 Interval Selection Method 86 3.3.6 0ther Wavelength Selection Methods and Software of Wavelength Selection Methods 94 3.4 Apple Soluble Solid Content Determination by NIR by Different iPLS Model 94 3.4.1 Apple NIR Spectroscopy Acquisition and Preprocessing 96 3.4.2 Determination ofApple SSC by Different PLS Models 102 3.4.3 Determination ofApple SSC by the most Predictive Models 106 3.5 Near-Infrared Quantitative Analysis of Pigment 109 3.5.1 Plant Material and NIRAcquisition 109 3.5.2 Quantitative Predication ofPigmentin Cucumber Leaves 111 3.5.3 Results Summary and Conclusion 117 4 Hyperspectrallmaging Detection 127 4.1.1 Spectral Band Usage and Chemicallmaging 129 4.1.2 Hyperspectrallmaging 132 4.2 HyperspectralImagesAcquisition andlnvestigation 133 4.2.1 HyperspectrallmageAcquisition 133 4.2.2 Hyperspectrallmage Preprocess 142 4.3 PCA and ICAAnalysis in Hyperspectral 143 4.3.1 PrincipalComponentAnalysis 145 4.3.2 Independent ComponentAnalysis 147 4.3.3 PCA and ICA in Spatial Way 148 4.3.4 PCA and ICA in Spectral Way 149 4.4 Applications for Food Quality and Safety Analysis 150 4.5 Hyperspectrallmaging for Quantitative Analysis of Pigments in Leaves 157 4.5.1 QuantitativeAnalysis of Pigments in Leaves 157 4.5.2 Hyperspectral Imaging Detection of Chlorophyll Distribution in Cucumber (Cucumis sativus) Leaves 159 4.5.3 Chlorophyll Spectrallndices for Quantity Determination 164 4.5.4 PCA and ICA in Information Extraction 170 4.5.5 Estimating Chlorophyll Concentration in each Pixel 173 4.6 Hyperspectrallmaging Detection of Total Flavonoids in Ginkgo Leaves 175 4.6.1 Fresh Ginkgo Leaf Samples and Total Flavonoid Content Determination 176 4.6.2 Acquisition ofHyperspectrallmages and Extraction 178 4.6.3 MLR Calibration Model of Total Flavonoid Content 178 5 Electronic Nose Measurements 195 5.1.1 Electronic Nose Mimics Human Olfaction 197 5.1.2 Structure of Electronic Nose 198 5.1.3 Applications ofElectronic Nose in Food Analysis 202 5.2.2 Semiconductive Gas Sensors 209 5.2.3 Silicon Carbide-Based Gas Sensors 211 5.2.4 Conducting Polymer-Based Sensors 212 5.2.5 Mechanical Sensor 214 5.2.6 Biosensor 216 5.3 Electronic Nose DataAnalysis 218 5.3.1 Preprocessing Techniques for Gas SensorArrays 220 5.3.2 Dimensionality Reduction 221 5.4 An Example of Electronic Nose in Apple Aroma Detection 227 5.4.1 Electronic Nose 227 5.4.2 Apple's Aroma Determined by Electronic Nose and Gas Chromatography Combined with Mass Spectrometry 229 5.4.3 Measure Results 231 6 Colorimetric Sensors Measurement 251 6.1.1 Fundamental Flaw ofNormal Electronic Nose Systems 252 6.1.2 0lfactory-Like Responses Converted to a Visual Output 253 6.1.3 Design ofa Colorimetric SensorArray 253 6.2 Porphyrins and Metalloporphyrins 255 6.2.1 The Chemical Properties ofPorphyrins and Metalloporphyrins 255 6.2.2 Metalloporphyrins, Supporting Materials and Corresponding Organic Compounds 257 6.3 Colorimetric Sensors Measurement System 261 6.3.4 Chemometrics, Reproducibility, and Resolution 264 6.3.5 Humiditylnterference 266 6.4 Colorimetric Sensors Measurements in the Vapor of Chemicals and Food 267 6.4.1 Colorimetric Sensors Measurements in Chemicals Vapor 267 6.4.2 Colorimetric Sensors Measurements in Food 268 6.4.3 Traditional Vinegars Identification by Colorimetric Sensor 270 6.4.4 Determination ofPork Spoilage by Colorimetric Gas SensorArray Based on Natural Pigments 276 7 Acoustic Measurements 289 7.1.1 The Perception ofSound 290 7.1.2 Basic Principles of Sound for Food Analysis 291 7.2 Sound MeasurementTechnique 294 7.2.1 Microphone Measurement Technique 294 7.2.2 Ultrasound MeasurementTechniques 295 7.2.3 Acoustic-Mechanical Methods 299 7.3 Acoustic SignalProcessing 300 7.3.1 Amplitude Analysis of Sound in Food 300 7.3.2 Frequency Analysis of Sounds in Food 301 7.3.3 0therAnalyses ofAcoustic Signatures in Food 302 7.3.4 Sound Analysis with Mechanical Data 302 7.4 Influence Factors on Sound in Food 304 7.4.1 Processing Conditions 304 7.4.2 Ingredients and Hydration 305 7.4.3 0ther Finished Product Properties 305 7.5 Acoustic Measurement in Food 306 7.5.1 Acoustic Measurement Used to Characterize Crisp,Crunchy, and Crackly Food 306 7.5.2 Ultrasound Measurement in Food 308 7.6 Example l: Eggshell Online Measurement by Acoustic Resonance 313 7.6.1 Eggs andAcoustic Resonance Detection 314 7.6.2 Results and Discussion 316 7.7 Example 2: Determination of Maturity and Juiciness of Melons by Ultrasound 321 7.7.1 Melons and the Tests ofElasticity, Ultrasound, Juiciness 322 7.7.2 Results and Discussion 327 7.8 Example 3: Measurement of Density, Ultrasonic Velocity, and Attenuation ofAdulterated Skim Milk 331 7.8.1 Milk and the Measurements ofParticle Size 332 8 Sensor Fusion Measurement 345 8.1 Introduction to Sensor Fusion 345 8.1.1 The Purpose ofSensor Management 346 8.1.2 The Role of Sensor Management in Information Fusion 347 8.1.3 Multisensor ManagementArchitectures 348 8.2 Sensor Fusion Method in Food and Agricultural Products 349 8.2.1 Attributes Associated with Organoleptic Properties (Step 1) 351 8.2.2 Reference Methods for Produce Quality 351 8.2.3 Nondestructive Methods for Produce Quality 348 8.2.4 DataAcquisition (Step 4) 352 8.2.5 Level ofRedundancy or Complementarity in the Nondestructive Sensors (Step 5) 352 8.2.6 Selecting and Applying the Proper Sensor Fusion 353 8.2.7 Evaluation ofthe Sensor Fusion System (Step 7) 356 8.2.8 Acceptance, Rejection, or Improvement of the Sensor Fusion System (Step 8) 356 8.3 Sensor Fusion in Food and Agricultural Products 357 8.4 Quality Assessment ofApples by Fusion Machine Vision,NIR Spectrophotometer, and EN Information 359 8.4.1 Three-SensorCombination System 360 8.4.2 Apple Quality Determination by Sensor Fusion Techniques 363 9 0ther Nondestructive Measurement Technologies 369 9.1.1 Transmissionlmaging Measurement 371 9.1.2 X-ray Computed Microtomography Measurement 373 9.1.3 X-ray Fluorescent Spectroscopy Measurement 374 9.1.4 Small-Angle X-ray Scattering Measurement 377 9.2 Raman Spectroscopy Technique 380 9.2.1 Introduction to Raman Spectroscopy in Food and Agro-products 381 9.2.2 Raman SpectroscopyEquipment 382 9.2.3 Raman Spectrospectry in Food and Agricultural Products 386 9.3 NuclearMagnetic Resonance 390 9.3.1 Principle ofNMR and MRIin Food Measurement 391 9.3.2 Application ofNMR Spectroscopy in Food 392 9.3.3 NMR Nuclear magnetic resonanceMRI 393 9.3.4 NMR Combined with Other Technologies 394 9.4 Terahertz Spectroscopy and Imaging 395 9.4.1 Terahertz Spectroscopy Systems 396 9.4.2 Terahertz Measurement in Food 398 9.4.3 Challenges and Limitations 399 Summary 400 Reference 401
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