1 Introduction
1.1 Food Quality and Safety
1.2 Method for Food Quality and Safety Assessment
1.3 Nondestructive Measurement Technology in Food Science and Technology
Summary
References and Further Reading
2 Machine Vision Online Measurements
2.1 Introduction
2.2 Images Acquisition System
2.2.1 LightingSystem
2.2.2 Camera
2.2.3 Lens
2.3 Image Processing
2.3.1 ImageSegmentation
2.3.2 Imagelnterpretation and Classificatio
2.4 Applications of Machine Vision in Food and Agricultural Products
2.4.1 Applications
2.4.2 Online Machine VisionApplications
2.5 Machine Vision forApples Grading
2.5.1 Machine Vision System for Apple Shape and Color Grading
2.5.2 Apples Defects Detection by Three-Color-Camera System
2.6 Machine Vision Online Sorting Maturity ofCherry Tomato
2.6.1 Hardware ofthe Detection System
2.6.2 Image Analysis
2.6.3 Sorting Results
2.7 Machine Vision Online Detection Quality of Soft Capsules
2.7.1 The Hardware of Soft Capsule Online Grading System
2.7.2 ImageProcess
2.7.3 Sorting Results
Summary
References
3 NIR Spectroscopy Detection
3.1 Introduction
3.2 A BriefReview ofRegression Methods in NIR
3.2.1 Calibration and Validation
3.2.2 Multiple linear Regression, Principal Component Regression, and Partial Least-Squares Regression
3.3 Variable Selection Methods
3.3.1 ManualApproaches: Knowledge-Based Selection
3.3.2 VariableSelectionbySingle-TermLinearRegression and Multiterm Regression
3.3.3 Successive ProjectionsAlgorithm and Uninformative Variable Eliminatio
3.3.4 Simulated Annealing, Artificial Neural Networks,and Genetic Algorithm ACO
3.3.5 Interval Selection Method
3.3.6 Other Wavelength Selection Methods and Software of Wavelength Selection Methods
3.4 Apple Soluble Solid Content Determination by NIR by Different iPL S Model
3.4.1 Apple NIR Spectroscopy Acquisition and Preprocessing
3.4.2 Determination ofApple SSC by Different PLS Models
3.4.3 Determination ofApple SSC by the most Predictive Models
3.5 Near-Infrared QuantitativeAnalysis of Pigment in Cucumber Leaves
3.5.1 Plant Materialand NIRAcquisitio
3.5.2 Quantitative Predication ofPigment in Cucumber Leaves
3.5.3 Results Summary and Conclusio
Summary
References
4 HyperspectralImagingDetection
4. 1 Introduction
4.1.1 Spectral Band Usage and Chemicallmaging
4.1.2 Hyperspectrallmaging
4.2 HyperspectralImagesAcquisitionandlnvestigation
4.2.1 HyperspectralImageAcquisitio
4.2.2 HyperspectrallmagePreprocess
4.3 PCA and ICAAnalysis in Hyperspectral
4.3.1 PrincipalComponentAnalysis
4.3.2 IndependentComponentAnalysis
4.3.3 PCA andICAin SpatialWay
……
5 Electronic Nose Measurements
6 Colorimetric Sensors Measurement
7 Acoustic Measurements
8 Sensor Fusion Measurement
9 Other Nondestructive Measurement Technologies
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