Near-Infrared Spectroscopy: Theory, Spectral Analysis, Instrumentation, and Applications

Preface
Contents
Part IIntroduction and Principles
1 Introduction
1.1 Discovery of Infrared (IR) Region
1.2 Introduction to NIR Spectroscopy
1.3 Brief History of NIR Spectroscopy
References
2 Principles and Characteristics of NIR Spectroscopy
2.1 Characteristics and Advantages of NIR Spectroscopy
2.1.1 Characteristics of NIR Spectroscopy
2.1.2 Characteristics of NIR Bands
2.1.3 Advantages of NIR Spectroscopy
2.1.4 Versatility of NIR Spectroscopy
2.1.5 Some Examples of NIR Spectra
2.1.6 Comparison of an NIR Spectrum with an IR Spectrum
2.2 Principles of NIR Spectroscopy
2.2.1 Principles of IR Spectroscopy
2.2.2 Molecular Vibrations
2.2.3 Anharmonicity
2.2.4 Overtones and Combination Modes
References
3 Theoretical Models of Light Scattering and Absorption
3.1 Early Explorations of Absorption, Scattering, and Extinction
3.2 The Application of Spectroscopy
3.3 The Physics of Light
3.4 Reflection and Refraction of Light at a Surface
3.5 Scatter from a Particle that is Bathed in a Beam
3.6 A Modeling Framework for Macroscopic Samples
3.7 The Schuster and Kubelka–Munk Equations
3.8 Quantifying Absorption, Transmission, and Remission in Plane Parallel Layers
3.9 The Representative Layer
3.10 Obtaining Linear Absorbance Data for Scattering Samples
References
Part IISpectral Analysis and Data Treatments
4 Spectral Analysis in the NIR Spectroscopy
4.1 Introduction to Spectral Analysis in the NIR Region
4.2 Conventional Spectral Analysis Method
4.3 Pretreatment Methods in NIR Spectroscopy
4.3.1 Noise Reduction Methods
4.3.2 Baseline Correction Methods
4.3.3 Resolution Enhancement Methods
4.3.4 Centering and Normalization Methods
References
5 Introduction to Quantum Vibrational Spectroscopy
5.1 Introduction
5.2 Normal Modes of Vibration
5.3 The Underlying Phenomena
5.3.1 The Potential Energy of a Molecular Oscillator
5.3.2 Quantum Chemical Methods for the Determination of the Electronic Structure of Molecular Systems
5.4 Harmonic Frequency Evaluation
5.4.1 Molecular Geometry Optimization Toward the Energy Minimum
5.4.2 Harmonic Approximation
5.5 Beyond the Harmonic Approximation
5.5.1 Anharmonic Approaches Formulated on the Basis of the Harmonic Approximation
5.5.2 Grid-Based Approaches
5.6 Applications of Anharmonic Approaches in NIR Spectroscopy
5.7 Summary and Future Prospects
References
6 Two-Dimensional Correlation Spectroscopy
6.1 Introduction
6.2 New Developments in Two-Dimensional Correlation Spectroscopy
6.2.1 Sample–Sample Correlation Spectroscopy
6.2.2 Perturbation-Correlation Moving-Window Two-Dimensional (PCMW2D) Correlation Spectroscopy
6.3 Applications of Two-Dimensional Correlation NIR Spectroscopy
References
7 NIR Data Exploration and Regression by Chemometrics—A Primer
7.1 Introduction
7.1.1 Dataset 1: Degree of Esterification in Pectins
7.1.2 Dataset 2: Glucose, Fructose and Sucrose Powder Mixture Design
7.1.3 Dataset 3: Authenticity of Gum Arabic
7.1.4 Dataset 4: Single-Seed NIR Spectra
7.2 Spectral Inspection and Pre-processing
7.2.1 Multiplicative Scatter Correction (MSC)
7.2.2 Spectral (Second) Derivatives
7.2.3 Application of Pre-processing to NIR Spectra
7.2.4 Outro
7.3 Unscrambling Spectral Mixtures by Self-Modeling Multivariate Curve Resolution (MCR)
7.3.1 Application of MCR to NIR Spectra
7.3.2 Outro
7.4 Spectral Exploration by Principal Component Analysis (PCA)
7.4.1 The PCA Method
7.4.2 Explained Variance
7.4.3 Application of PCA to NIR Spectra
7.4.4 PCA for Outlier Detection
7.4.5 PCA for Data Quality Control
7.4.6 Outro
7.5 Calibration by Partial Least Squares (PLS) Regression
7.5.1 Regression with Principal Components
7.5.2 Partial Least Squares Regression
7.5.3 Partial Least Squares Regression—Discriminant Analysis (PLS-DA)
7.5.4 Outro
7.6 Validation of Multivariate Models
7.6.1 Model Performance Metrics
7.6.2 Model Validation
7.6.3 Cross-Validation
7.6.4 Cross-Validation Systems
7.6.5 Bootstrapping
7.6.6 Test Set Validation
7.6.7 Application of PLS to NIR Spectra
7.6.8 Application of PLS-DA to NIR Spectra
7.6.9 Outro
7.7 Variable Selection in Regression
7.7.1 Regression Coefficients
7.7.2 Variable Importance in Projection
7.7.3 Forward Stepwise Selection
7.7.4 Recursively Weighted PLS (rPLS)
7.7.5 Interval PLS (iPLS)
7.7.6 Outro
7.8 ANOVA Simultaneous Component Analysis (ASCA)
7.8.1 Application of ASCA to NIR Spectra
7.8.2 Outro
7.9 Process Analytical Technology, Machine Learning and Other NIRS Trends
References
Part IIIInstrumentation
8 New Trend in Instrumentation of NIR Spectroscopy—Miniaturization
8.1 General Introduction
8.1.1 Basic Technology Design of NIR Spectrometers
8.1.2 Overview of the Technological Advancements in Miniaturized NIR Spectrometers
8.2 The Principles of the Technology Underlying Miniaturized NIR Spectroscopy
8.2.1 Light Sources
8.2.2 Detectors
8.2.3 Wavelength Selectors
8.3 Application and In-depth Evaluation of Performance Characteristics of Portable NIR Spectrometers
8.3.1 Example of an Application Where Differences Between Performances of Portable Instruments (Based on Different Designs) and a Benchtop Spectrometer Were Demonstrated
8.3.2 Example of an Application Where an Ultra-miniaturized and Affordable NIR Spectrometer Performed Semi-comparably with a Benchtop Instrument
8.4 The Conclusions and Prospects for Future
References
9 NIR Optics and Measurement Methods
9.1 Optics
9.1.1 Device Configuration
9.1.2 Near-Infrared Light Sources
9.1.3 Spectroscopic Elements
9.1.4 Detector
9.1.5 Other Optical Materials
9.2 Measuring Methods of NIR Spectroscopy
9.2.1 Outline of NIR Measuring Methods
9.2.2 Sample Pretreatments and Measurement Conditions
References
10 Hardware of Near-Infrared Spectroscopy
10.1 Noise Reduction Technology of the NIR Spectrometer
10.1.1 Noise and NIR Spectroscopy
10.1.2 Noise Reduction Using the FRS Method
10.1.3 Noise Reduction in a Linear Array Spectrometer
10.1.4 Noise Caused by Wavelength Accuracy and Repeatability
10.2 Grating Spectrometer
10.2.1 Wavelength Scanning Grating Spectrometer
10.2.2 Spectrometer with a Linear Array Detector
10.2.3 Hadamard Spectrometer
10.2.4 Wavelength Resolution and Measurement Interval
10.3 Designing a NIR Spectrometer for Special Materials
10.3.1 The First Step: Test Measurement
10.3.2 The Second Step: Determining the Specification
10.3.3 The Third Step: Manufacturing
10.4 Instrumental Differences
10.4.1 Effect of Instrumental Differences
10.4.2 Instrumental Differences Caused by the Sampling Optics
10.4.3 Instrumental Differences Caused by the Spectral Sensitivity and Slit Function
10.4.4 Considerations to Avoid Instrumental Differences
10.4.5 Standardization Methods for the Calibration
References
11 Time-of-Flight Spectroscopy
11.1 Introduction
11.2 Measuring Apparatus
11.3 Data Analysis
11.4 Application of TOF-NIRS to Agricultural Science
11.5 Application of TOF-NIRS to Medical Science
11.6 Application of TOF-NIRS to Forest Products
11.7 Brief Explanation for SR Spectroscopy
11.8 New Measurement System Minimizing the Effect of Light Scattering.
References
12 Method Development
12.1 Introduction
12.2 General Procedure for Method Development, Validation, and Lifecycle
12.3 Analytical Quality by Design (AQbD)
12.3.1 Introduction to AQbD
12.3.2 Analytical Target Profile
12.3.3 Feasibility Study
12.3.4 Risk Assessment
12.3.5 Method Development
12.3.6 Method Testing and Validation
12.3.7 Referencing, System Suitability, and Performance Monitoring
12.4 Method Lifecycle
12.5 Additional Considerations for Multipoint Systems
12.6 Summary
References
Part IVApplications
13 Overview of Application of NIR Spectroscopy to Physical Chemistry
13.1 Introduction
13.2 Hydrogen Bonding Studies
13.3 Anharmonic Effects in Vibrational Spectroscopy
13.4 Structural Information Derived from NIR Spectra
13.5 Solution Chemistry
13.6 Summary and Future Perspective
References
14 Application of NIR in Agriculture
14.1 Introduction
14.2 Applications in the Field and Crop Analysis
14.2.1 Soil Analysis by NIR—A Technique in Development
14.2.2 Crop Analysis—Direct Analysis in the Field or Laboratory Analysis to Support Farmers and Breeders
14.3 Applications on Farm Products or Effluents
14.3.1 An Efficient Tool to Assess Forage and Silage Quality for Precision Feeding
14.3.2 Determination of Key Parameters and Detection of Contaminants/Impurities in Feed
14.3.3 A Tool to Assess the Quality of Dairy Products and to Track Milk Quality in the Milking Parlour
14.3.4 Analysis of Faeces and Farm Effluent, A Way to Optimise Their Valuation
14.4 Applications in the Orchard and in the Fruit Sector
References
15 Applications: Food Science
15.1 Introduction
15.2 Cereals and Cereal Products
15.3 Meat and Meat Products
15.4 Fish and Fish Products
15.5 Milk and Milk Products
15.6 Vegetable and Olive Oils
15.7 Fruit and Vegetables
15.8 Honey
15.9 Tea
15.10 Coffee
15.11 Wine and Distilled Alcoholic Beverages
15.12 Beer
15.13 Aquaphotomics
15.14 Conclusion
References
16 Wooden Material and Environmental Sciences
16.1 Introduction
16.2 Wood
16.2.1 Wood Chemical Composition
16.2.2 Wood Moisture Content
16.2.3 Wood Density
16.2.4 Wooden Anatomical Features
16.2.5 Wood Mechanical Properties
16.2.6 Wood Engineering Wood
16.2.7 Wood Modification and Degradation
16.2.8 Wood Pulp and Paper
16.2.9 Wood Species Classification
16.2.10 Imaging Analysis at the Field of Wood
16.3 Soil
16.4 Sediment
16.5 Wastewater
16.6 Atmospheric Gas Detection
16.7 Archeological Science
16.8 Conclusion
References
17 Information and Communication Technology in Agriculture
17.1 NIR Network System
17.2 Assisting Smart Agriculture in Sugarcane Production
17.3 Combining NIR System with a GIS
17.4 On-Site Analysis for Agriculture
17.5 Advanced Unique Applications
References
18 Near-Infrared Spectroscopy in the Pharmaceutical Industry
18.1 Introduction
18.2 ICH Guidance, Validation Principles, and Lifecycle Management
18.3 Large Molecules
18.3.1 Bioreactor Monitoring and Control
18.3.2 Lyophilization
18.3.3 Summary
18.4 Small Molecules
18.4.1 Drug Substance Manufacturing
18.4.2 Drug Product Manufacturing
18.4.3 Summary
18.5 Raw Material Identification
18.6 Summary
References
19 Bio-applications of NIR Spectroscopy
19.1 Introduction
19.2 Medicinal Plant Analysis
19.3 Cell Analysis
19.4 Serum Analysis
19.5 Saliva Analysis
19.6 Tissue Analysis
19.7 Hemodialysis Analysis
19.8 Examination of Entire Organisms
19.9 NIR Studies of the Structure, Properties and Interactions of Biomolecules
19.10 Selected Other Applications
19.11 Conclusions
References
20 Medical Applications of NIR Spectroscopy
20.1 Introduction
20.2 Applications in Clinical Chemistry
20.2.1 Analysis of Blood and Other Bodyfluids
20.3 Applications of Non-invasive Technology in Clinical Chemistry
20.3.1 Non-invasive Technology for Glucose Monitoring
20.3.2 NIR Spectroscopy of Skin–Optical Data for Photon Migration Modeling
20.3.3 Non-invasive Technology for Hemoglobin and Blood Ethanol Monitoring
20.4 NIR Spectroscopy for Tissue Analysis
20.4.1 Applications for Spectral Histopathology
20.4.2 Monitoring of Blood-Tissue Oxygenation and Cytochrome Redox Status
20.4.3 Non-invasive Pulsatile NIR Spectroscopy
20.5 Applications of NIR-Fluorescence in Biomedicine
20.6 Concluding Remarks
References
21 Applications of NIR Techniques in Polymer Coatings and Synthetic Textiles
21.1 Introduction
21.2 Polymer Coatings and Printed Layers
21.2.1 Specific Challenges of the Analysis of Coatings and Other Thin Layers by NIR Spectroscopy
21.2.2 Monitoring of the Thickness of Coatings by NIR Spectroscopy
21.2.3 Conversion of UV-Cured Coatings
21.2.4 Hyperspectral Imaging of UV-Cured Coatings
21.2.5 Spectroscopic Techniques in Printing Technology
21.3 Synthetic Fibers and Textiles
21.3.1 Classification of Textile Fabrics
21.3.2 Quality Control in Fiber and Textile Production
21.3.3 Finishing of Yarns and Textiles and Subsequent Drying
21.3.4 Lamination of Textiles
21.4 Conclusion
References
22 NIR Imaging
22.1 Introduction
22.2 Instrumentation
22.2.1 General Features of NIR Imaging Device
22.2.2 Spectral Image Acquisition
22.2.3 Development of Instrument
22.3 Applications of NIR Imaging
22.3.1 Food-Related Applications
22.3.2 Contaminant Detection in Foods
22.3.3 Food Authentication
22.3.4 Food Quality Control
22.4 Pharmaceutical-Related Applications
22.4.1 Blend Process Monitoring [22]
22.4.2 Water Penetration Monitoring [23]
22.4.3 Investigation of Inhomogeneity During the Grinding Process [24]
22.4.4 Identification of Defective Tablets [25]
22.5 Polymer-Related Applications
22.5.1 Polymer Crystallinity Evaluation [26]
22.5.2 Biodegradable Polymer Evaluation [29, 30]
22.5.3 Monitoring of Biopolymer Photodegradation [31]
22.6 Bioscience-Related Applications
22.6.1 Application of Three Types of NIR Imaging System to Biology
22.6.2 NIR Imaging of Fish Egg Embryogenesis
22.6.3 High-Speed NIR Imaging of Fish Egg Embryogenesis
22.6.4 Blood Flow Imaging of Fish Egg Embryos
References
23 Inline and Online Process Analytical Technology with an Outlook for the Petrochemical Industry
23.1 Process Analytical Technology (PAT): A Systems Approach
23.1.1 Road Map for PAT
23.1.2 Taxonomy of Process Analyzers and Sampling
23.2 Future Concepts in the Process and Manufacturing Industry: Industrie 4.0, Industrial Internet of Things, and Their Impact on PAT Sensors
23.2.1 Concepts for the Next Generation of Production Systems
23.2.2 Industrial Internet Reference Architectural Model of Industrie 4.0: RAMI 4.0
23.2.3 Communication Between Cyber-Physical PAT Systems: Connected, Multimodal, Decentralized, and Secured
23.3 Robustness in PAT Applications with a Focus on NIR Spectroscopy: About Sensitivity, Selectivity, and Signal-to-Noise
23.3.1 General Approach to Optical Spectroscopy in PAT and Their Advantages
23.3.2 Sensitivity: Definition at Molecular Level and Classification of NIRS Within the Spectroscopic Toolbox
23.3.3 Selectivity: Classification of NIRS Within the Spectroscopic Toolbox
23.3.4 Robustness, Detection Limit (DL), and Signal-To-Noise Ratio (SNR)
23.4 Inline Spectroscopy of Liquids: Interfacing with Probes
23.4.1 Synopsis and Taxonomy of Probes
23.4.2 Retractable Probes for Cleaning in Place (CIP) and Working with Highly Toxic or Aggressive Media
23.5 Inline Spectroscopy of Surfaces, Thin Films, and Particulate Systems
23.5.1 Separation of Specular and Diffuse Reflectance in PAT Applications Using Polarization Spectroscopy
23.5.2 Penetration Depth of Specular and Diffuse Reflected Light
23.5.3 Robustness of the Inline Measurement Setup for Solids: Diffuse Illumination
23.6 PAT in the Petrochemical Industry as an Example for Inline Process Control
23.6.1 Petrochemical Industry
23.6.2 Objectives for the Integration of PAT Sensors in a Refinery and Future Smart Production
23.6.3 NIR Spectroscopy for the Petrochemical Industry
23.7 How to Run a PAT Project
23.7.1 Concept for a Knowledge-Based Production: Understanding Your Process on a Molecular Level
23.7.2 Final Functionality Test of the PAT Spectroscopic System for Long-Term Operation
23.7.3 Conclusion
Literature