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

This book provides knowledge of the basic theory, spectral analysis methods, chemometrics, instrumentation, and applications of near-infrared (NIR) spectroscopy--not as a handbook but rather as a sourcebook of NIR spectroscopy. Thus, some emphasis is placed on the description of basic knowledge that is important in learning and using NIR spectroscopy. The book also deals with applications for a variety of research fields that are very useful for a wide range of readers from graduate students to scientists and engineers in both academia and industry. For readers who are novices in NIR spectroscopy, this book provides a good introduction, and for those who already are familiar with the field it affords an excellent means of strengthening their knowledge about NIR spectroscopy and keeping abreast of recent developments. 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