Guide to Near-Infrared Spectroscopy

Name: Guide to Near-Infrared Spectroscopy
Brand: Nova
Price: 211.99 EUR
Availability: OnlineOnly

Francisco Garcia Martin Juan(Herausgeber*in)

Nova (Verlag)

Erschienen am 21. August 2023

223 Seiten

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979-8-88697-968-8 (ISBN)

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Inhalt

Intro
Contents
Preface
Chapter 1
Principles, Theories and Applications of Near-Infrared Spectroscopy for Food Quality and Safety Control
Abstract
Introduction
Theory
Instrumentation
Laboratory Stationary (i.e., Benchtop) NIR Spectrometer
Handheld and Micro NIR Spectrometers
Online NIR Spectrometer
Sample Presentation
Chemometrics
Spectral Data Pre-Processing
Classification Modelling
Principal Component Analysis (PCA)
Discriminant Analysis (DA)
Regression Modelling
Partial Least Square Regression (PLS)
Machine Learning Regression
Applications
Meat, Fish, and Fishery Products
Edible Oils, Milk and Dairy Products
Grains and Grain Products
Fruit and Vegetables
Future Directions
Conclusion
References
Chapter 2
The Current and Potential Roles of Near-Infrared Spectroscopy in the Digital Food Era
Abstract
Introduction
Current Applications of NIR Spectroscopy
Future and Potential Applications of NIR Spectrosopy in Food
Food Functionality
Food Security and Safety
Conclusion
References
Chapter 3
The Determination of Olive Oil's Moisture by a Hand-Held Near-Infrared Spectrometer
Abstract
Abbreviations
Olive Oil
Olive Cultivation
Economy and Market of Olive Oil
Relevance of Olive Oil
Physico-Chemical Parameters of Olive Oil
Moisture in Olive Oil
NIR Spectroscopy (NIRS)
NIRS Application to the Olive Oil Industry
Chemometrics
Stages of the Modeling Process
Data Pre-Treatment
Building of the Chemometric Model
Evaluation of the Calibration Model by the Validation Set
Parameters to Assess PLS-NIRS Results
Experimental Procedure
Olive Oils
Acquisition of NIR Spectra
Determination of the Moisture of VOO
Calculation of Standard Error of Laboratory (SEL)
Calibration Procedure
Results and Discussion
Moisture and Volatile Matter
NIR Spectra of VOOs
PLS Calibration Models
Development of the PLSLC Calibration Model
Development of the PLSCV Calibration Model
Prediction of Moisture in the Validation Set of Samples
Conclusion
References
Introduction
Main Components and Principal of Hyperspectral and Multispectral System
MSI Image Collection Using Multispectral Camera with Visible, Near Infrared and Thermal Waves
Spectral Image Analysis
Hyperspectral Image Acquisition and Principles
Multispectral Image Acquisition and Basic Principles
Radiometric Calibration
Image Processing and Extraction of Area of Interest
Predictive Modeling
Spectral Preprocessing
Variable Dimensionally Reduction and Featured Wavelength Selection
Application of HSI in Fruits and Vegetables
Application of MSI in Fruits and Vegetables
Conclusion
References
Chapter 5
The Prediction of Respiratory and Degradation Rates of Horticultural Crops by Near-Infrared Spectroscopy and Hyperspectral Imaging
Abstract
Introduction
Preservation Methods for Freshness of Horticultural Products
Relationship between Respiratory Enzymes and Degradation of Freshness
Measurement of the Respiratory Rate of Horticultural Crops
Relationship between Respiratory Enzymes and Light Absorption
Estimation of O2 Uptake Rate of Tomato Fruits by NIRS
Prediction of Degradation of Horticultural Crops by Hyperspectral Imaging
Conclusion
Acknowledgments
References
Introduction
NIR Spectroscopy System
Light Source
NIR Spectrometers
NIR Dispersive Spectrometer
NIR Fourier Transform Spectrometer, FT-NIR Spectrometer
NIR Linear Variable Filter (LVF) Spectrometer
NIR Diode Array Spectrometer
NIR Micro-Electro Mechanical (MEM) Spectrometer
Detector
NIR Si Photodetector
NIR Hyperspectral Image System
Near-Infrared Hyperspectral Image Principle
Components of the NIR Hyperspectral Image and Multispectral Systems
Tungsten Halogen Lamp
Xenon Lamp
Laser-Driven Light Source (LDLSTM)
Light Emitting Diode (LED) of Specific Band
Digital Camera or Area Detector
Image Spectrograph
Diffraction Gratings
The Prism-Grating-Prism Imaging Spectrograph
The Offner Spectrograph
The Czerny-Turner Spectrograph
Electronically Tunable Filter
Acousto-Optic Tunable Filter
Liquid Crystal Tunable Filter
Beam Splitter
Multivariate Analysis
Applications of NIR Spectroscopy, Hyperspectral, Multispectral Imaging in Energy Properties of Biomass
NIR Spectroscopy for Measurement of Energy Properties of Biomass
Rapid Elemental Composition Measurement of Commercial Pellets Using Line-Scan Hyperspectral Imaging Analysis
Machine Learning: Based Prediction of Selected Parameters of Commercial Biomass Pellets Using Line Scan Near-Infrared-Hyperspectral Imaging
A Low-Cost System for Moisture Content Detection of Bagasse Upon a Conveyor Belt with Multispectral Imaging and Various Machine Learning Methods
Conclusion
References
Chapter 7
The Determination of D-Xylose and Xylitol by Near-Infrared Spectroscopy Over the Fermentation of Olive Stone Hydrolysates
Abstract
Introduction
Application of NIRS to Fermentation Monitoring
Materials and Methods
Fermentation Samples
Reference Data
Spectra Acquisition
Calibration Procedure
Results and Discussion
Spectrum of the Fermentation Culture Medium
Prediction of D-Xylose by PLS-NIRS
Prediction of Xylitol by PLS-NIRS
Conclusion
References
Index
Editor's Contact Information
Chapter 4
Near-Infrared Hyperspectral and Multispectral Imaging Principles and Applications in the Quality of Fruits and Vegetables
Abstract
Chapter 6
Near-Infrared Spectroscopy, Hyperspectral, Multispectral Imaging Principles and Applications in Energy Properties of Biomass
Abstract
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