Food quality analysis : applications of analytical methods coupled with artificial intelligence

Food quality analysis applications of analytical methods coupled with artificial intelligence

Detalles Bibliográficos
Otros Autores: Shukla, Ashutosh Kumar, editor (editor)
Formato: Libro electrónico
Idioma:Inglés
Publicado: London : Academic Press [2023]
Materias:
Artificial intelligence > Industrial applications.
Food > Analysis.
Food industry and trade > Quality control.
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009835428706719
Tabla de Contenidos:
  • Front Cover
  • Food Quality Analysis
  • Copyright Page
  • Contents
  • List of contributors
  • Preface
  • 1. Importance of food quality analysis in relation to food safety and human health and COVID-19 in particular
  • 1.1 Introduction
  • 1.2 Importance of food quality analysis
  • 1.3 Compositional analysis of foods
  • 1.3.1 Moisture analysis
  • 1.3.2 Fat analysis
  • 1.3.3 Protein analysis
  • 1.3.4 Carbohydrate analysis
  • 1.3.5 Vitamin analysis
  • 1.3.6 Mineral analysis
  • 1.4 Chemical analysis of foods
  • 1.4.1 pH analysis
  • 1.4.2 Enzyme analysis
  • 1.4.3 Food contaminants analysis
  • 1.4.3.1 Pesticide analysis
  • 1.4.3.2 Mycotoxin analysis
  • 1.5 Importance of food analysis in relation to COVID-19
  • 1.5.1 Food safety management in COVID-19 era
  • 1.5.2 SARS-CoV-2 virus analysis
  • 1.6 Future prospects
  • 1.7 Conclusions
  • References
  • 2. Fourier transform infrared spectroscopy combined with multivariate analysis for quality analysis of fats and oils
  • 2.1 Introduction
  • 2.2 Fourier transform infrared spectroscopy and chemometrics
  • 2.3 Analysis of fat and oil components
  • 2.4 Determination of fat and oil parameters using Fourier transform infrared spectroscopy
  • References
  • 3. Fluorescence spectroscopy for beer quality analysis
  • 3.1 Introduction
  • 3.2 Concept of fluorescence
  • 3.3 Characteristics of fluorescence
  • 3.4 Factors affecting fluorescence phenomenon
  • 3.5 Fluorescence spectra and its types
  • 3.5.1 Total luminescence spectra
  • 3.5.2 Excitation spectra
  • 3.5.3 Emission spectra
  • 3.5.4 3D fluorescence spectra
  • 3.5.5 Synchronous fluorescence spectra
  • 3.5.5.1 Right-angled fluorescence
  • 3.5.5.2 Front-face fluorescence
  • 3.6 Phenomena of fluorescence scattering
  • 3.6.1 Raman scattering
  • 3.6.2 Rayleigh scattering
  • 3.7 Fluorescence geometry of beer
  • 3.8 Beer constituents having fluorescent properties.
  • 3.9 Application of fluorescence spectroscopy in beer
  • 3.9.1 Stratification of beer
  • 3.9.2 Bitterness of beer
  • 3.9.3 Vitamin B analysis of beer
  • 3.9.4 Storage analysis of beer
  • 3.10 Quality analysis of beer using PARAFAC model
  • 3.11 Conclusions
  • References
  • 4. Raman spectroscopy combined with multivariate analysis in quality analysis of food and pharmaceutical materials
  • 4.1 Introduction
  • 4.2 Principles of Raman spectroscopy
  • 4.3 Raman signal
  • 4.4 Types of Raman spectroscopy used for food analysis
  • 4.4.1 Micro Raman spectroscopy
  • 4.4.2 Raman imaging
  • 4.4.3 Surface-enhanced Raman spectroscopy
  • 4.4.4 Near-infrared Raman spectroscopy
  • 4.4.5 Fourier transform Raman spectroscopy
  • 4.4.6 Spatial offset Raman spectroscopy
  • 4.4.7 Raman spectral analysis
  • 4.5 Raman spectroscopy to detect the hazards caused by biological agents
  • 4.6 Multivariate analysis
  • 4.7 Raman spectroscopy for detection of food
  • 4.7.1 Raman for milk analysis
  • 4.7.2 Raman spectroscopy for butter and margarine
  • 4.7.3 Raman spectroscopy for yogurt
  • 4.7.4 Raman spectroscopy for meat analysis
  • 4.7.5 Raman for olive oil
  • 4.7.6 Raman spectroscopy for beverages
  • 4.7.7 Wine analysis
  • 4.8 Detection of chemicals using Raman analysis
  • 4.9 Raman detection for pharmaceuticals
  • 4.10 Raman to detect nanomaterials
  • 4.11 Raman analysis to prevent physical hazards
  • 4.12 Future perspective
  • Acknowledgments
  • References
  • 5. Chromatographic methods for the analysis of oils and fats
  • 5.1 Introduction
  • 5.2 Quality assessment of oils and fats
  • 5.3 Chromatographic based techniques
  • 5.3.1 Application of TLC for quality control of edible fats and oils
  • 5.3.1.1 Qualitative analysis
  • 5.3.1.2 Quantitative analysis
  • 5.3.2 GC-FID and GC-MS for quality assessment of fats and oils
  • 5.3.2.1 General principle.
  • 5.3.2.2 General official methods
  • 5.3.2.2.1 Fatty acid composition
  • 5.3.2.2.1.1 USP-NF &lt
  • 401&gt
  • 5.3.2.2.1.2 EP 10
  • 5.3.2.2.2 Sterols composition
  • 5.3.2.2.2.1 USP-NF
  • 5.3.2.2.2.2 EP 10
  • 5.3.2.2.3 Omega-3 fatty acid determination and profiles
  • 5.3.2.3 Application of gas chromatographic methods for quality assessment of fats and oils
  • 5.3.3 LC and related techniques for analysis of fats and oils
  • 5.3.3.1 Standard methods for quality assessment
  • 5.3.3.2 Application of liquid chromatographic methods for quality assessment of fats and oils
  • 5.4 Conclusions, recommendations, and future trends
  • Acknowledgement
  • References
  • 6. Gas chromatography and multivariate analysis for wheat flours
  • 6.1 Introduction
  • 6.2 Wheat grain compositions
  • 6.3 Wheat flour
  • 6.4 The standard for wheat flour
  • 6.5 Quality assessment of wheat and wheat-based products
  • 6.6 Application of gas chromatography coupled with mass spectroscopy
  • 6.6.1 Gas chromatography coupled with mass spectroscopy analytical procedures
  • 6.6.1.1 Extraction techniques
  • 6.6.1.2 Derivatization
  • 6.6.1.3 Chromatographic techniques
  • 6.6.1.4 GC-MS data processing and statistical analysis
  • 6.7 Application of gas chromatography coupled with mass spectroscopy and multivariate analysis in quality analysis of wheat...
  • 6.7.1 Gas chromatography coupled with mass spectroscopy in analysis of wheat components/chemical composition
  • 6.7.2 Gas chromatography coupled with mass spectroscopy analysis of volatile organic compounds in wheat flour and wheat-bas...
  • 6.8 Gas chromatography coupled with mass spectroscopy-based metabolomics in wheat study
  • 6.9 Gas chromatography coupled with mass spectroscopy wheat authentication
  • 6.10 Gas chromatography coupled with mass spectroscopy in wheat and wheat-based food spoilage and storage.
  • 6.11 Future gas chromatography coupled with mass spectroscopy application in wheat food safety
  • 6.12 Conclusions
  • References
  • 7. Electrochemical sensors coupled with machine learning for food safety and quality inspection
  • 7.1 Introduction
  • 7.2 Electrochemical sensor types used in food science and technology
  • 7.3 Machine learning techniques used in food science and technology
  • 7.4 Machine learning algorithms applied to food safety and quality inspection
  • 7.5 Machine learning applied to electrochemical sensors for monitoring food contaminants
  • 7.6 Conclusions and perspectives
  • References
  • Index
  • Back Cover.

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