Chapter
1.5 Quality programs – steps towards sector quality agreements
1.5.2 A closed system concept – the case of IKB
1.5.3 An open sector system concept – the case of Q&S
1.6 The information challenge
1.6.1 Information clusters
1.6.2 Organisational alternatives
1.6.3 Data ownership and data markets
1.6.4 Added value of emerging information infrastructures
Chapter 2 Methodologies for Improved Quality Control Assessment of Food Products
2.2 Use of FT-IR spectroscopy as a tool for the analysis of polysaccharide food additives
2.2.1 Identification of polysaccharide food additives by FT-IR spectroscopy
2.2.2 Influence of hydration on FT-IR spectra of food additive polysaccharides
2.3 Use of outer product (OP) and orthogonal signal correction (OSC) PLS1 regressions in FT-IR spectroscopy for quantification purposes of complex food sample matrices
2.3.1 Outer product (OP)-PLS1 regression applied to the prediction of the degree of methylesterification of pectic polysaccharides in extracts of olive and pear pulps
2.3.2 Orthogonal signal correction (OSC)-PLS1 regression applied to white and red wine polymeric material extracts
2.4 Screening and distinction of coffee brews based on headspace – solid phase microextraction combined with gas chromatography in tandem with principal component analysis (HS-SPME/GC-PCA)
2.5 Comprehensive two-dimensional gas chromatography (GC × GC) combined with time-of-flight mass spectrometry (ToFMS) as a powerful tool for food products analysis
2.5.1 GC × GC-ToFMS principles and advantages
2.5.2 Beer volatile profiling by HS-SPME/GC × GC-ToFMS
2.6 Study of cork (from Quercus suber L.) – wine model interactions based on voltammetric multivariate analysis
2.6.1 Evaluation of the voltammetric analysis in what concerns the cyclic and square wave technique
2.6.2 Cyclic voltammetric analysis for cork classification
Chapter 3 Developments in Electronic Noses for Quality and Safety Control
3.2 Overview of classical techniques for food quality testing
3.2.1 Chromatographic techniques
3.2.2 Spectroscopic techniques
3.2.4 Biological techniques
3.3.1 Various definitions of eNose reported in literature
3.4 Instrumentation of eNose (Loutfi et al., 2015)
3.4.1.1 Analytical distillation methods
3.4.1.2 Headspace analysis methods (HS)
3.4.1.3 Direct extraction methods
3.4.2 Detection system (Loutfi et al., 2015)
3.4.2.1 Types of chemical sensors for gaseous environment
3.4.3 Data processing system
3.5 Recent developments in electronic nose applications for food quality
3.5.4 Fruits and vegetables
3.5.6.1 Non-alcoholic beverages
3.5.6.2 Alcoholic beverages
Chapter 4 Proteomics and Peptidomics as Tools for Detection of Food Contamination by Bacteria
4.2 Bacteria as food-borne pathogens
4.3 Gram-positive bacteria
4.4 Gram-negative bacteria
4.6 Detection of bacterial contamination in food
4.6.1 Omics methods for detection of bacteria
4.6.1.1 Proteomic and peptidomic methods
4.6.1.2 Affinity-based methods
4.6.1.3 Mass spectrometry-based methods
4.7 Analysis of bacterial toxins
Chapter 5 Metabolomics in Assessment of Nutritional Status
5.2 Usability of metabolomics in nutrition sciences
5.3 The metabolite complement in human studies
5.4 Metabolomics within the analysis of relationship between diet and health
5.5 Individual differences in metabolic and nutritional phenotype
5.6 Assessment of nutritional status, example studies
5.6.2 Deficiencies in particular nutrients
Chapter 6 Rapid Microbiological Methods in Food Diagnostics
6.1.1 Why the need for rapid methods – their benefits and potential limitations
6.2 Quantitative vs qualitative
6.3 Culture dependent vs independent
6.4 Automation and multi-pathogen detection
6.5 Separation and concentration
6.6 Rapid methods that are currently in the market
6.6.1.1 DEFT – direct epifluorescent filter technique
6.6.1.2 FISH – fluorescent in situ hybridisation
6.6.1.4 Enzyme-linked immunosorbent assay (ELISA)
6.6.1.7 Solid phase cytometry
6.6.2 Metabolism-based detection
6.6.2.1 Head space analysis
6.6.3.1 Bioluminescence/ATP detection
6.6.4 Immunological/ serological based
6.6.4.1 Antibody-based latex agglutination assay
6.6.4.2 Immunoprecipitation
6.6.4.3 Immunomagnetic separation (IMS)
6.6.5 Nucleic acid-based (molecular)
6.6.5.2 DNA colony hybridisation
6.6.5.3 Polymerase chain reaction (PCR)
6.6.5.5 Loop-mediated isothermal amplification (LAMP)
6.6.5.7 Quantitative PCR (qPCR)
6.6.5.9 Droplet digital PCR
6.6.5.10 16S Riboprinting
6.6.6 Next-generation technologies
6.6.7 Immunosensors or biosensors
6.6.7.1 Electronic nose sensors
6.6.7.2 Mass-sensitive biosensors
6.6.7.3 Surface plasmon resonance (SPR)
6.6.7.4 Raman and Fourier transform spectroscopy
6.6.7.5 Fourier transform infrared spectroscopy (FTIR)
6.6.7.6 Fibre optic biosensor
6.6.7.7 Aptamer-based biosensors
6.6.7.8 Nanotechnology for pathogen detection
Chapter 7 Molecular Technologies for the Detection and Characterisation of Food-Borne Pathogens
7.2 Hybridisation-based methods
7.2.1 DNA hybridisation methods
7.2.2 RNA hybridisation methods
7.2.2.1 Fluorescent in situ hybridisation (FISH)
7.3 Nucleic acid amplification methods
7.3.1 Polymerase chain reaction
7.3.2 RNA-based amplification assays
7.3.2.1 Reverse transcriptase polymerase chain reaction
7.3.2.2 Viability dyes in RT-PCR
7.3.3 Isothermal amplification
7.3.3.1 Loop-mediated isothermal amplification (LAMP)
7.3.3.2 Nucleic acid sequence-based amplification (NASBA)
7.4 Molecular characterisation methods
7.4.1 Pulse field gel electrophoresis (PFGE)
7.4.2 Amplified fragment length polymorphism (AFLP)
7.4.3 Restriction fragment length polymorphism (RFLP)
7.4.4 Multi-locus variable-number tandem repeat analysis (MLVA)
7.4.5 Multi-locus sequence typing (MLST)
7.4.6 Whole genome sequencing (WGS)
Chapter 8 DNA-based Detection of GM Ingredients
8.2.1 Sampling and DNA extraction
8.2.2 Choice of target sequences
8.2.3 Conventional end-point PCR
8.2.6 Multiplex approaches
8.3 Quantification of GMOs
8.5 Challenges in GMO detection
8.5.1 Influences of food composition and processing
8.5.3 Certified reference material
8.5.4 Sequence information
Chapter 9 Enzyme-based Sensors
9.1 Introduction to enzymatic biosensors
9.3 Enzymatic biosensors and the food industry
9.4 Biosensors for the analysis of main food components
9.5 Biosensors for contaminants
9.6 Food freshness indicators, antinutrients and additives
Chapter 10 Immunology-based Biosensors
10.2 Antibodies and biosensors
10.2.1 Immunochemiluminescence biosensors
10.2.2 Site-directed antibody immobilisation techniques for immunosensors
10.2.3 Label-free arrayed imaging reflectometry (AIR) detection platform
10.3 Immunoassays for detection of microorganisms
10.4 Immunosensors and cancer biomarkers-immunoarrays
10.4.1 Microfluidic paper-based analytical devices (mPADs)
Chapter 11 Graphene and Carbon Nanotube-Based Biosensors for Food Analysis
11.2 Biosensing devices based on graphene and CNTs and their applications in food analysis
11.3 Future trends and prospects
Chapter 12 Nanoparticles-Based Sensors
12.2 Nanoparticles for sensor technology
12.2.1 Electrochemical techniques
12.2.2 Spectroscopic techniques
12.2.3 Nanoparticles characterisation
12.3 Nanoparticles-based sensors: applications
12.3.1 Nanoparticles based-sensors for pesticides detection in foods
12.3.2 Nanoparticles-based sensors for antibiotics, growth enhancers and other veterinary drugs detection in foods
12.3.3 Nanoparticles based-sensors for mycotoxins detection in foods
12.3.4 Nanoparticles based-sensors for microorganisms’ detection in foods
12.3.5 Nanoparticles-based sensors for detecting food valuable constituents
12.3.6 Nanoparticles based-sensors for detecting food contaminants and adulterations
12.3.7 Nanoparticles-based sensors for detecting food dyes/additives
12.3.8 Nanoparticles based-sensors for detecting metal ions in foods
12.4 Conclusions and future trends
Chapter 13 New Technologies for Nanoparticles Detection in Foods
13.2 Nanoparticle properties and applications in food industry
13.2.1 Preparation of nanoparticles
13.2.1.1 Top-down strategy
13.2.1.2 Bottom-up strategy
13.2.2 Properties of nanoparticles
13.2.2.1 Organic nanoparticles
13.2.2.2 Inorganic nanoparticles
13.2.2.3 Combined nanoparticles
13.2.3 Applications of nanoparticles in food industry
13.2.3.1 Food functionalisation
13.2.3.2 Food packaging and quality preservation
13.3 Toxicity of food-related nanoparticles
13.3.1 Biological fate of ingested nanoparticles
13.3.2 Toxicity studies of engineered nanoparticles
13.4 Methods of nanoparticle detection in food
13.4.1 Direct visualisations of nanomaterials
13.4.2 Measurement of nanoparticles by light-scattering methods
13.4.3 Electrochemical methods in nanoparticle analysis
13.4.4 Food monitoring and safety controls
Chapter 14 Rapid Liquid Chromatographic Techniques for Detection of Key (Bio)chemical Markers
14.2 The fundamentals of liquid chromatography
14.2.3 Size exclusion HPLC
14.3 Advances in modern HPLC
14.4 Analysis of biochemical markers: applications for nutritional quality
14.4.2 Carbohydrate and carboxylic acids
14.4.4 Minerals and trace elements
14.5 Analysis of biochemical markers: applications for food quality
14.5.1 Biochemical compounds
14.5.1.2 Nucleotides and nucleosides
14.5.3 Markers for process control
14.6 Analysis of biochemical markers: applications for the detection of food adulterations
14.7 Analysis of biochemical markers: applications for food safety
14.7.1 Biochemical compounds
14.7.2 Veterinary drug residues in foods of animal origin
14.7.3 Antibiotic residues in foods of animal origin
Chapter 15 Olfactometry Detection of Aroma Compounds
15.2 Extraction of volatile compounds from foods for GC-olfactometry analysis (GC-O)
15.3 Olfactometry techniques
15.3.1.1 Dilution analysis method
15.3.1.2 Detection frequency method
15.3.1.3 Direct intensity method
15.3.2 Use of GC-O methodologies
15.4 Applications of GC-O in food industry
15.4.1 Identification of key aroma compounds in different foods
15.4.2 Identification of off-flavours for quality control
15.4.3 Application of GC-O to production processes
15.4.4 Application of GC-O to reformulation of food aromas
16.4 Process monitoring and quality control
16.10 Conclusion: future trends and the advantages and disadvantages of chemometrics
Chapter 17 Automated Sampling Procedures
17.2 Extraction techniques for sample preparation
17.2.1 Extraction from liquid samples
17.2.1.1 Liquid-liquid extraction
17.2.1.2 Solvent microextraction (SME)
17.2.1.3 Solid-phase extraction (SPE)
17.2.2 Extraction from solid samples
17.2.2.1 Matrix solid phase dispersion (MSPD)
17.2.2.2 Pressurised liquid extraction (PLE)
17.2.2.3 Super-heated water extraction (SHWE)
17.2.2.4 Supercritical fluid extraction (SFE)
17.2.2.5 Microwave- and ultrasound-assisted extraction
Chapter 18 The Market for Diagnostic Devices in the Food Industry
18.3.2 Biological hazards
18.3.3.3 Organic contaminants
18.3.5 Desired product constituents
18.3.6 Source of constituents
18.5 Influence of processing on product composition
18.5.1 Reactions between naturally present substances in food
18.5.2 Contamination with cleaning and disinfection agents
18.6 Processing parameters
18.6.2 Flow rate and velocity distribution/temperature and temperature distribution
18.6.3 Droplet, bubble, crystal size and distribution
18.6.4 Additional parameters for high-pressure processing
18.6.5 Pulsed electric field (PEF) processing
18.7 Packaging parameters
Advances in Food Diagnostics
Disclaimer: Any content in publications that violate the sovereignty, the constitution or regulations of the PRC is not accepted or approved by CNPIEC.
