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This e-book (purchase required) covers the most common non-destructive methods used in food quality and authenticity analysis, including machine vision, Spectroscopy, E-nose/tongue, Ultrasonics, and hyperspectral imaging.. While these methods have been in practice for some time, the technological advancements of the last decade have improved the precision and reliability of these tools, making them more popular. 

The book intends to be a research volume giving an overview of the dominant non-destructive methods, including the more novel technologies such as biosensors and terahertz application.  It brings together detailed information on all these most current advances in technology and elucidates their application in food processing. It covers theory, principle, recent advances and practical applications in food analysis.  The book is aimed at students, researchers, food trainers and industry personnel.

The chapters all focus on applications in food analysis

• Spectrtoscopy: Optical Methods. Visible, NIR, FTIR
• NMR
• Computer vision systems
• X-Ray, CT and MRI
• Hyperspectral imaging
• Multispectral imaging
• Backscattering imaging
• Biospeckly imaging
• Thermal imaging
• Terahertz spectroscopy
• Ultrasonics
• Electronic nose and electronic tongue
• Biosensors
• Techniques based on electrical properties of food
• Colour and texture measurements
• AI and Machine Learning
• Back matter

This pre-print (open access) reviews recent advances in electroanalytical methods.  These have the advantage, for food authenticity applications, that they are generally cost-effective and adaptable to field conditions. This review covers the application of these techniques across various food matrices, including olive oil, honey, milk, and alcoholic beverages.

The author reports that, by leveraging methodologies such as voltammetry and chemometric data processing, significant advancements have been achieved in identifying both specific and non-specific adulterants.

The review highlights novel electrode materials, such as carbon-based nanostructures and ionic liquids, which enhance sensitivity and selectivity. Additionally, electronic tongues employing multivariate analysis have shown promise in distinguishing authentic products from adulterated ones.

The integration of machine learning and miniaturization offers potential for on-site testing, making these techniques accessible to non-experts. Despite challenges such as matrix complexity and the need for robust validation, the author concludes that electroanalytical methods represent a transformative approach to food authentication.