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Hardcover. Condizione: New. Brand new book, sourced directly from publisher. Dispatch time is 6-7 days from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

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Hardcover. Condizione: new. Hardcover. In processing food, hyperspectral imaging, combined with intelligent software, enables digital sorters (or optical sorters) to identify and remove defects and foreign material that are invisible to traditional camera and laser sorters. Hyperspectral Imaging Analysis and Applications for Food Quality explores the theoretical and practical issues associated with the development, analysis, and application of essential image processing algorithms in order to exploit hyperspectral imaging for food quality evaluations. It outlines strategies and essential image processing routines that are necessary for making the appropriate decision during detection, classification, identification, quantification, and/or prediction processes.Features Covers practical issues associated with the development, analysis, and application of essential image processing for food quality applications Surveys the breadth of different image processing approaches adopted over the years in attempting to implement hyperspectral imaging for food quality monitoring Explains the working principles of hyperspectral systems as well as the basic concept and structure of hyperspectral data Describes the different approaches used during image acquisition, data collection, and visualization The book is divided into three sections. Section I discusses the fundamentals of Imaging Systems: How can hyperspectral image cube acquisition be optimized? Also, two chapters deal with image segmentation, data extraction, and treatment. Seven chapters comprise Section II, which deals with Chemometrics. One explains the fundamentals of multivariate analysis and techniques while in six other chapters the reader will find information on and applications of a number of chemometric techniques: principal component analysis, partial least squares analysis, linear discriminant model, support vector machines, decision trees, and artificial neural networks. In the last section, Applications, numerous examples are given of applications of hyperspectral imaging systems in fish, meat, fruits, vegetables, medicinal herbs, dairy products, beverages, and food additives. This book explores issues associated with the development, analysis, and application of essential image processing algorithms. It outlines strategies and essential image processing routines needed for making the appropriate decision during detection, classification, identification, quantification and/or prediction processes. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

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Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

Condizione: New.

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Condizione: New. 1st edition NO-PA16APR2015-KAP.

Hardcover. Condizione: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.

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Condizione: Sehr gut. Zustand: Sehr gut | Seiten: 284 | Sprache: Englisch | Produktart: Bücher | In processing food, hyperspectral imaging, combined with intelligent software, enables digital sorters (or optical sorters) to identify and remove defects and foreign material that are invisible to traditional camera and laser sorters. Hyperspectral Imaging Analysis and Applications for Food Quality explores the theoretical and practical issues associated with the development, analysis, and application of essential image processing algorithms in order to exploit hyperspectral imaging for food quality evaluations. It outlines strategies and essential image processing routines that are necessary for making the appropriate decision during detection, classification, identification, quantification, and/or prediction processes. Features Covers practical issues associated with the development, analysis, and application of essential image processing for food quality applications Surveys the breadth of different image processing approaches adopted over the years in attempting to implement hyperspectral imaging for food quality monitoring Explains the working principles of hyperspectral systems as well as the basic concept and structure of hyperspectral data Describes the different approaches used during image acquisition, data collection, and visualization The book is divided into three sections. Section I discusses the fundamentals of Imaging Systems: How can hyperspectral image cube acquisition be optimized? Also, two chapters deal with image segmentation, data extraction, and treatment. Seven chapters comprise Section II, which deals with Chemometrics. One explains the fundamentals of multivariate analysis and techniques while in six other chapters the reader will find information on and applications of a number of chemometric techniques: principal component analysis, partial least squares analysis, linear discriminant model, support vector machines, decision trees, and artificial neural networks. In the last section, Applications, numerous examples are given of applications of hyperspectral imaging systems in fish, meat, fruits, vegetables, medicinal herbs, dairy products, beverages, and food additives.…

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Condizione: New. In English.

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Hardcover. Condizione: Brand New. 280 pages. 10.25x7.00x0.75 inches. In Stock.

Hardcover. Condizione: Brand New. 344 pages. 10.00x7.00x10.00 inches. In Stock.

Hardcover. Condizione: new. Hardcover. In processing food, hyperspectral imaging, combined with intelligent software, enables digital sorters (or optical sorters) to identify and remove defects and foreign material that are invisible to traditional camera and laser sorters. Hyperspectral Imaging Analysis and Applications for Food Quality explores the theoretical and practical issues associated with the development, analysis, and application of essential image processing algorithms in order to exploit hyperspectral imaging for food quality evaluations. It outlines strategies and essential image processing routines that are necessary for making the appropriate decision during detection, classification, identification, quantification, and/or prediction processes.Features Covers practical issues associated with the development, analysis, and application of essential image processing for food quality applications Surveys the breadth of different image processing approaches adopted over the years in attempting to implement hyperspectral imaging for food quality monitoring Explains the working principles of hyperspectral systems as well as the basic concept and structure of hyperspectral data Describes the different approaches used during image acquisition, data collection, and visualization The book is divided into three sections. Section I discusses the fundamentals of Imaging Systems: How can hyperspectral image cube acquisition be optimized? Also, two chapters deal with image segmentation, data extraction, and treatment. Seven chapters comprise Section II, which deals with Chemometrics. One explains the fundamentals of multivariate analysis and techniques while in six other chapters the reader will find information on and applications of a number of chemometric techniques: principal component analysis, partial least squares analysis, linear discriminant model, support vector machines, decision trees, and artificial neural networks. In the last section, Applications, numerous examples are given of applications of hyperspectral imaging systems in fish, meat, fruits, vegetables, medicinal herbs, dairy products, beverages, and food additives. This book explores issues associated with the development, analysis, and application of essential image processing algorithms. It outlines strategies and essential image processing routines needed for making the appropriate decision during detection, classification, identification, quantification and/or prediction processes. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Hardcover. Condizione: new. Hardcover. In todays world, ensuring the safety and quality of food is more critical than ever. At the same time, the need to reduce the environmental impact of laboratory practices is becoming a top priority across the scientific community. Green Analytical Chemistry in Food Analysis bridges these two essential goals, presenting a comprehensive and forward-thinking guide to apply green chemistry principles in the analytical evaluation of food.This book is a response to the growing demand for environmentally responsible techniques in food testing methods that do not sacrifice analytical accuracy, sensitivity, or precision. It explores how green analytical chemistry (GAC) can transform every step of the food analysis process, from sample collection and preparation to separation, detection, and data processing. Through a combination of modern technologies, novel methodologies, and sustainable thinking, the field is redefining how we approach contaminants, residues, and nutritional profiling in food.Key topics include Green Sample Preparation: Minimizing solvent usage and adopting eco-friendly extraction methods Sustainable Separation and Detection: Innovations in chromatography, spectrometry, titrimetry, and gravimetry with reduced chemical and energy footprints Cleaner Alternatives: Natural indicators, alternative solvents, and energy-efficient instruments Miniaturization and Direct Analysis: Reducing waste through compact, high-efficiency systems Advanced Tools: Chemometric and computational approaches to streamline processes and reduce laboratory interventions Real-World Applications: Case studies focusing on pesticide residues, mycotoxins, heavy metals, and other critical food contaminants Scoring Greenness: Calculation of green score using different available metrices with examples Concepts and Principles: Concepts and principles of GAC explained in simplest manner to understand in first time.Whether youre an analytical chemist, food scientist, environmental researcher, or student, this book offers valuable insights into implementing greener methods that meet todays strict regulatory standards while supporting global sustainability goals. Green Analytical Chemistry in Food Analysis is more than a technical resource it is a call to action for a cleaner, safer, and more responsible future in food science. Ensuring the safety of food is more critical than ever and reducing the environmental impact of laboratory practices is becoming a priority across the scientific community. Green Analytical Chemistry in Food Analysis bridges these goals, presenting a comprehensive guide to green chemistry principles in the evaluation of food. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Condizione: new. Hardcover. In todays world, ensuring the safety and quality of food is more critical than ever. At the same time, the need to reduce the environmental impact of laboratory practices is becoming a top priority across the scientific community. Green Analytical Chemistry in Food Analysis bridges these two essential goals, presenting a comprehensive and forward-thinking guide to apply green chemistry principles in the analytical evaluation of food.This book is a response to the growing demand for environmentally responsible techniques in food testing methods that do not sacrifice analytical accuracy, sensitivity, or precision. It explores how green analytical chemistry (GAC) can transform every step of the food analysis process, from sample collection and preparation to separation, detection, and data processing. Through a combination of modern technologies, novel methodologies, and sustainable thinking, the field is redefining how we approach contaminants, residues, and nutritional profiling in food.Key topics include Green Sample Preparation: Minimizing solvent usage and adopting eco-friendly extraction methods Sustainable Separation and Detection: Innovations in chromatography, spectrometry, titrimetry, and gravimetry with reduced chemical and energy footprints Cleaner Alternatives: Natural indicators, alternative solvents, and energy-efficient instruments Miniaturization and Direct Analysis: Reducing waste through compact, high-efficiency systems Advanced Tools: Chemometric and computational approaches to streamline processes and reduce laboratory interventions Real-World Applications: Case studies focusing on pesticide residues, mycotoxins, heavy metals, and other critical food contaminants Scoring Greenness: Calculation of green score using different available metrices with examples Concepts and Principles: Concepts and principles of GAC explained in simplest manner to understand in first time.Whether youre an analytical chemist, food scientist, environmental researcher, or student, this book offers valuable insights into implementing greener methods that meet todays strict regulatory standards while supporting global sustainability goals. Green Analytical Chemistry in Food Analysis is more than a technical resource it is a call to action for a cleaner, safer, and more responsible future in food science. Ensuring the safety of food is more critical than ever and reducing the environmental impact of laboratory practices is becoming a priority across the scientific community. Green Analytical Chemistry in Food Analysis bridges these goals, presenting a comprehensive guide to green chemistry principles in the evaluation of food. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

HRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condizione: New. New Book. Delivered from our UK warehouse in 4 to 14 business days. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.

HRD. Condizione: New. New Book. Shipped from UK. THIS BOOK IS PRINTED ON DEMAND. Established seller since 2000.