N.C. Basantia – författare

In today’s 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 you’re an analytical chemist, food scientist, environmental researcher, or student, this book offers valuable insights into implementing greener methods that meet today’s 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.

In today's 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 you're an analytical chemist, food scientist, environmental researcher, or student, this book offers valuable insights into implementing greener methods that meet today's 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.

In today's 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 you're an analytical chemist, food scientist, environmental researcher, or student, this book offers valuable insights into implementing greener methods that meet today's 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.

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.

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.