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This book is about the novel aspects and future trends of the hyperspectral imaging in agriculture, food, and environment. The topics covered by this book are hyperspectral imaging and their applications in the nondestructive quality assessment of fruits and vegetables, hyperspectral imaging for assessing quality and safety of meat, multimode hyperspectral imaging for food quality and safety, models fitting to pattern recognition in hyperspectral images, sequential classification of hyperspectral images, graph construction for hyperspectral data unmixing, target visualization method to process hyperspectral image, and soil contamination mapping with hyperspectral imagery. This book is a general reference work for students, professional engineers, and readers with interest in the subject.
Hyperspectral imaging or imaging spectroscopy is a novel technology for acquiring and analysing an image of a real scene by computers and other devices in order to obtain quantitative information for quality evaluation and process control. Image processing and analysis is the core technique in computer vision. With the continuous development in hardware and software for image processing and analysis, the application of hyperspectral imaging has been extended to the safety and quality evaluation of meat and produce. Especially in recent years, hyperspectral imaging has attracted much research and development attention, as a result rapid scientific and technological advances have increasingly taken place in food and agriculture, especially on safety and quality inspection, classification and evaluation of a wide range of food products, illustrating the great advantages of using the technology for objective, rapid, non-destructive and automated safety inspection as well as quality control. Therefore, as the first reference book in the area, Hyperspectral Imaging Technology in Food and Agriculture focuses on these recent advances. The book is divided into three parts, which begins with an outline of the fundamentals of the technology, followed by full covering of the application in the most researched areas of meats, fruits, vegetables, grains and other foods, which mostly covers food safety and quality as well as remote sensing applicable for crop production. Hyperspectral Imaging Technology in Food and Agriculture is written by international peers who have both academic and professional credentials, with each chapter addressing in detail one aspect of the relevant technology, thus highlighting the truly international nature of the work. Therefore the book should provide the engineer and technologist working in research, development, and operations in the food and agricultural industry with critical, comprehensive and readily accessible information on the art and science of hyperspectral imaging technology. It should also serve as an essential reference source to undergraduate and postgraduate students and researchers in universities and research institutions.
This book is about the novel aspects and future trends of the hyperspectral imaging in agriculture, food, and environment. The topics covered by this book are hyperspectral imaging and their applications in the nondestructive quality assessment of fruits and vegetables, hyperspectral imaging for assessing quality and safety of meat, multimode hyperspectral imaging for food quality and safety, models fitting to pattern recognition in hyperspectral images, sequential classification of hyperspectral images, graph construction for hyperspectral data unmixing, target visualization method to process hyperspectral image, and soil contamination mapping with hyperspectral imagery. This book is a general reference work for students, professional engineers, and readers with interest in the subject.
Hyperspectral Imaging, Volume 32, presents a comprehensive exploration of the different analytical methodologies applied on hyperspectral imaging and a state-of-the-art analysis of applications in different scientific and industrial areas. This book presents, for the first time, a comprehensive collection of the main multivariate algorithms used for hyperspectral image analysis in different fields of application. The benefits, drawbacks and suitability of each are fully discussed, along with examples of their application. Users will find state-of-the art information on the machinery for hyperspectral image acquisition, along with a critical assessment of the usage of hyperspectral imaging in diverse scientific fields. - Provides a comprehensive roadmap of hyperspectral image analysis, with benefits and considerations for each method discussed - Covers state-of-the-art applications in different scientific fields - Discusses the implementation of hyperspectral devices in different environments
A comprehensive source of in-depth information provided on existing and emerging food technologies based on the electromagnetic spectrum Electromagnetic Technologies in Food Science examines various methods employed in food applications that are based on the entire electromagnetic (EM) spectrum. Focusing on recent advances and challenges in food science and technology, this is an up-to-date volume that features vital contributions coming from an international panel of experts who have shared both fundamental and advanced knowledge of information on the dosimetry methods, and on potential applications of gamma irradiation, electron beams, X-rays, radio and microwaves, ultraviolet, visible, pulsed light, and more. Organized into four parts, the text begins with an accessible overview of the physics of the electromagnetic spectrum, followed by discussion on the application of the EM spectrum to non-thermal food processing. The physics of infrared radiation, microwaves, and other advanced heating methods are then deliberated in detail—supported by case studies and examples that illustrate a range of both current and potential applications of EM-based methods. The concluding section of the book describes analytical techniques adopted for quality control, such as hyperspectral imaging, infrared and Raman spectroscopy. This authoritative book resource: Covers advanced theoretical knowledge and practical applications on the use of EM spectrum as novel methods in food processing technology Discusses the latest progress in developing quality control methods, thus enabling the control of continuous fast-speed processes Explores future challenges and benefits of employing electromagnetic spectrum in food technology applications Addresses emerging processing technologies related to improving safety, preservation, and overall quality of various food commodities Electromagnetic Technologies in Food Science is an essential reading material for undergraduate and graduate students, researchers, academics, and agri-food professionals working in the area of food preservation, novel food processing techniques and sustainable food production.
Based on the integration of computer vision and spectrscopy techniques, hyperspectral imaging is a novel technology for obtaining both spatial and spectral information on a product. Used for nearly 20 years in the aerospace and military industries, more recently hyperspectral imaging has emerged and matured into one of the most powerful and rapidly growing methods of non-destructive food quality analysis and control. Hyperspectral Imaging for Food Quality Analysis and Control provides the core information about how this proven science can be practically applied for food quality assessment, including information on the equipment available and selection of the most appropriate of those instruments. Additionally, real-world food-industry-based examples are included, giving the reader important insights into the actual application of the science in evaluating food products. - Presentation of principles and instruments provides core understanding of how this science performs, as well as guideline on selecting the most appropriate equipment for implementation - Includes real-world, practical application to demonstrate the viability and challenges of working with this technology - Provides necessary information for making correct determination on use of hyperspectral imaging
World population is growing at an alarming rate and is anticipated to reach about six billion by the end of year 2050. On the other hand, agricultural productivity is not increasing at a required rate to keep up with the food demand. The reasons for this are water shortages, depleting soil fertility and mainly various abiotic stresses. The fast pace at which developments and novel findings that are recently taking place in the cutting edge areas of molecular biology and basic genetics, have reinforced and augmented the efficiency of science outputs in dealing with plant abiotic stresses. In depth understanding of the stresses and their effects on plants is of paramount importance to evolve effective strategies to counter them. This book is broadly dived into sections on the stresses, their mechanisms and tolerance, genetics and adaptation, and focuses on the mechanic aspects in addition to touching some adaptation features. The chief objective of the book hence is to deliver state of the art information for comprehending the nature of abiotic stress in plants. We attempted here to present a judicious mixture of outlooks in order to interest workers in all areas of plant sciences.
Evaluating the performance of various types of hyperspectral vegetation indices in characterizing agricultural crops, this volume discusses non-invasive quantification of foliar pigments, leaf nitrogen concentration of cereal crop, the estimation of nitrogen content in crops and pastures, forest leaf chlorophyll content, among others. Each chapter reviews existing “state-of-art” knowledge, highlights the advances made, and provides guidance for appropriate use of hyperspectral images in study of vegetation. The concluding chapter provides readers with the editor’s view and guidance on the highlights and the essence of the Volume 2 and the editor’s perspective.
This book reviews the state of the art in algorithmic approaches addressing the practical challenges that arise with hyperspectral image analysis tasks, with a focus on emerging trends in machine learning and image processing/understanding. It presents advances in deep learning, multiple instance learning, sparse representation based learning, low-dimensional manifold models, anomalous change detection, target recognition, sensor fusion and super-resolution for robust multispectral and hyperspectral image understanding. It presents research from leading international experts who have made foundational contributions in these areas. The book covers a diverse array of applications of multispectral/hyperspectral imagery in the context of these algorithms, including remote sensing, face recognition and biomedicine. This book would be particularly beneficial to graduate students and researchers who are taking advanced courses in (or are working in) the areas of image analysis, machine learning and remote sensing with multi-channel optical imagery. Researchers and professionals in academia and industry working in areas such as electrical engineering, civil and environmental engineering, geosciences and biomedical image processing, who work with multi-channel optical data will find this book useful.
This book presents an integrated and multidisciplinary approach to quality and innovation in the food sector with particular emphasis on consumer perception of quality. Chapters cover such topics as identification of environmental variables, practices crops, and cultivars to improve nutritional and functional quality of different food matrices; increased preservation of biodiversity through the use of genetic resources; nutritional and functional characterization of food matrices; and evaluation of the main bioactive substances that give food its functional qualities.