Advanced Nondestructive Detection Technologies In Food

This book comprehensively introduces non-destructive methods for food quality (i.e. external, internal, sensory, components, and microbiological indicators) detection, through optics, acoustics, chemistry, imaging, and bionic sensing. It highlights in-situ detection of food quality and safety, including principles, signal processing, and analysis of data, non-destructive detection system, and application in the food industry for each method. First, this book introduces the principles and characteristics of various food non-destructive methods. As non-destructive measurements always involve obtaining big data for each testing, this book also describes in detail the signal and big data processing for each non-destructive method. The chapters also introduce the rapid portable detection equipment for food and agricultural products developed in recent years, as well as the intelligent monitoring equipment in the process of food processing. Relevant application cases are provided to help readers better understanding how to apply non-destructive technology for food quality detection. In the noninvasive measurement of food quality, this book has a systematic introduction of the detection principle, data processing, and rapid detection system, in-field detection case studies. This book is novel and practical and can be used as a professional textbook for undergraduates majoring in food science and engineering. It can also be used as a reference book for scientific research and technical personnel engaged in the field of food quality and safety detection.

Fast, non-destructive detection technology and equipment for food quality and safety is a powerful technical support tool to ensure the development of food industry informatization and intelligence, with the advantages of fast speed, convenient operation, and easy online inspection. During the past two decades, such technologies have found numerous successful applications for food and agricultural product detection and processing. Owing to improvements in the manufacturing of photoelectric sensor pieces and progress in artificial intelligence and software algorithms, fast non-destructive detection technologies are able to provide more accurate, reliable, and stable solutions for food quality and safety detection and processing. They are closely integrated with the Internet of Things and intelligent manufacturing, promoting a new wave of innovation in intelligent manufacturing in the food industry. The application of new sensing technology and equipment in the fast, non-destructive detection of food has always been at the forefront of scientific and technological research. This Special Issue aims to focus on the latest research progress of this application and jointly discuss the focus of development of this research direction.

The expert contributors to Nondestructive Testing of Food Quality clearly explain present industry advances and how to turn available instrumentation into valuable assets. Readers learn how the competencies of product knowledge, process understanding, instrumentation, principles of sensing, process control, and analytical methodology are required to turn an application into success. The broad-based coverage of topics addresses the most dominant sensor technologies keeping in mind the research initiatives advancing these technologies not only in food but also in the pharmaceutical sectors. Coverage includes: ultrasound, near infrared spectroscopy, mid-infrared spectroscopy, Raman spectroscopy, hyperspectral imaging systems, magnetic resonance imaging, electronic nose, z-nose, biosensors, microwave absorption, and nanoparticles and colloids as sensors.

This book consists of selected peer-reviewed articles from the International Conference on Computer Vision, High Performance Computing, Smart Devices and Networks (CHSN-2020), held at JNTU, Kakinada, India. The theme and areas of the conference include vast scope for latest concepts and trends in communication engineering, information theory and networks, signal, image and speech processing, wireless and mobile communication, Internet of Things, and cybersecurity for societal causes and humanitarian applications. ​

Digital agriculture is an emerging concept of modern farming that refers to managing farms using modern Engineering, Information and Communication Technologies (EICT) aiming at increasing the overall efficiency of agricultural production, improving the quantity and quality of products, and optimizing the human labor required and natural resource consumption in operations. This encyclopedia is designed to collect the summaries of knowledge on as many as subjects or aspects relevant to ECIT for digital agriculture, present such knowledge in entries, and arrange them alphabetically by articles titles. Springer Major Reference Works platform offers Live Update capability. Our reference work takes full advantage of this feature, which allows for continuous improvement or revision of published content electronically. The Editorial Board Dr. Irwin R. Donis-Gonzalez, University of California Davis, Dept. Biological and Agricultural Engineering, Davis, USA (Section: Postharvest Technologies) Prof. Paul Heinemann, Pennsylvania State University, Department Head of Agricultural and Biological Engineering, PA, USA (Section: Technologies for Crop Production) Prof. Manoj Karkee, Washington State University, Center for Precision and Automated Agricultural Systems, Washington, USA (Section: Robotics and Automation Technologies) Prof. Minzan Li, China Agricultural University, Beijing, China (Section: Precision Agricultural Technologies) Prof. Dikai Liu, University of Technology Sydney (UTS),Faculty of Engineering & Information Technologies, Broadway NSW, Australia (Section: AI, Information and Communication Technologies) Prof. Tomas Norton, University of Leuven, Dept. of Biosystems, Heverlee Leuven, Belgium (Section: Technologies for Animal and Aquatic Production) Dr. Manuela Zude-Sasse, Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB), Precision Horticulture, Potsdam, Germany (Section: Engineering and Mechanization Technologies)

Quality and safety of agricultural products affect human nutrition and health. Agricultural products results from natural process influenced by a myriad of factors (e.g., genetics, environments before harvest, postharvest storage conditions). These factors lead to significant variations of agricultural products, externally and internally, which consequently pose great challenges with quality and safety evaluation. Development of advanced techniques for measuring agricultural product quality and safety is thus crucial to ensuring high quality, nutritious and safe food supplies. Non-destructive sensing technologies (e.g., optical, thermal, ultrasonic), in conjunction with advanced data analytics (e.g., machine learning) and control and automation technology, have evolved as a potent means for augmenting existing quality and safety control efforts of agricultural products, which largely rely on human or manual product assessment. With advancements in sensor and computer technologies, recent years have seen commercial-scale adoption of non-destructive sensing technology (e.g., machine vision, near-infrared spectroscopy) for postharvest quality evaluation for a diversity of specialty crop products (e.g., apples, citrus, kiwi). However, there are still numerous challenges with robust, high-performance detection of many quality and safety issues, such as subsurface/internal defects and contamination. This Research Topic covers the latest developments and applications of advanced non-destructive sensing technologies for quality and safety evaluation of agricultural products, with relevant areas including but not limited to: 1. Assessment of external and internal quality; 2. Detection of subsurface and internal defects; 3. Safety detection of agricultural products; 4. Design and development of advanced sensing system; 5. Multi-modal sensing and applications; 6. Online product grading and sorting; 7. Data handling methods (e.g., machine learning)

This book offers readers an overview of some of the most recent advances in the field of detectors for X-ray imaging. Coverage includes both technology and applications, with an in-depth review of the research topics from leading specialists in the field. Emphasis is on high-Z materials like CdTe, CZT and perovskites, since they offer the best implementation possibilities for direct conversion X-ray detectors. Authors discuss material challenges, detector operation physics and technology and readout integrated circuits required to detect signals processes by high-Z sensors.

Even though the perception of food quality may depend on its hedonic and often subjective attributes, it is essential to quantitatively evaluate its quality and safety. Fortunately, the advent of sophisticated systems, including nondestructive testing techniques, has made it possible to definitively evaluate food quality. Reflecting these advances,