Agri-product such as grains, fruits and vegetables play a very important role in people's daily life. The agri-product quality directly affects human life and health. Agri-product quality refers to the quality characteristics acceptable to consumers, which mainly includes external factors such as size, shape, color, defect and texture, and internal factors such as physical properties, chemical composition and tissue diseases. Generally speaking, variety, climate, soil, cultivation techniques, diseases and pests are all factors that affect the agri-product quality. Traditional methods for agri-product quality evaluation are time-consuming, complex, and expensive. With the continuous development of modern science and technology, rapid and nondestructive detection technologies are applied to evaluate the quality of agri-product. These technologies could obtain the optical, acoustics and electrical properties of a specific substance and then reveal the appearance and internal quality of the agri-product. Furthermore, the trend today is that consumers have become more exigent for information about the products they purchase, which makes the nondestructive detection technology has more important application value in the field of agri-product quality evaluation.

With rapid progress being made in both theory and practical applications, Artificial Intelligence (AI) is transforming every aspect of life and leading the world towards a sustainable future. AI technology is fundamentally and radically affecting agriculture with a move towards smart systems. The outcome of this transition is improved efficiency, reduced environmental pollution, and enhanced productivity of crops. Nondestructive Evaluation of Agro-products by Intelligent Sensing Techniques is a reference which provides readers timely updates in the progress of intelligent sensing techniques used for nondestructive evaluation of agro-products. Chapters, each contributed by experts in food safety and technology, describe existing and innovative techniques that could be or have been applied to agro-products quality and safety evaluation, processing, harvest, traceability, and so on. The book includes 11 individual chapters, with each chapter focusing on a specific aspect of intelligent sensing techniques applied in agriculture. Specifically, the first chapter introduces the reader to representative techniques and methods for nondestructive evaluation. Subsequent chapters present detailed information about the processing and quality evaluation of agro-products (e.g., fruits, and vegetables), food grading, food tracing, and the use of robots for harvesting specialty crops. Key Features: - 11 chapters, contributed by experts that cover basic and applied research in agriculture - introduces readers to nondestructive evaluation techniques - covers food quality evaluation processes - covers food grading and traceability systems - covers frontier topics that represent future trends (robots and UAVs used in agriculture) - familiarizes the readers with several intelligent sensing technologies used in the agricultural sector (including machine vision, near-infrared spectroscopy, hyperspectral/multispectral imaging, bio-sensing, multi-technology fusion detection) - provides bibliographic references for further reading - gives applied examples on both common and specialty crops This reference is intended as a source of updated information for consultants, students and academicians involved in agriculture, crops science and food biotechnology. Professionals involved in food safety and security planning and policymaking will also benefit from the information presented by the authors.

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)

Colorimetric Sensors: Techniques to Measure Food Safety and Quality explores the latest advancements in colorimetric sensors/indicators and their applications. It consolidates state-of-the-art developments and current approaches in the fabrication of colorimetric sensors/indicators for cutting-edge applications. This book documents the principles of colorimetric sensors, sensor fabrication and characterization, sensitivity and detection limits of colorimetric sensors based on natural pigments, synthetic dyes, and nanotechnologies, as well as safety, quality controls, and regulatory aspects, followed by an assessment of their safety and quality. In addition, global trends in the application of colorimetric sensors in monitoring food freshness, challenges, marketing, and potential future development applications are addressed in detail. How the applications of colorimetric sensors/indicators in the analysis of cereal and cereal-based products, meat and meat products, liquid and semiliquid foods, food authentication, food toxicants, and pathogens, among others, is also discussed. This book can be used as a textbook for graduate students, a reference book for medical biologists, nanobiotechnologists, nanoengineers, agricultural scientists, and general biologists, and an inspiration for industrialists and policymakers studying smart nanomaterials. Graduate students and food scientists of all levels will also benefit. - Serves as a valuable source for researchers interested in the fundamental, basic, and modern applications of colorimetric sensors/intelligent food packaging - Presents colorimetric sensors for use as rapid and cost-effective analytical tools to measure food safety and quality - Covers colorimetric sensors/intelligent food packaging fabricated from natural, and synthetic dyes, and nanotechnology-based biomolecules for the assessment of food safety and quality - Demonstrates methods for evaluating the authenticity and odorants crucial to consumer acceptance of food products - Considers future industrial application, commercialization, regulatory aspects of colorimetric sensors/ indicators, and global trends for monitoring food freshness

Intelligent agriculture is the inevitable trend of future agriculture. As the brain of intelligent agriculture, advanced sensors determine the degree of agricultural environment and crop perception. However, an outstanding problem is the long-standing lack of effective sensing and monitoring tools in agriculture. Most information still relies on time-consuming and complex laboratory analysis and can only be off-line measured. Therefore, in-situ, on-line and sensitive methods for monitoring information about the agricultural environment and crops are urgently needed. With the development of material science, manufacturing technology and spectroscopy, more and more fast and high-precision spectroscopic methods and sensors are applied in the agricultural environment, livestock breeding and crop. Especially with the development of spectral enhancement, image processing and deep learning techniques, the study of the advanced spectroscopic methods to rapidly and precisely detect heavy metals and nutrients in the soil, harmful gas, water pollutant and crop stress will reduce the probability of subjective error judgment and improves agricultural management and production efficiency. Application of spectroscopy in an agricultural environment and livestock breeding is a research topic of Frontiers in Physics that publishes original research on the field of agricultural physics. And the aim of this research topic is to explore novel and groundbreaking spectroscopic methods to rapidly and in-situ detect information about the agricultural environment, livestock breeding and crop stress, which could be beneficial in the development of Intelligent agriculture.

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.