Advanced Nondestructive Detection Technologies in Food

AvQuansheng Chen,Hao Lin

Inbunden, Engelska, 2021

1 608 kr

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Beskrivning

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.

Produktinformation

Utgivningsdatum:2021-08-28
Mått:155 x 235 x 24 mm
Vikt:751 g
Format:Inbunden
Språk:Engelska
Antal sidor:333
Förlag:Springer Verlag, Singapore
ISBN:9789811633591

Utforska kategorier

Kemi inom Naturvetenskap och teknik
Tillverkningsteknik inom Naturvetenskap och teknik

Mer om författaren

Quansheng Chen Dr. Quansheng Chen is a professor in the School of Food and Biological Engineering of Jiangsu University. He has been engaged in the research of non-destructive detection of food quality and safety for nearly twenty 20 years. His main research interest includes using NIR, computer vision, spectral imaging, and multi-sensors fusion technologies food quality and safety non-destructive detection, and real-time monitoring for food quality using non-destructive methods. Hao Lin Dr. Hao Lin is an associate professor in the School of Food and Biological Engineering of Jiangsu University. He has been engaged in the research of non-destructive detection of food quality and safety for fifteen years. His main research interest includes using NIR, bionic sensors, colorimetric sensors, acoustic sensor technologies for food quality and safety non-destructive detection, and the development of intelligent equipment. Jiewen Zhao Dr. Jiewen Zhao is a professor in the School of Food and Biological Engineering of Jiangsu University. He has been engaged in the research of non-destructive detection of food quality and safety for more than thirty years. His main research interest includes using NIR, computer vision, bionic sensors, spectral imaging and multi-sensors fusion technologies food quality and safety non-destructive detection, and online grading for food quality using non-destructive methods.

Innehållsförteckning

Chapter 1 Introduction. -Chapter 2 Computer Vision Technologies in Food.- Chapter 3 Near Infrared Spectroscopy Analysis in Food.- Chapter 4 Spectral Imaging Technologies in Food.- Chapter 5 CSAs Array Technologies in Food.- Chapter 6 Acoustic and Vibrating Signal Analysis Technologies in Food.- Chapter 7 Bionic Sensors Technologies in Food.- Chapter 8 Multi-Sensors data fusion Technologies in Food External and Internal Quality Comprehensive Evaluation.- Chapter 9 Intelligent and Portable Equipments of Nondestructve Detection Technologies in Food.- Chapter 10 Nondestructive Deatection Technologies for Real-time Monitoring Food Processing.