Hyperspectral Imaging for Food Quality Analysis and Control

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.




Readership
Food engineers and technologists working in research, product and process development, and operations.
Secondary audience: Undergraduate and graduate food science students exploring food quality and control

Contents
Part I: Fundamentals; Principles of Hyperspectral Imaging Technology; Spectral Pre-Processing Techniques; Hypercube Classification Methods; Hyperspectral Image Processing Techniques; Hyperspectral Imaging Instruments; Part II: Applications; Pork Quality Using a Hyperspectral Imaging System; Automated Poultry Carcass Inspection by Hyperspectral-Multispectral Line-Scan Imaging System; Quality Evaluation of Fish Fillets by Hyperspectral Imaging; Bruise Detection of Apples Using Hyperspectral Imaging; Analysis of Hyperspectral Images of Citrus Fruits; Using NIR Hyperspectral Imaging for Bruise Detection of Strawberr; Visualization of Sugar Distribution of Melons by Hyperspectral Technique; Measuring Ripening of Tomatoes Using Imaging Spectrometry; Hyperspectral Reflectance Imaging for Detection of Bruising on Pickling Cucumber; Classification of Wheat Kernels Using Near-Infrared Reflectance Hyperspectral Imaging.

Author Information
Edited by Da-Wen Sun, National University of Ireland, Earlsfort Terrace, Dublin