Abstract
Traditional methods are still widely used in most food industries due to the unavailability of smart alternatives. Traditional destructive methods are not suitable in today's hypercompetitive marketplace. Consequently, a cost-effective, efficient, rapid, and reliable method is required. In particular, there is a great interest in developing nondestructive optical technologies that have the capability of monitoring in a real-time assessment. Among them, hyperspectral imaging techniques have received ample attention. Hyperspectral imaging systems provide spatial and spectral details; therefore, these systems introduce new sensing facilities that enable improved inspection. Moreover, hyperspectral imaging can be used for online monitoring if properly optimized. This chapter first describes the fundamentals of hyperspectral imaging techniques, followed by an overview of multivariate data analysis, optimal wavelength selection, model evaluation, multivariate image analysis, and software for data/image analysis. Finally, the applications of hyperspectral imaging for evaluating quality, safety, and authenticity of muscle foods are illustrated.
Original language | English (US) |
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Title of host publication | Computer Vision Technology for Food Quality Evaluation |
Subtitle of host publication | Second Edition |
Editors | Da-Wen Sun |
Publisher | Academic Press |
Pages | 111-139 |
Number of pages | 29 |
Edition | 2 |
ISBN (Print) | 9780128022320 |
DOIs | |
State | Published - Apr 27 2016 |
Externally published | Yes |
Keywords
- Beef
- Chicken
- Fish
- Hyperspectral imaging
- Lamb
- Multispectral imaging
- Multivariate analysis
- Muscle foods
- Pork
ASJC Scopus subject areas
- Engineering(all)
- Agricultural and Biological Sciences(all)