| Literature DB >> 33401804 |
Yuan-Yuan Pu1, Yao-Ze Feng1, Da-Wen Sun1.
Abstract
Objective quality assessment and efficacious safety surveillance for agricultural and food products are inseparable from innovative techniques. Hyperspectral imaging (HSI), a rapid, nondestructive, and chemical-free method, is now emerging as a powerful analytical tool for product inspection by simultaneously offering spatial information and spectral signals from one object. This paper focuses on recent advances and applications of HSI in detecting, classifying, and visualizing quality and safety attributes of fruits and vegetables. First, the basic principles and major instrumental components of HSI are presented. Commonly used methods for image processing, spectral pretreatment, and modeling are summarized. More importantly, morphological calibrations that are essential for nonflat objects as well as feature wavebands extraction for model simplification are provided. Second, in spite of the physical and visual attributes (size, shape, weight, color, and surface defects), applications from the last decade are reviewed specifically categorized into textural characteristics inspection, biochemical components detection, and safety features assessment. Finally, technical challenges and future trends of HSI are discussed.Keywords: classification; fruits and vegetables; hyperspectral imaging; quality assessment; safety inspection
Year: 2015 PMID: 33401804 DOI: 10.1111/1541-4337.12123
Source DB: PubMed Journal: Compr Rev Food Sci Food Saf ISSN: 1541-4337 Impact factor: 12.811