Nondestructive Identification of Salmon Adulteration with Water Based on Hyperspectral Data
Joint Authors
Zhang, Xu
Wang, Huihui
Zhang, Tao
Wang, Biyao
Yan, Pengtao
Wang, Kunlun
Lv, Yan
Source
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-26
Country of Publication
Egypt
No. of Pages
10
Abstract EN
For the identification of salmon adulteration with water injection, a nondestructive identification method based on hyperspectral images was proposed.
The hyperspectral images of salmon fillets in visible and near-infrared ranges (390–1050 nm) were obtained with a system.
The original hyperspectral data were processed through the principal-component analysis (PCA).
According to the image quality and PCA parameters, a second principal-component (PC2) image was selected as the feature image, and the wavelengths corresponding to the local extremum values of feature image weighting coefficients were extracted as feature wavelengths, which were 454.9, 512.3, and 569.1 nm.
On this basis, the color combined with spectra at feature wavelengths, texture combined with spectra at feature wavelengths, and color-texture combined with spectra at feature wavelengths were independently set as the input, for the modeling of salmon adulteration identification based on the self-organizing feature map (SOM) network.
The distances between neighboring neurons and feature weights of the models were analyzed to realize the visualization of identification results.
The results showed that the SOM-based model, with texture-color combined with fusion features of spectra at feature wavelengths as the input, was evaluated to possess the best performance and identification accuracy is as high as 96.7%.
American Psychological Association (APA)
Zhang, Tao& Wang, Biyao& Yan, Pengtao& Wang, Kunlun& Zhang, Xu& Wang, Huihui…[et al.]. 2018. Nondestructive Identification of Salmon Adulteration with Water Based on Hyperspectral Data. Journal of Food Quality،Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1185071
Modern Language Association (MLA)
Zhang, Tao…[et al.]. Nondestructive Identification of Salmon Adulteration with Water Based on Hyperspectral Data. Journal of Food Quality No. 2018 (2018), pp.1-10.
https://search.emarefa.net/detail/BIM-1185071
American Medical Association (AMA)
Zhang, Tao& Wang, Biyao& Yan, Pengtao& Wang, Kunlun& Zhang, Xu& Wang, Huihui…[et al.]. Nondestructive Identification of Salmon Adulteration with Water Based on Hyperspectral Data. Journal of Food Quality. 2018. Vol. 2018, no. 2018, pp.1-10.
https://search.emarefa.net/detail/BIM-1185071
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1185071