Nondestructive freshness evaluation of mackerel fish using Vis/NIR hyperspectral imaging and multivariate analysis
Nondestructive freshness evaluation models for chub mackerel (Scomber japonicus) fillets were developed using visible/near-infrared (Vis/NIR) hyperspectral imaging and multivariate regression analysis. Total 96 mackerel samples were investigated during 6 days of storage under five different conditio...
| Main Authors: | , , , , , , , , , , |
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| Format: | Article |
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Elsevier
2024
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| Online Access: | http://psasir.upm.edu.my/id/eprint/112812/ |
| _version_ | 1848866043971239936 |
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| author | Ryu, Jiwon Hong, Suk-Ju Park, Seongmin Kim, Eungchan Lee, Chang-Hyup Kim, Sungjay Ismail, Azfar Lee, ChangSug Kim, DongHee Jo, Cheorun Kim, Ghiseok |
| author_facet | Ryu, Jiwon Hong, Suk-Ju Park, Seongmin Kim, Eungchan Lee, Chang-Hyup Kim, Sungjay Ismail, Azfar Lee, ChangSug Kim, DongHee Jo, Cheorun Kim, Ghiseok |
| author_sort | Ryu, Jiwon |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | Nondestructive freshness evaluation models for chub mackerel (Scomber japonicus) fillets were developed using visible/near-infrared (Vis/NIR) hyperspectral imaging and multivariate regression analysis. Total 96 mackerel samples were investigated during 6 days of storage under five different conditions for measurement of pH, total volatile basic nitrogen (TVB-N), and K values along with acquisition of hyperspectral images. With partial least squares regression (PLSR) and support vector regression (SVR) along with wavelength selection method using Variables Importance in Projection (VIP) scores, performances of PLSR, VIP-PLSR, SVR, and VIP-SVR models were evaluated and compared. The VIP-PLSR models showed the best performance for predicting the freshness indicators, with R2 values of 0.86, 0.86, and 0.91 for pH, TVB-N, and K values, respectively. Furthermore, it was shown that the identification and removal of noise pixels from the hyperspectral data based on correlation analysis was effective in improving the regression results. © 2024 Elsevier Ltd |
| first_indexed | 2025-11-15T14:14:20Z |
| format | Article |
| id | upm-112812 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T14:14:20Z |
| publishDate | 2024 |
| publisher | Elsevier |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1128122024-11-11T03:35:10Z http://psasir.upm.edu.my/id/eprint/112812/ Nondestructive freshness evaluation of mackerel fish using Vis/NIR hyperspectral imaging and multivariate analysis Ryu, Jiwon Hong, Suk-Ju Park, Seongmin Kim, Eungchan Lee, Chang-Hyup Kim, Sungjay Ismail, Azfar Lee, ChangSug Kim, DongHee Jo, Cheorun Kim, Ghiseok Nondestructive freshness evaluation models for chub mackerel (Scomber japonicus) fillets were developed using visible/near-infrared (Vis/NIR) hyperspectral imaging and multivariate regression analysis. Total 96 mackerel samples were investigated during 6 days of storage under five different conditions for measurement of pH, total volatile basic nitrogen (TVB-N), and K values along with acquisition of hyperspectral images. With partial least squares regression (PLSR) and support vector regression (SVR) along with wavelength selection method using Variables Importance in Projection (VIP) scores, performances of PLSR, VIP-PLSR, SVR, and VIP-SVR models were evaluated and compared. The VIP-PLSR models showed the best performance for predicting the freshness indicators, with R2 values of 0.86, 0.86, and 0.91 for pH, TVB-N, and K values, respectively. Furthermore, it was shown that the identification and removal of noise pixels from the hyperspectral data based on correlation analysis was effective in improving the regression results. © 2024 Elsevier Ltd Elsevier 2024 Article PeerReviewed Ryu, Jiwon and Hong, Suk-Ju and Park, Seongmin and Kim, Eungchan and Lee, Chang-Hyup and Kim, Sungjay and Ismail, Azfar and Lee, ChangSug and Kim, DongHee and Jo, Cheorun and Kim, Ghiseok (2024) Nondestructive freshness evaluation of mackerel fish using Vis/NIR hyperspectral imaging and multivariate analysis. Journal of Food Engineering, 377. art. no. 112086. pp. 1-12. ISSN 0260-8774 https://www.sciencedirect.com/science/article/abs/pii/S0260877424001523?via%3Dihub 10.1016/j.jfoodeng.2024.112086 |
| spellingShingle | Ryu, Jiwon Hong, Suk-Ju Park, Seongmin Kim, Eungchan Lee, Chang-Hyup Kim, Sungjay Ismail, Azfar Lee, ChangSug Kim, DongHee Jo, Cheorun Kim, Ghiseok Nondestructive freshness evaluation of mackerel fish using Vis/NIR hyperspectral imaging and multivariate analysis |
| title | Nondestructive freshness evaluation of mackerel fish using Vis/NIR hyperspectral imaging and multivariate analysis |
| title_full | Nondestructive freshness evaluation of mackerel fish using Vis/NIR hyperspectral imaging and multivariate analysis |
| title_fullStr | Nondestructive freshness evaluation of mackerel fish using Vis/NIR hyperspectral imaging and multivariate analysis |
| title_full_unstemmed | Nondestructive freshness evaluation of mackerel fish using Vis/NIR hyperspectral imaging and multivariate analysis |
| title_short | Nondestructive freshness evaluation of mackerel fish using Vis/NIR hyperspectral imaging and multivariate analysis |
| title_sort | nondestructive freshness evaluation of mackerel fish using vis/nir hyperspectral imaging and multivariate analysis |
| url | http://psasir.upm.edu.my/id/eprint/112812/ http://psasir.upm.edu.my/id/eprint/112812/ http://psasir.upm.edu.my/id/eprint/112812/ |