Classification of organic beef freshness using VNIR hyperspectral imaging. (July 2017)
- Record Type:
- Journal Article
- Title:
- Classification of organic beef freshness using VNIR hyperspectral imaging. (July 2017)
- Main Title:
- Classification of organic beef freshness using VNIR hyperspectral imaging
- Authors:
- Crichton, Stuart O.J.
Kirchner, Sascha M.
Porley, Victoria
Retz, Stefanie
von Gersdorff, Gardis
Hensel, Oliver
Weygandt, Martin
Sturm, Barbara - Abstract:
- Abstract: Consumer trust in the food industry is heavily reliant upon accurate labelling of meat products. As such, methods, which can verify whether meat is correctly labelled are of great value to producers, retailers, and consumers. This paper illustrates two approaches to classify between, fresh and frozen thawed, and in a novel manner matured and matured frozen-thawed, as well as fresh and matured beef using the 500–1010 nm waveband, captured using hyperspectral imaging, and CIELAB measurements. The results show successful classification based upon CIELAB between 1) fresh and frozen-thawed (CCR = 0.93), and 2) fresh and matured (CCR = 0.92). With successful classification between matured and matured frozen-thawed beef using the entire spectral range (CCR = 1.00). The performance of reduced spectral models is also investigated. Overall it was found that CIELAB co-ordinates can be used for successful classification for all comparisons except between matured and matured frozen-thawed. Biochemical and physical changes of the meat are thoroughly discussed for each condition. Highlights: Spectral changes introduced by freezing-thawing are similar for both fresh and matured beef. VNIR region aids near optimal classification of all beef conditions. Chromatic changes differ to a greater extent with fresh beef, than with matured. CIELAB chromaticity values prove a more viable, near optimal, basis for classification. Full spectrum must be used for classification between maturedAbstract: Consumer trust in the food industry is heavily reliant upon accurate labelling of meat products. As such, methods, which can verify whether meat is correctly labelled are of great value to producers, retailers, and consumers. This paper illustrates two approaches to classify between, fresh and frozen thawed, and in a novel manner matured and matured frozen-thawed, as well as fresh and matured beef using the 500–1010 nm waveband, captured using hyperspectral imaging, and CIELAB measurements. The results show successful classification based upon CIELAB between 1) fresh and frozen-thawed (CCR = 0.93), and 2) fresh and matured (CCR = 0.92). With successful classification between matured and matured frozen-thawed beef using the entire spectral range (CCR = 1.00). The performance of reduced spectral models is also investigated. Overall it was found that CIELAB co-ordinates can be used for successful classification for all comparisons except between matured and matured frozen-thawed. Biochemical and physical changes of the meat are thoroughly discussed for each condition. Highlights: Spectral changes introduced by freezing-thawing are similar for both fresh and matured beef. VNIR region aids near optimal classification of all beef conditions. Chromatic changes differ to a greater extent with fresh beef, than with matured. CIELAB chromaticity values prove a more viable, near optimal, basis for classification. Full spectrum must be used for classification between matured beef conditions. … (more)
- Is Part Of:
- Meat science. Volume 129(2017)
- Journal:
- Meat science
- Issue:
- Volume 129(2017)
- Issue Display:
- Volume 129, Issue 2017 (2017)
- Year:
- 2017
- Volume:
- 129
- Issue:
- 2017
- Issue Sort Value:
- 2017-0129-2017-0000
- Page Start:
- 20
- Page End:
- 27
- Publication Date:
- 2017-07
- Subjects:
- Beef -- Chromaticity -- Classification -- Freezing -- Hyperspectral -- Maturation -- Quality -- Storage -- Support vector machines -- SVM -- VNIR
Meat -- Periodicals
Meat industry and trade -- Periodicals
Viande -- Périodiques
Viande -- Industrie -- Périodiques
Meat
Meat industry and trade
Periodicals
641.36 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03091740 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.meatsci.2017.02.005 ↗
- Languages:
- English
- ISSNs:
- 0309-1740
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5413.796500
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- 654.xml